title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate how
an idealized human agent can compute that which is not turing computable.
until someone is willing to grant me an cs.LO endorsement i'm feeling a
bit hesitant to go further into the arguments... idk u could tempt me
prolly Efn+
i'm willing to post the section headers as of now:
1 the halting problem--
2 the circle-free problem
-a2.1 turing's diagonal
-a2.2 a simpler form
3 the self-referential set-classification paradox generalized
-a3.1 clarification on self-reference
4 how undecidability is it?
-a4.1 reducing circle-free to halting
-a4.2 on the "existence" of recursive undecidability
5 rectifying EYou
-a5.1 bugfix: adding an identify check
-a5.2 bugfix: injecting a partial recognizer
-a5.3 a fallacy in turing's proof
6 the anti-diagonal problem
-a6.1 a proposed limit to undecidability within computing
-a6.2 a second fallacy in turing's paper
7 refuting the church turing thesis
-a7.1 the terminal machine
-a7.2 a record on the side
-a7.3 inject value and reduce
-a7.4 objective mechanics vs addressable simulation
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate how
an idealized human agent can compute that which is not turing computable.
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing computable? Much can be computed with a Turing computable partial
method.
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate how
an idealized human agent can compute that which is not turing computable.
until someone is willing to grant me an cs.LO endorsement i'm feeling a
bit hesitant to go further into the arguments... idk u could tempt me
prolly Efn+
i'm willing to post the section headers as of now:
1 the halting problem
2 the circle-free problem
2.1 turing's diagonal
2.2 a simpler form
3 the self-referential set-classification paradox generalized
3.1 clarification on self-reference
4 how undecidability is it?
4.1 reducing circle-free to halting
4.2 on the "existence" of recursive undecidability
5 rectifying EYou
5.1 bugfix: adding an identify check
5.2 bugfix: injecting a partial recognizer
5.3 a fallacy in turing's proof
6 the anti-diagonal problem
6.1 a proposed limit to undecidability within computing
6.2 a second fallacy in turing's paper
7 refuting the church turing thesis
7.1 the terminal machine
7.2 a record on the side
7.3 inject value and reduce
7.4 objective mechanics vs addressable simulation
On 08/26/2026 10:40 PM, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate how
an idealized human agent can compute that which is not turing computable.
until someone is willing to grant me an cs.LO endorsement i'm feeling a
bit hesitant to go further into the arguments... idk u could tempt me
prolly Efn+
i'm willing to post the section headers as of now:
1 the halting problem
2 the circle-free problem
-a 2.1 turing's diagonal
-a 2.2 a simpler form
3 the self-referential set-classification paradox generalized
-a 3.1 clarification on self-reference
4 how undecidability is it?
-a 4.1 reducing circle-free to halting
-a 4.2 on the "existence" of recursive undecidability
5 rectifying EYou
-a 5.1 bugfix: adding an identify check
-a 5.2 bugfix: injecting a partial recognizer
-a 5.3 a fallacy in turing's proof
6 the anti-diagonal problem
-a 6.1 a proposed limit to undecidability within computing
-a 6.2 a second fallacy in turing's paper
7 refuting the church turing thesis
-a 7.1 the terminal machine
-a 7.2 a record on the side
-a 7.3 inject value and reduce
-a 7.4 objective mechanics vs addressable simulation
What you might find is yourself establishing the _independence_
of various ordinary theorems vis-a-vis their conjecture, from
usual ordinary theories that you'll be finding have implicits
and stipulations that while so seemingly innocuous or plain,
were always inside a box that declared itself open and closed.
On 27/08/2026 1:40 PM, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
until someone is willing to grant me an cs.LO endorsement i'm feeling
a bit hesitant to go further into the arguments... idk u could tempt
me prolly Efn+
i'm willing to post the section headers as of now:
I'm also a little hesitant I'll understand your paper, but the following section headers are indeed enticing.-a Will you put the paper up some-
where plebs like me can read them, once you publish?
1 the halting problem
2 the circle-free problem
-a-a2.1 turing's diagonal
-a-a2.2 a simpler form
3 the self-referential set-classification paradox generalized
-a-a3.1 clarification on self-reference
4 how undecidability is it?
-a-a4.1 reducing circle-free to halting
-a-a4.2 on the "existence" of recursive undecidability
5 rectifying EYou
-a-a5.1 bugfix: adding an identify check
-a-a5.2 bugfix: injecting a partial recognizer
-a-a5.3 a fallacy in turing's proof
6 the anti-diagonal problem
-a-a6.1 a proposed limit to undecidability within computing
-a-a6.2 a second fallacy in turing's paper
7 refuting the church turing thesis
-a-a7.1 the terminal machine
-a-a7.2 a record on the side
-a-a7.3 inject value and reduce
-a-a7.4 objective mechanics vs addressable simulation
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing
computable? Much can be computed with a Turing computable partial
method.
On 27/08/2026 1:40 PM, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
until someone is willing to grant me an cs.LO endorsement i'm feeling
a bit hesitant to go further into the arguments... idk u could tempt
me prolly Efn+
i'm willing to post the section headers as of now:
I'm also a little hesitant I'll understand your paper, but the following section headers are indeed enticing.-a Will you put the paper up some-
where plebs like me can read them, once you publish?
1 the halting problem
2 the circle-free problem
-a-a2.1 turing's diagonal
-a-a2.2 a simpler form
3 the self-referential set-classification paradox generalized
-a-a3.1 clarification on self-reference
4 how undecidability is it?
-a-a4.1 reducing circle-free to halting
-a-a4.2 on the "existence" of recursive undecidability
5 rectifying EYou
-a-a5.1 bugfix: adding an identify check
-a-a5.2 bugfix: injecting a partial recognizer
-a-a5.3 a fallacy in turing's proof
6 the anti-diagonal problem
-a-a6.1 a proposed limit to undecidability within computing
-a-a6.2 a second fallacy in turing's paper
7 refuting the church turing thesis
-a-a7.1 the terminal machine
-a-a7.2 a record on the side
-a-a7.3 inject value and reduce
-a-a7.4 objective mechanics vs addressable simulation
On 8/27/26 7:34 AM, Ross Finlayson wrote:
On 08/26/2026 10:40 PM, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate how >>> an idealized human agent can compute that which is not turing
computable.
until someone is willing to grant me an cs.LO endorsement i'm feeling a
bit hesitant to go further into the arguments... idk u could tempt me
prolly Efn+
i'm willing to post the section headers as of now:
1 the halting problem
2 the circle-free problem
-a 2.1 turing's diagonal
-a 2.2 a simpler form
3 the self-referential set-classification paradox generalized
-a 3.1 clarification on self-reference
4 how undecidability is it?
-a 4.1 reducing circle-free to halting
-a 4.2 on the "existence" of recursive undecidability
5 rectifying EYou
-a 5.1 bugfix: adding an identify check
-a 5.2 bugfix: injecting a partial recognizer
-a 5.3 a fallacy in turing's proof
6 the anti-diagonal problem
-a 6.1 a proposed limit to undecidability within computing
-a 6.2 a second fallacy in turing's paper
7 refuting the church turing thesis
-a 7.1 the terminal machine
-a 7.2 a record on the side
-a 7.3 inject value and reduce
-a 7.4 objective mechanics vs addressable simulation
What you might find is yourself establishing the _independence_
while a particular number can be computed by an idealize human agent
(the anti-diagonal across turing computable sequences),
it is necessary that said number is not turing computable lest a contradiction would be generated as per turing's original paper /on computable numbers/
of various ordinary theorems vis-a-vis their conjecture, from
usual ordinary theories that you'll be finding have implicits
and stipulations that while so seemingly innocuous or plain,
were always inside a box that declared itself open and closed.
On 27/08/2026 3:49 PM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing
computable? Much can be computed with a Turing computable partial
method.
I previously gave this practical counter example, and you're welcome
to prove me wrong.
You pick up an Antikythera mechanism, and use it to compute something, anything.
Now, after that feat, how do you do this with a Turing machine?
-aYou can obviously simulate the Antikythera mechanism with a Turing> machine, but you cannot /compute/ as one.
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes
i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is
not turing computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a
function that is strictly outside the bounds of turing computability
If you can't simulate that agent with a Turing-complete computer you
cant use it for any computation. If you can you can compute the same
with a Turing machine.
computable? Much can be computed with a Turing computable partial
method.
at this point i suspect there to be machines which may not be
"computable" by any partial decider, but even that is just not quite
equal to what an idealized agent can mechanically prove in a finite
amount of steps (which is necessarily not computable by any turing
machine)
You can suspect anything but without a proof that is nothing.
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a function that is strictly outside the bounds of turing computability
computable? Much can be computed with a Turing computable partial
method.
at this point i suspect there to be machines which may not be
"computable" by any partial decider, but even that is just not quite
equal to what an idealized agent can mechanically prove in a finite
amount of steps (which is necessarily not computable by any turing machine)
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes
i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is
not turing computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a
function that is strictly outside the bounds of turing computability
If you can't simulate that agent with a Turing-complete computer you
cant use it for any computation. If you can you can compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two different
ways, which in of itself has not be proven.
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof, which can't be simulated by a turing machine because any value computed by a turing machine is necessarily addressable
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes
i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is >>>>>> not turing computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a
function that is strictly outside the bounds of turing computability
If you can't simulate that agent with a Turing-complete computer you
cant use it for any computation. If you can you can compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two different
ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You
may be able to compute some values of an uncomputable function but you
can't know that you can compute for arguments that will be given later
unless you have a method.
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably infinite address space and any finite or countably infinite is
accessible.
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>> i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is >>>>>> not turing computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a
function that is strictly outside the bounds of turing computability
If you can't simulate that agent with a Turing-complete computer you
cant use it for any computation. If you can you can compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two different
ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You
may be able to compute some values of an uncomputable function but you
can't know that you can compute for arguments that will be given later
unless you have a method.
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably infinite address space and any finite or countably infinite is
accessible.
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>> i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is >>>>>> not turing computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a
function that is strictly outside the bounds of turing computability
If you can't simulate that agent with a Turing-complete computer you
cant use it for any computation. If you can you can compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two different
ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You
may be able to compute some values of an uncomputable function but you
can't know that you can compute for arguments that will be given later
unless you have a method.
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably infinite address space and any finite or countably infinite is
accessible.
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:yes, i use the concept of an idealized human agent to compute a
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>>> i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which >>>>>>> is not turing computable.
Is there any way to prove that humans can compute anyhing not Turing >>>>>
function that is strictly outside the bounds of turing computability
If you can't simulate that agent with a Turing-complete computer you
cant use it for any computation. If you can you can compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two different
ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You
may be able to compute some values of an uncomputable function but you
can't know that you can compute for arguments that will be given later
unless you have a method.
my paper specifically details how that method can exist, and how the algorithm differs from all the partial classifiers found in the turing computable space, and why no turing machine can truly implement the objective total algorithm even if it is mechanically computable.
i might be the first to realize: algorithms exist independently in
abstract from the more concrete mechanical implementations found in
turing machine constructions, which are inherently more limited by their formally addressable nature.
this isn't like a bad thing either, turing machines are great and
incredibly useful. i'm trying to increase their productivity by
resolving their limitations more accurately so we stop tripping over the halting problem as excuse to not be proving correctness for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go about producing and maintaining computing infrastructure. the dumb fucking
corpo ratrace to nowhere instead of producing the systems we not only
need but deserve is just so ungodly
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably
infinite address space and any finite or countably infinite is
accessible.
it's not uncountability that prevents the addressing, it's a mechanical discontinuity, and i can only explain by properly describing the
justifying thought experiment
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:If you can't simulate that agent with a Turing-complete computer you >>>>> cant use it for any computation. If you can you can compute the same >>>>> with a Turing machine.
On 27/08/2026 08:40, dart200 wrote:yes, i use the concept of an idealized human agent to compute a
title of my next paper is tentative, but i'm kinda liking it.
yes i'm quite serious about refuting the church turing thesis. i >>>>>>>> demonstrate how an idealized human agent can compute that which >>>>>>>> is not turing computable.
Is there any way to prove that humans can compute anyhing not Turing >>>>>>
function that is strictly outside the bounds of turing computability >>>>>
that's just asserting the church-turing thesis at me in two
different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You
may be able to compute some values of an uncomputable function but you
can't know that you can compute for arguments that will be given later
unless you have a method.
my paper specifically details how that method can exist, and how the
algorithm differs from all the partial classifiers found in the turing
computable space, and why no turing machine can truly implement the
objective total algorithm even if it is mechanically computable.
You havn't posted a pointer to your article so we can't comment.
But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i might be the first to realize: algorithms exist independently in
abstract from the more concrete mechanical implementations found in
turing machine constructions, which are inherently more limited by
their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be described.
But there is no known way to describe an anlgorithm that cannot be
described as a Turing machine.
this isn't like a bad thing either, turing machines are great and
incredibly useful. i'm trying to increase their productivity by
resolving their limitations more accurately so we stop tripping over
the halting problem as excuse to not be proving correctness for every
single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go
about producing and maintaining computing infrastructure. the dumb
fucking corpo ratrace to nowhere instead of producing the systems we
not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably
infinite address space and any finite or countably infinite is
accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway
butthat does not prevent a simulation of full accessibility. Restrictions
in accessibility can also be simulated.
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:If you can't simulate that agent with a Turing-complete computer you >>>>> cant use it for any computation. If you can you can compute the same >>>>> with a Turing machine.
On 27/08/2026 08:40, dart200 wrote:yes, i use the concept of an idealized human agent to compute a
title of my next paper is tentative, but i'm kinda liking it. >>>>>>>> yes i'm quite serious about refuting the church turing thesis. i >>>>>>>> demonstrate how an idealized human agent can compute that which >>>>>>>> is not turing computable.
Is there any way to prove that humans can compute anyhing not Turing >>>>>>
function that is strictly outside the bounds of turing computability >>>>>
that's just asserting the church-turing thesis at me in two
different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You
may be able to compute some values of an uncomputable function but you
can't know that you can compute for arguments that will be given later
unless you have a method.
my paper specifically details how that method can exist, and how the
algorithm differs from all the partial classifiers found in the turing
computable space, and why no turing machine can truly implement the
objective total algorithm even if it is mechanically computable.
You havn't posted a pointer to your article so we can't comment.
But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i might be the first to realize: algorithms exist independently in
abstract from the more concrete mechanical implementations found in
turing machine constructions, which are inherently more limited by
their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be described.
But there is no known way to describe an anlgorithm that cannot be
described as a Turing machine.
this isn't like a bad thing either, turing machines are great and
incredibly useful. i'm trying to increase their productivity by
resolving their limitations more accurately so we stop tripping over
the halting problem as excuse to not be proving correctness for every
single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go
about producing and maintaining computing infrastructure. the dumb
fucking corpo ratrace to nowhere instead of producing the systems we
not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably
infinite address space and any finite or countably infinite is
accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway
butthat does not prevent a simulation of full accessibility. Restrictions
in accessibility can also be simulated.
On 27/08/2026 14:46, Johann 'Myrkraverk' Oskarsson wrote:
On 27/08/2026 3:49 PM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes
i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is
not turing computable.
Is there any way to prove that humans can compute anyhing not Turing
computable? Much can be computed with a Turing computable partial
method.
I previously gave this practical counter example, and you're welcome
to prove me wrong.
You pick up an Antikythera mechanism, and use it to compute something,
anything.
Unlikely, as the mechanism is not fylly known. Only one damaged example
is known and there is no evicence that more was ever constructed.
Now, after that feat, how do you do this with a Turing machine?
-aYou can obviously simulate the Antikythera mechanism with a Turing> machine, but you cannot /compute/ as one.
Simulation is enough. If one can simulate a machine one can compute
what the simulated machine can compute.
On 08/29/2026 01:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:yes, i use the concept of an idealized human agent to compute a
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>>> i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is >>>>>>> not turing computable.
Is there any way to prove that humans can compute anyhing not Turing >>>>>
function that is strictly outside the bounds of turing computability
If you can't simulate that agent with a Turing-complete computer you
cant use it for any computation. If you can you can compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two different
ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You
may be able to compute some values of an uncomputable function but you
can't know that you can compute for arguments that will be given later
unless you have a method.
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably
infinite address space and any finite or countably infinite is
accessible.
If Turing computes a limit, is it perfect?
I imagine by "countably infinite" you don't include "nonstandard
countable", yet, anybody who talks about point-at-infinity,
compactification, fixed-point theorems, or even divergence
to infinity, gets one to deal with. "Super-tasks" and for
the "super-martingale" and the like is what it's often called,
and nature does it all the time every day and so does anybody
who ever passed calculus class.
"Zeno machines", then, compute.
("Bzzzt, does compute.")
On 28/08/2026 3:21 PM, Mikko wrote:
On 27/08/2026 14:46, Johann 'Myrkraverk' Oskarsson wrote:
On 27/08/2026 3:49 PM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes
i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is
not turing computable.
Is there any way to prove that humans can compute anyhing not Turing
computable? Much can be computed with a Turing computable partial
method.
I previously gave this practical counter example, and you're welcome
to prove me wrong.
You pick up an Antikythera mechanism, and use it to compute something,
anything.
Unlikely, as the mechanism is not fylly known. Only one damaged example
is known and there is no evicence that more was ever constructed.
Dear Mikko,
I'm afraid you're wading in error and confusion.-a Please stop breathing those sauna fumes in Finland, and do your original research.-a Here is
mine.
-a https://www.antikytheramechanism.co.uk/category/all-products
So, 1) the mechanism is fully known, 2) and there have been reconstruct-
ions since.-a Now, if you want to /define/ a reconstruction as an invalid method of arguing on Usenet, I'll just have to tip my top hat to you,
and insist you invent a time machine instead.
Now, after that feat, how do you do this with a Turing machine?machine, but you cannot /compute/ as one.
-aYou can obviously simulate the Antikythera mechanism with a Turing>
Simulation is enough. If one can simulate a machine one can compute
what the simulated machine can compute.
Let there be epsilon less than delta.-a Once you have constructed a simu- lation, I'll construct a level, and a fine bolt to adjust it.-a I believe I'll try for twenty thousand threads per inch.-a So the question is, can
I nudge an arbitrary long lever, with a bolt -- hopefully starting at
twenty thousand threads per inch -- finely enough, that each nudge fits within the smallest floating point precision you have -- I'm going to
assume you were going to use double precision in C, REAL*8 in Fortran 77
or f64 in Rust -- and you won't /see it/ because your simulation lacks
real world precision?
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:If you can't simulate that agent with a Turing-complete computer you >>>>>> cant use it for any computation. If you can you can compute the same >>>>>> with a Turing machine.
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. >>>>>>>>> yes i'm quite serious about refuting the church turing thesis. >>>>>>>>> i demonstrate how an idealized human agent can compute that >>>>>>>>> which is not turing computable.
Is there any way to prove that humans can compute anyhing not >>>>>>>> Turing
yes, i use the concept of an idealized human agent to compute a >>>>>>> function that is strictly outside the bounds of turing computability >>>>>>
that's just asserting the church-turing thesis at me in two
different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You >>>> may be able to compute some values of an uncomputable function but you >>>> can't know that you can compute for arguments that will be given later >>>> unless you have a method.
my paper specifically details how that method can exist, and how the
algorithm differs from all the partial classifiers found in the
turing computable space, and why no turing machine can truly
implement the objective total algorithm even if it is mechanically
computable.
You havn't posted a pointer to your article so we can't comment.
But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as "evidence"?
i might be the first to realize: algorithms exist independently in
abstract from the more concrete mechanical implementations found in
turing machine constructions, which are inherently more limited by
their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be described.
But there is no known way to describe an anlgorithm that cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine model directly
to express algorithms, we use it as a fundamental basis for mechanical computation, but the way we discuss algorithms is far more high level
the only difference between the agent's algorithm and the partial classifiers that exist in turing machines, is that a partial classifier
must deal with self-references, whereas the agent does not have to
logically reckon about that because it's not possible to create a direct reference to computational process, again my paper will go into more
detail here specifically
this isn't like a bad thing either, turing machines are great and
incredibly useful. i'm trying to increase their productivity by
resolving their limitations more accurately so we stop tripping over
the halting problem as excuse to not be proving correctness for every
single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go
about producing and maintaining computing infrastructure. the dumb
fucking corpo ratrace to nowhere instead of producing the systems we
not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof,
which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably
infinite address space and any finite or countably infinite is
accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway
butthat does not prevent a simulation of full accessibility. Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
it's like trying to program a random turing machine to directly access
it's own source code ... the information exists in abstract, but the
turing machine model does not have a mechanical means of accessing it (barring a program implemented with a genuine quine, but those are exceptions stemming from programmatic solutions, not the fundamental mechanics of the machine)
or it's like asking a turing machine being simulated by another to arbitrarily access values from the machine that is simulating it...
that's just not mechanically possible.
On 31/08/2026 04:22, Johann 'Myrkraverk' Oskarsson wrote:
On 28/08/2026 3:21 PM, Mikko wrote:
On 27/08/2026 14:46, Johann 'Myrkraverk' Oskarsson wrote:
On 27/08/2026 3:49 PM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>> i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which is >>>>>> not turing computable.
Is there any way to prove that humans can compute anyhing not Turing >>>>> computable? Much can be computed with a Turing computable partial
method.
I previously gave this practical counter example, and you're welcome
to prove me wrong.
You pick up an Antikythera mechanism, and use it to compute something, >>>> anything.
Unlikely, as the mechanism is not fylly known. Only one damaged example
is known and there is no evicence that more was ever constructed.
Dear Mikko,
I'm afraid you're wading in error and confusion.-a Please stop breathing
those sauna fumes in Finland, and do your original research.-a Here is
mine.
-a-a https://www.antikytheramechanism.co.uk/category/all-products
So, 1) the mechanism is fully known, 2) and there have been reconstruct-
ions since.-a Now, if you want to /define/ a reconstruction as an invalid
method of arguing on Usenet, I'll just have to tip my top hat to you,
and insist you invent a time machine instead.
The reconstruction is reasonble but it is impossible to verify every
detail. But the mechanism is understood sufficiently well that the
the purpose and idea can be understood. That a part of the writing on
the machine has been read also helps.
The remaining uncertainties are small and irrelevant to our discussion.
Now, after that feat, how do you do this with a Turing machine?Turing> machine, but you cannot /compute/ as one.
-aYou can obviously simulate the Antikythera mechanism with a
Simulation is enough. If one can simulate a machine one can compute
what the simulated machine can compute.
Let there be epsilon less than delta.-a Once you have constructed a simu-
lation, I'll construct a level, and a fine bolt to adjust it.-a I believe
I'll try for twenty thousand threads per inch.-a So the question is, can
I nudge an arbitrary long lever, with a bolt -- hopefully starting at
twenty thousand threads per inch -- finely enough, that each nudge fits
within the smallest floating point precision you have -- I'm going to
assume you were going to use double precision in C, REAL*8 in Fortran 77
or f64 in Rust -- and you won't /see it/ because your simulation lacks
real world precision?
The topic was Turing computability. Particuar floating point limitations
are irrelevant. Computability of real numbers means computability to any desired precision.
On 31/08/2026 5:36 PM, Mikko wrote:
On 31/08/2026 04:22, Johann 'Myrkraverk' Oskarsson wrote:
On 28/08/2026 3:21 PM, Mikko wrote:
On 27/08/2026 14:46, Johann 'Myrkraverk' Oskarsson wrote:
On 27/08/2026 3:49 PM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>>> i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which
is not turing computable.
Is there any way to prove that humans can compute anyhing not Turing >>>>>> computable? Much can be computed with a Turing computable partial
method.
I previously gave this practical counter example, and you're welcome >>>>> to prove me wrong.
You pick up an Antikythera mechanism, and use it to compute something, >>>>> anything.
Unlikely, as the mechanism is not fylly known. Only one damaged example >>>> is known and there is no evicence that more was ever constructed.
Dear Mikko,
I'm afraid you're wading in error and confusion. Please stop breathing
those sauna fumes in Finland, and do your original research. Here is
mine.
https://www.antikytheramechanism.co.uk/category/all-products
So, 1) the mechanism is fully known, 2) and there have been reconstruct- >>> ions since. Now, if you want to /define/ a reconstruction as an invalid >>> method of arguing on Usenet, I'll just have to tip my top hat to you,
and insist you invent a time machine instead.
The reconstruction is reasonble but it is impossible to verify every
detail. But the mechanism is understood sufficiently well that the
the purpose and idea can be understood. That a part of the writing on
the machine has been read also helps.
The remaining uncertainties are small and irrelevant to our discussion.
Now, after that feat, how do you do this with a Turing machine?Turing> machine, but you cannot /compute/ as one.
You can obviously simulate the Antikythera mechanism with a
Simulation is enough. If one can simulate a machine one can compute
what the simulated machine can compute.
Let there be epsilon less than delta. Once you have constructed a simu- >>> lation, I'll construct a level, and a fine bolt to adjust it. I believe >>> I'll try for twenty thousand threads per inch. So the question is, can
I nudge an arbitrary long lever, with a bolt -- hopefully starting at
twenty thousand threads per inch -- finely enough, that each nudge fits
within the smallest floating point precision you have -- I'm going to
assume you were going to use double precision in C, REAL*8 in Fortran 77 >>> or f64 in Rust -- and you won't /see it/ because your simulation lacks
real world precision?
The topic was Turing computability. Particuar floating point limitations
are irrelevant. Computability of real numbers means computability to any
desired precision.
Right, so you want to stick to that argument? Can you construct arbi-
trary precision floating point library, and can I still create an arbi-
trary long lever, with an arbitrary fine threaded bolt to push it, so
that when you try to allocate more R.A.M. for the results, you panic
because your tower of computation runs out of memory and forgets every- thing?
I'm assuming you're going to write your simulator in Rust, being a duly anointed philosopher of a doctorate, I have no idea which, so I've added comp.lang.misc to this discussion, as comp.lang.rust is still being de-
bated in news.groups.proposals.
I will now await for you to finish said simulator, before I begin con- structing my very own mechanical shop of machinery, and /define/ myself
as having won said argument until you show an actual working simulator
I can then crash with a panic!
Enjoy making the simulator in Rust!
On 08/31/2026 04:23 AM, Johann 'Myrkraverk' Oskarsson wrote:
On 31/08/2026 5:36 PM, Mikko wrote:
On 31/08/2026 04:22, Johann 'Myrkraverk' Oskarsson wrote:
On 28/08/2026 3:21 PM, Mikko wrote:
On 27/08/2026 14:46, Johann 'Myrkraverk' Oskarsson wrote:
On 27/08/2026 3:49 PM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>>>> i'm quite serious about refuting the church turing thesis. i
demonstrate how an idealized human agent can compute that which >>>>>>>> is not turing computable.
Is there any way to prove that humans can compute anyhing not Turing >>>>>>> computable? Much can be computed with a Turing computable partial >>>>>>> method.
I previously gave this practical counter example, and you're welcome >>>>>> to prove me wrong.
You pick up an Antikythera mechanism, and use it to compute
something,
anything.
Unlikely, as the mechanism is not fylly known. Only one damaged
example
is known and there is no evicence that more was ever constructed.
Dear Mikko,
I'm afraid you're wading in error and confusion.-a Please stop breathing >>>> those sauna fumes in Finland, and do your original research.-a Here is >>>> mine.
-a-a https://www.antikytheramechanism.co.uk/category/all-products
So, 1) the mechanism is fully known, 2) and there have been
reconstruct-
ions since.-a Now, if you want to /define/ a reconstruction as an
invalid
method of arguing on Usenet, I'll just have to tip my top hat to you,
and insist you invent a time machine instead.
The reconstruction is reasonble but it is impossible to verify every
detail. But the mechanism is understood sufficiently well that the
the purpose and idea can be understood. That a part of the writing on
the machine has been read also helps.
The remaining uncertainties are small and irrelevant to our discussion.
Now, after that feat, how do you do this with a Turing machine?Turing> machine, but you cannot /compute/ as one.
You can obviously simulate the Antikythera mechanism with a
Simulation is enough. If one can simulate a machine one can compute
what the simulated machine can compute.
Let there be epsilon less than delta.-a Once you have constructed a
simu-
lation, I'll construct a level, and a fine bolt to adjust it.-a I
believe
I'll try for twenty thousand threads per inch.-a So the question is, can >>>> I nudge an arbitrary long lever, with a bolt -- hopefully starting at
twenty thousand threads per inch -- finely enough, that each nudge fits >>>> within the smallest floating point precision you have -- I'm going to
assume you were going to use double precision in C, REAL*8 in
Fortran 77
or f64 in Rust -- and you won't /see it/ because your simulation lacks >>>> real world precision?
The topic was Turing computability. Particuar floating point limitations >>> are irrelevant. Computability of real numbers means computability to any >>> desired precision.
Right, so you want to stick to that argument?-a Can you construct arbi-
trary precision floating point library, and can I still create an arbi-
trary long lever, with an arbitrary fine threaded bolt to push it, so
that when you try to allocate more R.A.M. for the results, you panic
because your tower of computation runs out of memory and forgets every-
thing?
I'm assuming you're going to write your simulator in Rust, being a duly
anointed philosopher of a doctorate, I have no idea which, so I've added
comp.lang.misc to this discussion, as comp.lang.rust is still being de-
bated in news.groups.proposals.
I will now await for you to finish said simulator, before I begin con-
structing my very own mechanical shop of machinery, and /define/ myself
as having won said argument until you show an actual working simulator
I can then crash with a panic!
Enjoy making the simulator in Rust!
"Interval arithmetic" is a usual sort of principled account
with regards to "extended-precision arithmetic" that though
mostly the "computer algebra systems" keep things formulaic
throughout and only approximate numbers at the end.
It's like when computing rotations in computer graphics,
and there's a great account that matrix-manipulation the
matrix-manipulation starts to have that 90-degree rotations
start looking slightly off, i.e., it's relevant to getting
things straight left-to-right and up-to-down, or according
to the various coordinate and sign conventions or representations
on a grid of picture-elements, that for simple accounts like
vertical and horizontal lines on paper that making floating-point
is graphically unsettling.
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. >>>>>>>>>> yes i'm quite serious about refuting the church turing thesis. >>>>>>>>>> i demonstrate how an idealized human agent can compute that >>>>>>>>>> which is not turing computable.
Is there any way to prove that humans can compute anyhing not >>>>>>>>> Turing
yes, i use the concept of an idealized human agent to compute a >>>>>>>> function that is strictly outside the bounds of turing
computability
If you can't simulate that agent with a Turing-complete computer you >>>>>>> cant use it for any computation. If you can you can compute the same >>>>>>> with a Turing machine.
that's just asserting the church-turing thesis at me in two
different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. You >>>>> may be able to compute some values of an uncomputable function but you >>>>> can't know that you can compute for arguments that will be given later >>>>> unless you have a method.
my paper specifically details how that method can exist, and how the
algorithm differs from all the partial classifiers found in the
turing computable space, and why no turing machine can truly
implement the objective total algorithm even if it is mechanically
computable.
You havn't posted a pointer to your article so we can't comment.
But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as "evidence"?
Usually I wouldn't but it is possible to do so. One just need to
understand what it is evidence about.
i might be the first to realize: algorithms exist independently in
abstract from the more concrete mechanical implementations found in
turing machine constructions, which are inherently more limited by
their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be described.
But there is no known way to describe an anlgorithm that cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine model
directly to express algorithms, we use it as a fundamental basis for
mechanical computation, but the way we discuss algorithms is far more
high level
Yes, a Turing machine is not a practical way of doing things. It is
a mathematicial model that is useful when one wants to probe that
some function is or is not computable. But being computable does not
mean that the computation can be performed quickly enough. The theory
of complexity of computation nees a different model.
the only difference between the agent's algorithm and the partial
classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does not
have to logically reckon about that because it's not possible to
create a direct reference to computational process, again my paper
will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation.
An algrithm does not interprete, it just specifies computational
actions.
this isn't like a bad thing either, turing machines are great and
incredibly useful. i'm trying to increase their productivity by
resolving their limitations more accurately so we stop tripping over
the halting problem as excuse to not be proving correctness for
every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go
about producing and maintaining computing infrastructure. the dumb
fucking corpo ratrace to nowhere instead of producing the systems we
not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof, >>>>>> which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably >>>>> infinite address space and any finite or countably infinite is
accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway
butthat does not prevent a simulation of full accessibility.
Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical relevant to algorithms?
it's like trying to program a random turing machine to directly access
it's own source code ... the information exists in abstract, but the
turing machine model does not have a mechanical means of accessing it
(barring a program implemented with a genuine quine, but those are
exceptions stemming from programmatic solutions, not the fundamental
mechanics of the machine)
An algorithm cannot and need not access its "source code". It knows
the argument and that fully determines the value of the function.
or it's like asking a turing machine being simulated by another to
arbitrarily access values from the machine that is simulating it...
that's just not mechanically possible.
The simulating machine can use any value it can access. But the process
is not a simulation if those values are not present in the real thing
the simulation itendes to simulate.
On 31/08/2026 10:33 PM, Ross Finlayson wrote:
On 08/31/2026 04:23 AM, Johann 'Myrkraverk' Oskarsson wrote:
On 31/08/2026 5:36 PM, Mikko wrote:
On 31/08/2026 04:22, Johann 'Myrkraverk' Oskarsson wrote:
On 28/08/2026 3:21 PM, Mikko wrote:
On 27/08/2026 14:46, Johann 'Myrkraverk' Oskarsson wrote:
On 27/08/2026 3:49 PM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes >>>>>>>>> i'm quite serious about refuting the church turing thesis. i >>>>>>>>> demonstrate how an idealized human agent can compute that which >>>>>>>>> is not turing computable.
Is there any way to prove that humans can compute anyhing not
Turing
computable? Much can be computed with a Turing computable partial >>>>>>>> method.
I previously gave this practical counter example, and you're welcome >>>>>>> to prove me wrong.
You pick up an Antikythera mechanism, and use it to compute
something,
anything.
Unlikely, as the mechanism is not fylly known. Only one damaged
example
is known and there is no evicence that more was ever constructed.
Dear Mikko,
I'm afraid you're wading in error and confusion. Please stop
breathing
those sauna fumes in Finland, and do your original research. Here is >>>>> mine.
https://www.antikytheramechanism.co.uk/category/all-products
So, 1) the mechanism is fully known, 2) and there have been
reconstruct-
ions since. Now, if you want to /define/ a reconstruction as an
invalid
method of arguing on Usenet, I'll just have to tip my top hat to you, >>>>> and insist you invent a time machine instead.
The reconstruction is reasonble but it is impossible to verify every
detail. But the mechanism is understood sufficiently well that the
the purpose and idea can be understood. That a part of the writing on
the machine has been read also helps.
The remaining uncertainties are small and irrelevant to our discussion. >>>>
Now, after that feat, how do you do this with a Turing machine? >>>>>> > You can obviously simulate the Antikythera mechanism with aTuring> machine, but you cannot /compute/ as one.
Simulation is enough. If one can simulate a machine one can compute >>>>>> what the simulated machine can compute.
Let there be epsilon less than delta. Once you have constructed a
simu-
lation, I'll construct a level, and a fine bolt to adjust it. I
believe
I'll try for twenty thousand threads per inch. So the question is,
can
I nudge an arbitrary long lever, with a bolt -- hopefully starting at >>>>> twenty thousand threads per inch -- finely enough, that each nudge
fits
within the smallest floating point precision you have -- I'm going to >>>>> assume you were going to use double precision in C, REAL*8 in
Fortran 77
or f64 in Rust -- and you won't /see it/ because your simulation lacks >>>>> real world precision?
The topic was Turing computability. Particuar floating point
limitations
are irrelevant. Computability of real numbers means computability to
any
desired precision.
Right, so you want to stick to that argument? Can you construct arbi-
trary precision floating point library, and can I still create an arbi-
trary long lever, with an arbitrary fine threaded bolt to push it, so
that when you try to allocate more R.A.M. for the results, you panic
because your tower of computation runs out of memory and forgets every-
thing?
I'm assuming you're going to write your simulator in Rust, being a duly
anointed philosopher of a doctorate, I have no idea which, so I've added >>> comp.lang.misc to this discussion, as comp.lang.rust is still being de-
bated in news.groups.proposals.
I will now await for you to finish said simulator, before I begin con-
structing my very own mechanical shop of machinery, and /define/ myself
as having won said argument until you show an actual working simulator
I can then crash with a panic!
Enjoy making the simulator in Rust!
"Interval arithmetic" is a usual sort of principled account
with regards to "extended-precision arithmetic" that though
mostly the "computer algebra systems" keep things formulaic
throughout and only approximate numbers at the end.
Do you mean to say that an /Antikythera mechanical simulator/
can be done purely in algebraic terms, and does not need float-
ing point at all?
Wouldn't that simulator just run out of R.A.M. faster than arbi-
trary precision floating point library?
It's like when computing rotations in computer graphics,
and there's a great account that matrix-manipulation the
matrix-manipulation starts to have that 90-degree rotations
start looking slightly off, i.e., it's relevant to getting
things straight left-to-right and up-to-down, or according
to the various coordinate and sign conventions or representations
on a grid of picture-elements, that for simple accounts like
vertical and horizontal lines on paper that making floating-point
is graphically unsettling.
I thought this was already solved in the 90s -- or earlier? -- by
using quaternions instead of matrices for the rotations, and that
it would remove the weird wobbling that comes from repeated calcu-
lations of the rotation matrix?
Please enlighten us on this subject!
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. >>>>>>>>>>> yes i'm quite serious about refuting the church turing
thesis. i demonstrate how an idealized human agent can
compute that which is not turing computable.
Is there any way to prove that humans can compute anyhing not >>>>>>>>>> Turing
yes, i use the concept of an idealized human agent to compute a >>>>>>>>> function that is strictly outside the bounds of turing
computability
If you can't simulate that agent with a Turing-complete computer >>>>>>>> you
cant use it for any computation. If you can you can compute the >>>>>>>> same
with a Turing machine.
that's just asserting the church-turing thesis at me in two
different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing computable. >>>>>> You
may be able to compute some values of an uncomputable function but >>>>>> you
can't know that you can compute for arguments that will be given
later
unless you have a method.
my paper specifically details how that method can exist, and how
the algorithm differs from all the partial classifiers found in the >>>>> turing computable space, and why no turing machine can truly
implement the objective total algorithm even if it is mechanically
computable.
You havn't posted a pointer to your article so we can't comment.
But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as "evidence"?
Usually I wouldn't but it is possible to do so. One just need to
understand what it is evidence about.
i might be the first to realize: algorithms exist independently in
abstract from the more concrete mechanical implementations found in >>>>> turing machine constructions, which are inherently more limited by
their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be described.
But there is no known way to describe an anlgorithm that cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine model
directly to express algorithms, we use it as a fundamental basis for
mechanical computation, but the way we discuss algorithms is far more
high level
Yes, a Turing machine is not a practical way of doing things. It is
a mathematicial model that is useful when one wants to probe that
some function is or is not computable. But being computable does not
mean that the computation can be performed quickly enough. The theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. i'm
address the theoretical domain of computability, not complexity
the only difference between the agent's algorithm and the partial
classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does not
have to logically reckon about that because it's not possible to
create a direct reference to computational process, again my paper
will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation.
an true self-reference is not a matter of interpretation. for a running machine this is an exact copy of the source code for the running machine
An algrithm does not interprete, it just specifies computational
actions.
this isn't like a bad thing either, turing machines are great and
incredibly useful. i'm trying to increase their productivity by
resolving their limitations more accurately so we stop tripping
over the halting problem as excuse to not be proving correctness
for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go
about producing and maintaining computing infrastructure. the dumb
fucking corpo ratrace to nowhere instead of producing the systems
we not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing
computability due to an issue of addressability, or lack thereof, >>>>>>> which can't be simulated by a turing machine because any value
computed by a turing machine is necessarily addressable
That has not been proven. There is no way to implement an uncountably >>>>>> infinite address space and any finite or countably infinite is
accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway
butthat does not prevent a simulation of full accessibility.
Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical
relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine access
to it's own source code in order to function optimally
while this can be implemented programmatically using a quine, it's not
by default a mechanism of turing machines, so any random program does
not have access to their own source code, only ones implemented with
quines have definitive access to that. the rest struggle from a
mechanical limitation, and that's the point of the example
sure, many/most algos may not need it, but some do, and unless they have
a programmatic solution they struggle from a what is a mechanical discontinuity
it's like trying to program a random turing machine to directly
access it's own source code ... the information exists in abstract,
but the turing machine model does not have a mechanical means of
accessing it (barring a program implemented with a genuine quine, but
those are exceptions stemming from programmatic solutions, not the
fundamental mechanics of the machine)
An algorithm cannot and need not access its "source code". It knows
the argument and that fully determines the value of the function.
or it's like asking a turing machine being simulated by another to
arbitrarily access values from the machine that is simulating it...
that's just not mechanically possible.
The simulating machine can use any value it can access. But the process
is not a simulation if those values are not present in the real thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation.
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking >>>>>>>>>>>> it. yes i'm quite serious about refuting the church turing >>>>>>>>>>>> thesis. i demonstrate how an idealized human agent can >>>>>>>>>>>> compute that which is not turing computable.
Is there any way to prove that humans can compute anyhing not >>>>>>>>>>> Turing
yes, i use the concept of an idealized human agent to compute >>>>>>>>>> a function that is strictly outside the bounds of turing
computability
If you can't simulate that agent with a Turing-complete
computer you
cant use it for any computation. If you can you can compute the >>>>>>>>> same
with a Turing machine.
that's just asserting the church-turing thesis at me in two
different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing
computable. You
may be able to compute some values of an uncomputable function
but you
can't know that you can compute for arguments that will be given >>>>>>> later
unless you have a method.
my paper specifically details how that method can exist, and how
the algorithm differs from all the partial classifiers found in
the turing computable space, and why no turing machine can truly
implement the objective total algorithm even if it is mechanically >>>>>> computable.
You havn't posted a pointer to your article so we can't comment.
But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as
"evidence"?
Usually I wouldn't but it is possible to do so. One just need to
understand what it is evidence about.
i might be the first to realize: algorithms exist independently in >>>>>> abstract from the more concrete mechanical implementations found
in turing machine constructions, which are inherently more limited >>>>>> by their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be described. >>>>> But there is no known way to describe an anlgorithm that cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine model
directly to express algorithms, we use it as a fundamental basis for
mechanical computation, but the way we discuss algorithms is far
more high level
Yes, a Turing machine is not a practical way of doing things. It is
a mathematicial model that is useful when one wants to probe that
some function is or is not computable. But being computable does not
mean that the computation can be performed quickly enough. The theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. i'm
address the theoretical domain of computability, not complexity
the only difference between the agent's algorithm and the partial
classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does
not have to logically reckon about that because it's not possible to
create a direct reference to computational process, again my paper
will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation.
an true self-reference is not a matter of interpretation. for a
running machine this is an exact copy of the source code for the
running machine
Whithout any interpretation there are no references, only synbols.
Without references there are no self-references.
An algrithm does not interprete, it just specifies computational
actions.
this isn't like a bad thing either, turing machines are great and >>>>>> incredibly useful. i'm trying to increase their productivity by
resolving their limitations more accurately so we stop tripping
over the halting problem as excuse to not be proving correctness
for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go >>>>>> about producing and maintaining computing infrastructure. the dumb >>>>>> fucking corpo ratrace to nowhere instead of producing the systems >>>>>> we not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turingThat has not been proven. There is no way to implement an
computability due to an issue of addressability, or lack
thereof, which can't be simulated by a turing machine because >>>>>>>> any value computed by a turing machine is necessarily addressable >>>>>>>
uncountably
infinite address space and any finite or countably infinite is
accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway
butthat does not prevent a simulation of full accessibility.
Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical
relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine
access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing machines. They are never optimal.
Ordinary computers perform quite well without any ability to access
their own "source code".
while this can be implemented programmatically using a quine, it's not
by default a mechanism of turing machines, so any random program does
not have access to their own source code, only ones implemented with
quines have definitive access to that. the rest struggle from a
mechanical limitation, and that's the point of the example
sure, many/most algos may not need it, but some do, and unless they
have a programmatic solution they struggle from a what is a mechanical
discontinuity
it's like trying to program a random turing machine to directly
access it's own source code ... the information exists in abstract,
but the turing machine model does not have a mechanical means of
accessing it (barring a program implemented with a genuine quine,
but those are exceptions stemming from programmatic solutions, not
the fundamental mechanics of the machine)
An algorithm cannot and need not access its "source code". It knows
the argument and that fully determines the value of the function.
or it's like asking a turing machine being simulated by another to
arbitrarily access values from the machine that is simulating it...
that's just not mechanically possible.
The simulating machine can use any value it can access. But the process
is not a simulation if those values are not present in the real thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation.
No, it is an essential aspect of the meanings of the words.
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking >>>>>>>>>>>>> it. yes i'm quite serious about refuting the church turing >>>>>>>>>>>>> thesis. i demonstrate how an idealized human agent can >>>>>>>>>>>>> compute that which is not turing computable.
Is there any way to prove that humans can compute anyhing >>>>>>>>>>>> not Turing
yes, i use the concept of an idealized human agent to compute >>>>>>>>>>> a function that is strictly outside the bounds of turing >>>>>>>>>>> computability
If you can't simulate that agent with a Turing-complete
computer you
cant use it for any computation. If you can you can compute >>>>>>>>>> the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two >>>>>>>>> different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing
computable. You
may be able to compute some values of an uncomputable function >>>>>>>> but you
can't know that you can compute for arguments that will be given >>>>>>>> later
unless you have a method.
my paper specifically details how that method can exist, and how >>>>>>> the algorithm differs from all the partial classifiers found in >>>>>>> the turing computable space, and why no turing machine can truly >>>>>>> implement the objective total algorithm even if it is
mechanically computable.
You havn't posted a pointer to your article so we can't comment.
But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as
"evidence"?
Usually I wouldn't but it is possible to do so. One just need to
understand what it is evidence about.
i might be the first to realize: algorithms exist independently >>>>>>> in abstract from the more concrete mechanical implementations
found in turing machine constructions, which are inherently more >>>>>>> limited by their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be described. >>>>>> But there is no known way to describe an anlgorithm that cannot be >>>>>> described as a Turing machine.
on the flip side we never actually use the turing machine model
directly to express algorithms, we use it as a fundamental basis
for mechanical computation, but the way we discuss algorithms is
far more high level
Yes, a Turing machine is not a practical way of doing things. It is
a mathematicial model that is useful when one wants to probe that
some function is or is not computable. But being computable does not
mean that the computation can be performed quickly enough. The theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. i'm
address the theoretical domain of computability, not complexity
the only difference between the agent's algorithm and the partial
classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does
not have to logically reckon about that because it's not possible
to create a direct reference to computational process, again my
paper will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation.
an true self-reference is not a matter of interpretation. for a
running machine this is an exact copy of the source code for the
running machine
Whithout any interpretation there are no references, only synbols.
Without references there are no self-references.
a self-reference is a finite length value of data that encodes the exact transition table for the running machine
sure the encoding is up to "interpretation", but given a specified (and correct) method of encoding machines, the self-reference is exact and
not up to interpretation.
i think we agree on this
An algrithm does not interprete, it just specifies computational
actions.
this isn't like a bad thing either, turing machines are great and >>>>>>> incredibly useful. i'm trying to increase their productivity by >>>>>>> resolving their limitations more accurately so we stop tripping >>>>>>> over the halting problem as excuse to not be proving correctness >>>>>>> for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we go >>>>>>> about producing and maintaining computing infrastructure. the
dumb fucking corpo ratrace to nowhere instead of producing the
systems we not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing >>>>>>>>> computability due to an issue of addressability, or lackThat has not been proven. There is no way to implement an
thereof, which can't be simulated by a turing machine because >>>>>>>>> any value computed by a turing machine is necessarily addressable >>>>>>>>
uncountably
infinite address space and any finite or countably infinite is >>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway >>>>>> butthat does not prevent a simulation of full accessibility.
Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical
relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine
access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing
machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to
optimal functionality, ei deciding some maximal subset of machines
within a given semantic set (like set of halting machine, or set of circle-free machine)
this maximal subset may be turing-complete, but i wouldn't expect you to accept that without reading the proof i have to yet to post.
actually, even correctly deciding a less-than-maximal subset of turing machines requires a true self-reference
Ordinary computers perform quite well without any ability to access
their own "source code".
sure, the point is there exist some algos that require a self-reference
while this can be implemented programmatically using a quine, it's
not by default a mechanism of turing machines, so any random program
does not have access to their own source code, only ones implemented
with quines have definitive access to that. the rest struggle from a
mechanical limitation, and that's the point of the example
sure, many/most algos may not need it, but some do, and unless they
have a programmatic solution they struggle from a what is a
mechanical discontinuity
it's like trying to program a random turing machine to directly
access it's own source code ... the information exists in abstract, >>>>> but the turing machine model does not have a mechanical means of
accessing it (barring a program implemented with a genuine quine,
but those are exceptions stemming from programmatic solutions, not
the fundamental mechanics of the machine)
An algorithm cannot and need not access its "source code". It knows
the argument and that fully determines the value of the function.
or it's like asking a turing machine being simulated by another to
arbitrarily access values from the machine that is simulating it... >>>>> that's just not mechanically possible.
The simulating machine can use any value it can access. But the process >>>> is not a simulation if those values are not present in the real thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation.
No, it is an essential aspect of the meanings of the words.
idk what ur arguing,
but what i'm trying to convey is that a mechanical discontinuity happens when a computation run on a turing machine lacks a mechanism to directly access some specific information.
i gave you two examples of where a lack of mechanism creates aYour examples were not clear. And examples are not very good for the
mechanical discontinuity, and if u don't want to consider them then i
cannot help you further here
On 01/09/2026 22:50, dart200 wrote:
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking >>>>>>>>>>>>>> it. yes i'm quite serious about refuting the church turing >>>>>>>>>>>>>> thesis. i demonstrate how an idealized human agent can >>>>>>>>>>>>>> compute that which is not turing computable.
Is there any way to prove that humans can compute anyhing >>>>>>>>>>>>> not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>> compute a function that is strictly outside the bounds of >>>>>>>>>>>> turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>> computer you
cant use it for any computation. If you can you can compute >>>>>>>>>>> the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two >>>>>>>>>> different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing
computable. You
may be able to compute some values of an uncomputable function >>>>>>>>> but you
can't know that you can compute for arguments that will be
given later
unless you have a method.
my paper specifically details how that method can exist, and how >>>>>>>> the algorithm differs from all the partial classifiers found in >>>>>>>> the turing computable space, and why no turing machine can truly >>>>>>>> implement the objective total algorithm even if it is
mechanically computable.
You havn't posted a pointer to your article so we can't comment. >>>>>>> But in this discussion you have posted no evidence that you can
compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as
"evidence"?
Usually I wouldn't but it is possible to do so. One just need to
understand what it is evidence about.
i might be the first to realize: algorithms exist independently >>>>>>>> in abstract from the more concrete mechanical implementations >>>>>>>> found in turing machine constructions, which are inherently more >>>>>>>> limited by their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be
described.
But there is no known way to describe an anlgorithm that cannot be >>>>>>> described as a Turing machine.
on the flip side we never actually use the turing machine model
directly to express algorithms, we use it as a fundamental basis
for mechanical computation, but the way we discuss algorithms is
far more high level
Yes, a Turing machine is not a practical way of doing things. It is
a mathematicial model that is useful when one wants to probe that
some function is or is not computable. But being computable does not >>>>> mean that the computation can be performed quickly enough. The theory >>>>> of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. i'm
address the theoretical domain of computability, not complexity
the only difference between the agent's algorithm and the partial >>>>>> classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does >>>>>> not have to logically reckon about that because it's not possible >>>>>> to create a direct reference to computational process, again my
paper will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation.
an true self-reference is not a matter of interpretation. for a
running machine this is an exact copy of the source code for the
running machine
Whithout any interpretation there are no references, only synbols.
Without references there are no self-references.
a self-reference is a finite length value of data that encodes the
exact transition table for the running machine
That's not a reference, it is a self-description. Though the running
machine does not care and hardly knows whether the description is a self-descriptipn.
sure the encoding is up to "interpretation", but given a specified
(and correct) method of encoding machines, the self-reference is exact
and not up to interpretation.
The meaning of "exact" also depends on interpretation.
i think we agree on this
An algrithm does not interprete, it just specifies computational
actions.
this isn't like a bad thing either, turing machines are great >>>>>>>> and incredibly useful. i'm trying to increase their productivity >>>>>>>> by resolving their limitations more accurately so we stop
tripping over the halting problem as excuse to not be proving >>>>>>>> correctness for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we >>>>>>>> go about producing and maintaining computing infrastructure. the >>>>>>>> dumb fucking corpo ratrace to nowhere instead of producing the >>>>>>>> systems we not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing >>>>>>>>>> computability due to an issue of addressability, or lackThat has not been proven. There is no way to implement an
thereof, which can't be simulated by a turing machine because >>>>>>>>>> any value computed by a turing machine is necessarily addressable >>>>>>>>>
uncountably
infinite address space and any finite or countably infinite is >>>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a
mechanical discontinuity, and i can only explain by properly
describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway >>>>>>> butthat does not prevent a simulation of full accessibility.
Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical >>>>> relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine
access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing
machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to
optimal functionality, ei deciding some maximal subset of machines
within a given semantic set (like set of halting machine, or set of
circle-free machine)
Then you should use some other word. Words derived from "optimum" are understood to refer performance and resource consumption aspectes of computation.
There are problems where every partial algorithm fails to compute for
some argument that another partial agorithm computes. One example is
the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect you
to accept that without reading the proof i have to yet to post.
THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of turing
machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Ordinary computers perform quite well without any ability to access
their own "source code".
sure, the point is there exist some algos that require a self-reference
Not proven.
while this can be implemented programmatically using a quine, it's
not by default a mechanism of turing machines, so any random program
does not have access to their own source code, only ones implemented
with quines have definitive access to that. the rest struggle from a
mechanical limitation, and that's the point of the example
sure, many/most algos may not need it, but some do, and unless they
have a programmatic solution they struggle from a what is a
mechanical discontinuity
it's like trying to program a random turing machine to directly
access it's own source code ... the information exists in
abstract, but the turing machine model does not have a mechanical >>>>>> means of accessing it (barring a program implemented with a
genuine quine, but those are exceptions stemming from programmatic >>>>>> solutions, not the fundamental mechanics of the machine)
An algorithm cannot and need not access its "source code". It knows
the argument and that fully determines the value of the function.
or it's like asking a turing machine being simulated by another to >>>>>> arbitrarily access values from the machine that is simulating
it... that's just not mechanically possible.
The simulating machine can use any value it can access. But the
process
is not a simulation if those values are not present in the real thing >>>>> the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation.
No, it is an essential aspect of the meanings of the words.
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world
whereas "algorithm" refers to a mathematical concept. The real world
does not limit mathematics in any way.
but what i'm trying to convey is that a mechanical discontinuity
happens when a computation run on a turing machine lacks a mechanism
to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
--i gave you two examples of where a lack of mechanism creates aYour examples were not clear. And examples are not very good for the
mechanical discontinuity, and if u don't want to consider them then i
cannot help you further here
purpose. Or at least, for a rough idea, you need counter-examples, too.
But complete definitions are clearer.
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking >>>>>>>>>>>>>>> it. yes i'm quite serious about refuting the church >>>>>>>>>>>>>>> turing thesis. i demonstrate how an idealized human agent >>>>>>>>>>>>>>> can compute that which is not turing computable.
Is there any way to prove that humans can compute anyhing >>>>>>>>>>>>>> not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>> compute a function that is strictly outside the bounds of >>>>>>>>>>>>> turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>> computer you
cant use it for any computation. If you can you can compute >>>>>>>>>>>> the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two >>>>>>>>>>> different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing
computable. You
may be able to compute some values of an uncomputable function >>>>>>>>>> but you
can't know that you can compute for arguments that will be >>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, and >>>>>>>>> how the algorithm differs from all the partial classifiers
found in the turing computable space, and why no turing machine >>>>>>>>> can truly implement the objective total algorithm even if it is >>>>>>>>> mechanically computable.
You havn't posted a pointer to your article so we can't comment. >>>>>>>> But in this discussion you have posted no evidence that you can >>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as
"evidence"?
Usually I wouldn't but it is possible to do so. One just need to
understand what it is evidence about.
i might be the first to realize: algorithms exist independently >>>>>>>>> in abstract from the more concrete mechanical implementations >>>>>>>>> found in turing machine constructions, which are inherently >>>>>>>>> more limited by their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be
described.
But there is no known way to describe an anlgorithm that cannot be >>>>>>>> described as a Turing machine.
on the flip side we never actually use the turing machine model >>>>>>> directly to express algorithms, we use it as a fundamental basis >>>>>>> for mechanical computation, but the way we discuss algorithms is >>>>>>> far more high level
Yes, a Turing machine is not a practical way of doing things. It is >>>>>> a mathematicial model that is useful when one wants to probe that
some function is or is not computable. But being computable does not >>>>>> mean that the computation can be performed quickly enough. The theory >>>>>> of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity.
i'm address the theoretical domain of computability, not complexity
an true self-reference is not a matter of interpretation. for a
the only difference between the agent's algorithm and the partial >>>>>>> classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does >>>>>>> not have to logically reckon about that because it's not possible >>>>>>> to create a direct reference to computational process, again my >>>>>>> paper will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation. >>>>>
running machine this is an exact copy of the source code for the
running machine
Whithout any interpretation there are no references, only synbols.
Without references there are no self-references.
a self-reference is a finite length value of data that encodes the
exact transition table for the running machine
That's not a reference, it is a self-description. Though the running
that's what a self-reference is for turing machines, it can only
reference itself by an exact copy
machine does not care and hardly knows whether the description is a
self-descriptipn.
it matters for certain algos like partial semantic deciders that must be aware of when they are deciding on a self-reference
sure the encoding is up to "interpretation", but given a specified
(and correct) method of encoding machines, the self-reference is
exact and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
i think we agree on this
An algrithm does not interprete, it just specifies computational
actions.
this isn't like a bad thing either, turing machines are great >>>>>>>>> and incredibly useful. i'm trying to increase their
productivity by resolving their limitations more accurately so >>>>>>>>> we stop tripping over the halting problem as excuse to not be >>>>>>>>> proving correctness for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we >>>>>>>>> go about producing and maintaining computing infrastructure. >>>>>>>>> the dumb fucking corpo ratrace to nowhere instead of producing >>>>>>>>> the systems we not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing >>>>>>>>>>> computability due to an issue of addressability, or lack >>>>>>>>>>> thereof, which can't be simulated by a turing machine because >>>>>>>>>>> any value computed by a turing machine is necessarily
addressable
That has not been proven. There is no way to implement an >>>>>>>>>> uncountably
infinite address space and any finite or countably infinite is >>>>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a >>>>>>>>> mechanical discontinuity, and i can only explain by properly >>>>>>>>> describing the justifying thought experiment
A finite or countable address space is fully discontinuous
anyway butthat does not prevent a simulation of full
accessibility. Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical >>>>>> relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine
access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing
machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to
optimal functionality, ei deciding some maximal subset of machines
within a given semantic set (like set of halting machine, or set of
circle-free machine)
Then you should use some other word. Words derived from "optimum" are
understood to refer performance and resource consumption aspectes of
computation.
i explained my usage
There are problems where every partial algorithm fails to compute for
some argument that another partial agorithm computes. One example is
the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect you
to accept that without reading the proof i have to yet to post.
THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of
turing machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Ordinary computers perform quite well without any ability to access
their own "source code".
sure, the point is there exist some algos that require a self-reference
Not proven.
while this can be implemented programmatically using a quine, it's
not by default a mechanism of turing machines, so any random
program does not have access to their own source code, only ones
implemented with quines have definitive access to that. the rest
struggle from a mechanical limitation, and that's the point of the
example
sure, many/most algos may not need it, but some do, and unless they >>>>> have a programmatic solution they struggle from a what is a
mechanical discontinuity
it's like trying to program a random turing machine to directly >>>>>>> access it's own source code ... the information exists in
abstract, but the turing machine model does not have a mechanical >>>>>>> means of accessing it (barring a program implemented with a
genuine quine, but those are exceptions stemming from
programmatic solutions, not the fundamental mechanics of the
machine)
An algorithm cannot and need not access its "source code". It knows >>>>>> the argument and that fully determines the value of the function. >>>>>>> or it's like asking a turing machine being simulated by another >>>>>>> to arbitrarily access values from the machine that is simulating >>>>>>> it... that's just not mechanically possible.
The simulating machine can use any value it can access. But the
process
is not a simulation if those values are not present in the real thing >>>>>> the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation.
No, it is an essential aspect of the meanings of the words.
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world
whereas "algorithm" refers to a mathematical concept. The real world
does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
but what i'm trying to convey is that a mechanical discontinuity
happens when a computation run on a turing machine lacks a mechanism
to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it.
communication is a two way street
On 02/09/2026 17:56, dart200 wrote:
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda >>>>>>>>>>>>>>>> liking it. yes i'm quite serious about refuting the >>>>>>>>>>>>>>>> church turing thesis. i demonstrate how an idealized >>>>>>>>>>>>>>>> human agent can compute that which is not turing >>>>>>>>>>>>>>>> computable.
Is there any way to prove that humans can compute anyhing >>>>>>>>>>>>>>> not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>>> compute a function that is strictly outside the bounds of >>>>>>>>>>>>>> turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>>> computer you
cant use it for any computation. If you can you can compute >>>>>>>>>>>>> the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two >>>>>>>>>>>> different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing
computable. You
may be able to compute some values of an uncomputable
function but you
can't know that you can compute for arguments that will be >>>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, and >>>>>>>>>> how the algorithm differs from all the partial classifiers >>>>>>>>>> found in the turing computable space, and why no turing
machine can truly implement the objective total algorithm even >>>>>>>>>> if it is mechanically computable.
You havn't posted a pointer to your article so we can't comment. >>>>>>>>> But in this discussion you have posted no evidence that you can >>>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as
"evidence"?
Usually I wouldn't but it is possible to do so. One just need to >>>>>>> understand what it is evidence about.
i might be the first to realize: algorithms existTHe concept of algorithm comtains that an algorithm can be
independently in abstract from the more concrete mechanical >>>>>>>>>> implementations found in turing machine constructions, which >>>>>>>>>> are inherently more limited by their formally addressable nature. >>>>>>>>>
described.
But there is no known way to describe an anlgorithm that cannot be >>>>>>>>> described as a Turing machine.
on the flip side we never actually use the turing machine model >>>>>>>> directly to express algorithms, we use it as a fundamental basis >>>>>>>> for mechanical computation, but the way we discuss algorithms is >>>>>>>> far more high level
Yes, a Turing machine is not a practical way of doing things. It is >>>>>>> a mathematicial model that is useful when one wants to probe that >>>>>>> some function is or is not computable. But being computable does not >>>>>>> mean that the computation can be performed quickly enough. The
theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity.
i'm address the theoretical domain of computability, not complexity >>>>>>
an true self-reference is not a matter of interpretation. for a
the only difference between the agent's algorithm and theWhether something is a self-reference is a matter of interpretation. >>>>>>
partial classifiers that exist in turing machines, is that a
partial classifier must deal with self-references, whereas the >>>>>>>> agent does not have to logically reckon about that because it's >>>>>>>> not possible to create a direct reference to computational
process, again my paper will go into more detail here specifically >>>>>>>
running machine this is an exact copy of the source code for the
running machine
Whithout any interpretation there are no references, only synbols.
Without references there are no self-references.
a self-reference is a finite length value of data that encodes the
exact transition table for the running machine
That's not a reference, it is a self-description. Though the running
that's what a self-reference is for turing machines, it can only
reference itself by an exact copy
It is not a copy, it is a description. A copy of a Turing machine is a
Turing machine, which is as unaccessible as self.
A description does not refer to a partuclar machine. A description that describes a machine also describes copies of that machine.
machine does not care and hardly knows whether the description is a
self-descriptipn.
it matters for certain algos like partial semantic deciders that must
be aware of when they are deciding on a self-reference
For that they need to be able to identify a self-description. That is
not a trivial problem.
sure the encoding is up to "interpretation", but given a specified
(and correct) method of encoding machines, the self-reference is
exact and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
A string that is an exact self-reference in some interprete|ition may
refer to something else or hothing in another interpretation. An uninterpreted string does not refer.
i think we agree on this
An algrithm does not interprete, it just specifies computational >>>>>>> actions.
this isn't like a bad thing either, turing machines are great >>>>>>>>>> and incredibly useful. i'm trying to increase their
productivity by resolving their limitations more accurately so >>>>>>>>>> we stop tripping over the halting problem as excuse to not be >>>>>>>>>> proving correctness for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we >>>>>>>>>> go about producing and maintaining computing infrastructure. >>>>>>>>>> the dumb fucking corpo ratrace to nowhere instead of producing >>>>>>>>>> the systems we not only need but deserve is just so ungodly >>>>>>>>>>
the agent can compute something outside the bounds of turing >>>>>>>>>>>> computability due to an issue of addressability, or lack >>>>>>>>>>>> thereof, which can't be simulated by a turing machine >>>>>>>>>>>> because any value computed by a turing machine is
necessarily addressable
That has not been proven. There is no way to implement an >>>>>>>>>>> uncountably
infinite address space and any finite or countably infinite is >>>>>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a >>>>>>>>>> mechanical discontinuity, and i can only explain by properly >>>>>>>>>> describing the justifying thought experiment
A finite or countable address space is fully discontinuous
anyway butthat does not prevent a simulation of full
accessibility. Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything
mechanical
relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine >>>>>> access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing >>>>> machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to
optimal functionality, ei deciding some maximal subset of machines
within a given semantic set (like set of halting machine, or set of
circle-free machine)
Then you should use some other word. Words derived from "optimum" are
understood to refer performance and resource consumption aspectes of
computation.
i explained my usage
Even with an explanation it is confusing. Another word or phrase could
be better.
There are problems where every partial algorithm fails to compute for
some argument that another partial agorithm computes. One example is
the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect
you to accept that without reading the proof i have to yet to post.
THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of
turing machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Not proven.Ordinary computers perform quite well without any ability to access
their own "source code".
sure, the point is there exist some algos that require a self-reference >>>
while this can be implemented programmatically using a quine, it's >>>>>> not by default a mechanism of turing machines, so any randomNo, it is an essential aspect of the meanings of the words.
program does not have access to their own source code, only ones
implemented with quines have definitive access to that. the rest
struggle from a mechanical limitation, and that's the point of the >>>>>> example
sure, many/most algos may not need it, but some do, and unless
they have a programmatic solution they struggle from a what is a
mechanical discontinuity
it's like trying to program a random turing machine to directly >>>>>>>> access it's own source code ... the information exists in
abstract, but the turing machine model does not have a
mechanical means of accessing it (barring a program implemented >>>>>>>> with a genuine quine, but those are exceptions stemming from
programmatic solutions, not the fundamental mechanics of the
machine)
An algorithm cannot and need not access its "source code". It knows >>>>>>> the argument and that fully determines the value of the function. >>>>>>>> or it's like asking a turing machine being simulated by another >>>>>>>> to arbitrarily access values from the machine that is simulating >>>>>>>> it... that's just not mechanically possible.
The simulating machine can use any value it can access. But the >>>>>>> process
is not a simulation if those values are not present in the real >>>>>>> thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation. >>>>>
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world
whereas "algorithm" refers to a mathematical concept. The real world
does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
An idealized machine does not have specific mechanics. The idealization
omits unimprtant implementation details. It may avoid some constraints
of real computers like the requiremt that every machine instruction
must perform a Turing-computable function. Or it may have additional restrictins that real computers have not. But neither restrictins are "mechanical", only functional.
but what i'm trying to convey is that a mechanical discontinuity
happens when a computation run on a turing machine lacks a mechanism
to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it.
That is an unavoidable consequence of bad presentation.
communication is a two way street
Not always. A can read what for example Turing has written but I can't
ask Turing about the exact meanings of his words. Unless you can write
a preentation that can be understood by readers who can't or don't ask questions it doesn't matter whether you have discovered something. But
if it is useful or otherwise interesting someone with better skills of presentation will discover it and publish.
On 9/3/26 1:06 AM, Mikko wrote:
On 02/09/2026 17:56, dart200 wrote:
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:There is no known method to compute what is not Turing >>>>>>>>>>>> computable. You
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda >>>>>>>>>>>>>>>>> liking it. yes i'm quite serious about refuting the >>>>>>>>>>>>>>>>> church turing thesis. i demonstrate how an idealized >>>>>>>>>>>>>>>>> human agent can compute that which is not turing >>>>>>>>>>>>>>>>> computable.
Is there any way to prove that humans can compute >>>>>>>>>>>>>>>> anyhing not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>>>> compute a function that is strictly outside the bounds of >>>>>>>>>>>>>>> turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>>>> computer you
cant use it for any computation. If you can you can >>>>>>>>>>>>>> compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two >>>>>>>>>>>>> different ways, which in of itself has not be proven. >>>>>>>>>>>>
may be able to compute some values of an uncomputable >>>>>>>>>>>> function but you
can't know that you can compute for arguments that will be >>>>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, and >>>>>>>>>>> how the algorithm differs from all the partial classifiers >>>>>>>>>>> found in the turing computable space, and why no turing >>>>>>>>>>> machine can truly implement the objective total algorithm >>>>>>>>>>> even if it is mechanically computable.
You havn't posted a pointer to your article so we can't comment. >>>>>>>>>> But in this discussion you have posted no evidence that you can >>>>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as >>>>>>>>> "evidence"?
Usually I wouldn't but it is possible to do so. One just need to >>>>>>>> understand what it is evidence about.
i might be the first to realize: algorithms exist
independently in abstract from the more concrete mechanical >>>>>>>>>>> implementations found in turing machine constructions, which >>>>>>>>>>> are inherently more limited by their formally addressable >>>>>>>>>>> nature.
THe concept of algorithm comtains that an algorithm can be >>>>>>>>>> described.
But there is no known way to describe an anlgorithm that
cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine model >>>>>>>>> directly to express algorithms, we use it as a fundamental
basis for mechanical computation, but the way we discuss
algorithms is far more high level
Yes, a Turing machine is not a practical way of doing things. It is >>>>>>>> a mathematicial model that is useful when one wants to probe that >>>>>>>> some function is or is not computable. But being computable does >>>>>>>> not
mean that the computation can be performed quickly enough. The >>>>>>>> theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. >>>>>>> i'm address the theoretical domain of computability, not complexity >>>>>>>
the only difference between the agent's algorithm and theWhether something is a self-reference is a matter of
partial classifiers that exist in turing machines, is that a >>>>>>>>> partial classifier must deal with self-references, whereas the >>>>>>>>> agent does not have to logically reckon about that because it's >>>>>>>>> not possible to create a direct reference to computational
process, again my paper will go into more detail here specifically >>>>>>>>
interpretation.
an true self-reference is not a matter of interpretation. for a >>>>>>> running machine this is an exact copy of the source code for the >>>>>>> running machine
Whithout any interpretation there are no references, only synbols. >>>>>> Without references there are no self-references.
a self-reference is a finite length value of data that encodes the
exact transition table for the running machine
That's not a reference, it is a self-description. Though the running
that's what a self-reference is for turing machines, it can only
reference itself by an exact copy
It is not a copy, it is a description. A copy of a Turing machine is a
Turing machine, which is as unaccessible as self.
it's a copy (in some encoding) of the transition table the we use to
define and then refer to a particular machine, and what it specifically computes.
it's how machines reference to each other. it's how a machine
can reference itself, including referencing any particular value it can computes
A description does not refer to a partuclar machine. A description that
describes a machine also describes copies of that machine.
machine does not care and hardly knows whether the description is a
self-descriptipn.
it matters for certain algos like partial semantic deciders that must
be aware of when they are deciding on a self-reference
For that they need to be able to identify a self-description. That is
not a trivial problem.
i never said it was trivial, just that it matters.
sure the encoding is up to "interpretation", but given a specified
(and correct) method of encoding machines, the self-reference is
exact and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
A string that is an exact self-reference in some interprete|ition may
refer to something else or hothing in another interpretation. An
uninterpreted string does not refer.
we can stick to handling one particular encoding of machines when it
comes how to reckon about undecidability within computing.
i think we agree on this
An algrithm does not interprete, it just specifies computational >>>>>>>> actions.
this isn't like a bad thing either, turing machines are great >>>>>>>>>>> and incredibly useful. i'm trying to increase their
productivity by resolving their limitations more accurately >>>>>>>>>>> so we stop tripping over the halting problem as excuse to not >>>>>>>>>>> be proving correctness for every single program we deploy... >>>>>>>>>>>
no, testing isn't good enough bro, nor is the braindead way >>>>>>>>>>> we go about producing and maintaining computing
infrastructure. the dumb fucking corpo ratrace to nowhere >>>>>>>>>>> instead of producing the systems we not only need but deserve >>>>>>>>>>> is just so ungodly
the agent can compute something outside the bounds of >>>>>>>>>>>>> turing computability due to an issue of addressability, or >>>>>>>>>>>>> lack thereof, which can't be simulated by a turing machine >>>>>>>>>>>>> because any value computed by a turing machine is
necessarily addressable
That has not been proven. There is no way to implement an >>>>>>>>>>>> uncountably
infinite address space and any finite or countably infinite is >>>>>>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a >>>>>>>>>>> mechanical discontinuity, and i can only explain by properly >>>>>>>>>>> describing the justifying thought experiment
A finite or countable address space is fully discontinuous >>>>>>>>>> anyway butthat does not prevent a simulation of full
accessibility. Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything
mechanical
relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine >>>>>>> access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing >>>>>> machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to
optimal functionality, ei deciding some maximal subset of machines
within a given semantic set (like set of halting machine, or set of >>>>> circle-free machine)
Then you should use some other word. Words derived from "optimum" are
understood to refer performance and resource consumption aspectes of
computation.
i explained my usage
Even with an explanation it is confusing. Another word or phrase could
be better.
thank you for ur input
There are problems where every partial algorithm fails to compute for
some argument that another partial agorithm computes. One example is
the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect
you to accept that without reading the proof i have to yet to post.
THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of
turing machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Ordinary computers perform quite well without any ability to access >>>>>> their own "source code".
sure, the point is there exist some algos that require a self-
reference
Not proven.
while this can be implemented programmatically using a quine,No, it is an essential aspect of the meanings of the words.
it's not by default a mechanism of turing machines, so any random >>>>>>> program does not have access to their own source code, only ones >>>>>>> implemented with quines have definitive access to that. the rest >>>>>>> struggle from a mechanical limitation, and that's the point of
the example
sure, many/most algos may not need it, but some do, and unless
they have a programmatic solution they struggle from a what is a >>>>>>> mechanical discontinuity
it's like trying to program a random turing machine to directly >>>>>>>>> access it's own source code ... the information exists in
abstract, but the turing machine model does not have a
mechanical means of accessing it (barring a program implemented >>>>>>>>> with a genuine quine, but those are exceptions stemming from >>>>>>>>> programmatic solutions, not the fundamental mechanics of the >>>>>>>>> machine)
An algorithm cannot and need not access its "source code". It knows >>>>>>>> the argument and that fully determines the value of the function. >>>>>>>>> or it's like asking a turing machine being simulated by another >>>>>>>>> to arbitrarily access values from the machine that is
simulating it... that's just not mechanically possible.
The simulating machine can use any value it can access. But the >>>>>>>> process
is not a simulation if those values are not present in the real >>>>>>>> thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation. >>>>>>
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world
whereas "algorithm" refers to a mathematical concept. The real world
does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
An idealized machine does not have specific mechanics. The idealization
yes it does. it has a head. and a tape. and various commands it can
process in accordance with a transition table that then has mechanical effects on that head and tape. those are the mechanics of the idealized computing machine, and that's how i'm using the word
i explained my usage
omits unimprtant implementation details. It may avoid some constraints
of real computers like the requiremt that every machine instruction
must perform a Turing-computable function. Or it may have additional
restrictins that real computers have not. But neither restrictins are
"mechanical", only functional.
but what i'm trying to convey is that a mechanical discontinuity
happens when a computation run on a turing machine lacks a
mechanism to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it.
That is an unavoidable consequence of bad presentation.
it can also be the consequence of bad listening, which is really quite endemic in online discussion
communication is a two way street
Not always. A can read what for example Turing has written but I can't
ask Turing about the exact meanings of his words. Unless you can write
a preentation that can be understood by readers who can't or don't ask
questions it doesn't matter whether you have discovered something. But
if it is useful or otherwise interesting someone with better skills of
presentation will discover it and publish.
jeez sentiments like that make me wonder if this god-forsaking species
is even worthy of further progress tbh ...
but i'm not doing it for the rest of ya'll. i'm doing it to build a--
better world for my kid, so that he doesn't need to suffer thru a world floundering around in a rather asinine implementation of general
computing that even remotely do what we need it do, to be frank
but i'm not doing it for the rest of ya'll. i'm doing it to build a
better world for my kid, so that he doesn't need to suffer thru a world floundering around in a rather asinine implementation of general
computing that even remotely do what we need it do, to be frank
On 03/09/2026 19:39, dart200 wrote:
On 9/3/26 1:06 AM, Mikko wrote:
On 02/09/2026 17:56, dart200 wrote:
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:There is no known method to compute what is not Turing >>>>>>>>>>>>> computable. You
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda >>>>>>>>>>>>>>>>>> liking it. yes i'm quite serious about refuting the >>>>>>>>>>>>>>>>>> church turing thesis. i demonstrate how an idealized >>>>>>>>>>>>>>>>>> human agent can compute that which is not turing >>>>>>>>>>>>>>>>>> computable.
Is there any way to prove that humans can compute >>>>>>>>>>>>>>>>> anyhing not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>>>>> compute a function that is strictly outside the bounds >>>>>>>>>>>>>>>> of turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>>>>> computer you
cant use it for any computation. If you can you can >>>>>>>>>>>>>>> compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in >>>>>>>>>>>>>> two different ways, which in of itself has not be proven. >>>>>>>>>>>>>
may be able to compute some values of an uncomputable >>>>>>>>>>>>> function but you
can't know that you can compute for arguments that will be >>>>>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, and >>>>>>>>>>>> how the algorithm differs from all the partial classifiers >>>>>>>>>>>> found in the turing computable space, and why no turing >>>>>>>>>>>> machine can truly implement the objective total algorithm >>>>>>>>>>>> even if it is mechanically computable.
You havn't posted a pointer to your article so we can't comment. >>>>>>>>>>> But in this discussion you have posted no evidence that you can >>>>>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as >>>>>>>>>> "evidence"?
Usually I wouldn't but it is possible to do so. One just need to >>>>>>>>> understand what it is evidence about.
i might be the first to realize: algorithms exist
independently in abstract from the more concrete mechanical >>>>>>>>>>>> implementations found in turing machine constructions, which >>>>>>>>>>>> are inherently more limited by their formally addressable >>>>>>>>>>>> nature.
THe concept of algorithm comtains that an algorithm can be >>>>>>>>>>> described.
But there is no known way to describe an anlgorithm that >>>>>>>>>>> cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine >>>>>>>>>> model directly to express algorithms, we use it as a
fundamental basis for mechanical computation, but the way we >>>>>>>>>> discuss algorithms is far more high level
Yes, a Turing machine is not a practical way of doing things. >>>>>>>>> It is
a mathematicial model that is useful when one wants to probe that >>>>>>>>> some function is or is not computable. But being computable >>>>>>>>> does not
mean that the computation can be performed quickly enough. The >>>>>>>>> theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. >>>>>>>> i'm address the theoretical domain of computability, not complexity >>>>>>>>
the only difference between the agent's algorithm and the >>>>>>>>>> partial classifiers that exist in turing machines, is that a >>>>>>>>>> partial classifier must deal with self-references, whereas the >>>>>>>>>> agent does not have to logically reckon about that because >>>>>>>>>> it's not possible to create a direct reference to
computational process, again my paper will go into more detail >>>>>>>>>> here specifically
Whether something is a self-reference is a matter of
interpretation.
an true self-reference is not a matter of interpretation. for a >>>>>>>> running machine this is an exact copy of the source code for the >>>>>>>> running machine
Whithout any interpretation there are no references, only synbols. >>>>>>> Without references there are no self-references.
a self-reference is a finite length value of data that encodes the >>>>>> exact transition table for the running machine
That's not a reference, it is a self-description. Though the running
that's what a self-reference is for turing machines, it can only
reference itself by an exact copy
It is not a copy, it is a description. A copy of a Turing machine is a
Turing machine, which is as unaccessible as self.
it's a copy (in some encoding) of the transition table the we use to
define and then refer to a particular machine, and what it
specifically computes.
The same behaviour can be presented with different transition tables in
the same language. Trivial changes include the order of the rules and
the naming of the states. In addition tape symbols that are not used for input nor output can be replaced. THerefore it is not tirivial to
determine whether the table describes self. And in any case, it does not refer to self instead of a similar one as both are described by the same table.
it's how machines reference to each other. it's how a machine can
reference itself, including referencing any particular value it can
computes
Machines can describe themselves or other machines but a description
is not a reference: another machine similar to self is not self but
is described by the same description.
A description does not refer to a partuclar machine. A description that
describes a machine also describes copies of that machine.
machine does not care and hardly knows whether the description is a
self-descriptipn.
it matters for certain algos like partial semantic deciders that
must be aware of when they are deciding on a self-reference
For that they need to be able to identify a self-description. That is
not a trivial problem.
i never said it was trivial, just that it matters.
You never proved that it is possible.
sure the encoding is up to "interpretation", but given a specified >>>>>> (and correct) method of encoding machines, the self-reference is
exact and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
A string that is an exact self-reference in some interprete|ition may
refer to something else or hothing in another interpretation. An
uninterpreted string does not refer.
we can stick to handling one particular encoding of machines when it
comes how to reckon about undecidability within computing.
Does it matter that a problem can be solvable if presented one way
but unsolvable if preneted in another way?
i think we agree on this
An algrithm does not interprete, it just specifies computational >>>>>>>>> actions.
this isn't like a bad thing either, turing machines are >>>>>>>>>>>> great and incredibly useful. i'm trying to increase their >>>>>>>>>>>> productivity by resolving their limitations more accurately >>>>>>>>>>>> so we stop tripping over the halting problem as excuse to >>>>>>>>>>>> not be proving correctness for every single program we >>>>>>>>>>>> deploy...
no, testing isn't good enough bro, nor is the braindead way >>>>>>>>>>>> we go about producing and maintaining computing
infrastructure. the dumb fucking corpo ratrace to nowhere >>>>>>>>>>>> instead of producing the systems we not only need but >>>>>>>>>>>> deserve is just so ungodly
the agent can compute something outside the bounds of >>>>>>>>>>>>>> turing computability due to an issue of addressability, or >>>>>>>>>>>>>> lack thereof, which can't be simulated by a turing machine >>>>>>>>>>>>>> because any value computed by a turing machine is >>>>>>>>>>>>>> necessarily addressable
That has not been proven. There is no way to implement an >>>>>>>>>>>>> uncountably
infinite address space and any finite or countably infinite is >>>>>>>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a >>>>>>>>>>>> mechanical discontinuity, and i can only explain by properly >>>>>>>>>>>> describing the justifying thought experiment
A finite or countable address space is fully discontinuous >>>>>>>>>>> anyway butthat does not prevent a simulation of full
accessibility. Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything
mechanical
relevant to algorithms?
a halting classifier/decider, even if only partial, needs
genuine access to it's own source code in order to function
optimally
If you want to talk about optimization you must not talk about
Turing
machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to >>>>>> optimal functionality, ei deciding some maximal subset of machines >>>>>> within a given semantic set (like set of halting machine, or set
of circle-free machine)
Then you should use some other word. Words derived from "optimum" are >>>>> understood to refer performance and resource consumption aspectes of >>>>> computation.
i explained my usage
Even with an explanation it is confusing. Another word or phrase could
be better.
thank you for ur input
You are welcome.
There are problems where every partial algorithm fails to compute for >>>>> some argument that another partial agorithm computes. One example is >>>>> the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect >>>>>> you to accept that without reading the proof i have to yet to post. >>>>>THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of
turing machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Ordinary computers perform quite well without any ability to access >>>>>>> their own "source code".
sure, the point is there exist some algos that require a self-
reference
Not proven.
while this can be implemented programmatically using a quine, >>>>>>>> it's not by default a mechanism of turing machines, so anyNo, it is an essential aspect of the meanings of the words.
random program does not have access to their own source code, >>>>>>>> only ones implemented with quines have definitive access to
that. the rest struggle from a mechanical limitation, and that's >>>>>>>> the point of the example
sure, many/most algos may not need it, but some do, and unless >>>>>>>> they have a programmatic solution they struggle from a what is a >>>>>>>> mechanical discontinuity
it's like trying to program a random turing machine to
directly access it's own source code ... the information
exists in abstract, but the turing machine model does not have >>>>>>>>>> a mechanical means of accessing it (barring a program
implemented with a genuine quine, but those are exceptions >>>>>>>>>> stemming from programmatic solutions, not the fundamental >>>>>>>>>> mechanics of the machine)
An algorithm cannot and need not access its "source code". It >>>>>>>>> knows
the argument and that fully determines the value of the function. >>>>>>>>>> or it's like asking a turing machine being simulated by
another to arbitrarily access values from the machine that is >>>>>>>>>> simulating it... that's just not mechanically possible.
The simulating machine can use any value it can access. But the >>>>>>>>> process
is not a simulation if those values are not present in the real >>>>>>>>> thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation. >>>>>>>
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world >>>>> whereas "algorithm" refers to a mathematical concept. The real world >>>>> does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
An idealized machine does not have specific mechanics. The idealization
yes it does. it has a head. and a tape. and various commands it can
process in accordance with a transition table that then has mechanical
effects on that head and tape. those are the mechanics of the
idealized computing machine, and that's how i'm using the word
Those are mathematical descriptions. Perhaps you mean systematic?
i explained my usage
omits unimprtant implementation details. It may avoid some constraints
of real computers like the requiremt that every machine instruction
must perform a Turing-computable function. Or it may have additional
restrictins that real computers have not. But neither restrictins are
"mechanical", only functional.
but what i'm trying to convey is that a mechanical discontinuity
happens when a computation run on a turing machine lacks a
mechanism to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it.
That is an unavoidable consequence of bad presentation.
it can also be the consequence of bad listening, which is really quite
endemic in online discussion
In case of bad listening the cause and consequences are on the same side
so the other side needn't care.
communication is a two way street
Not always. A can read what for example Turing has written but I can't
ask Turing about the exact meanings of his words. Unless you can write
a preentation that can be understood by readers who can't or don't ask
questions it doesn't matter whether you have discovered something. But
if it is useful or otherwise interesting someone with better skills of
presentation will discover it and publish.
jeez sentiments like that make me wonder if this god-forsaking species
is even worthy of further progress tbh ...
Worthy or not, it is able.
but i'm not doing it for the rest of ya'll. i'm doing it to build a
better world for my kid, so that he doesn't need to suffer thru a
world floundering around in a rather asinine implementation of general
computing that even remotely do what we need it do, to be frank
On 9/4/26 1:37 AM, Mikko wrote:
On 03/09/2026 19:39, dart200 wrote:
On 9/3/26 1:06 AM, Mikko wrote:
On 02/09/2026 17:56, dart200 wrote:
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:that's what a self-reference is for turing machines, it can only
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:There is no known method to compute what is not Turing >>>>>>>>>>>>>> computable. You
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda >>>>>>>>>>>>>>>>>>> liking it. yes i'm quite serious about refuting the >>>>>>>>>>>>>>>>>>> church turing thesis. i demonstrate how an idealized >>>>>>>>>>>>>>>>>>> human agent can compute that which is not turing >>>>>>>>>>>>>>>>>>> computable.
Is there any way to prove that humans can compute >>>>>>>>>>>>>>>>>> anyhing not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>>>>>> compute a function that is strictly outside the bounds >>>>>>>>>>>>>>>>> of turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>>>>>> computer you
cant use it for any computation. If you can you can >>>>>>>>>>>>>>>> compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in >>>>>>>>>>>>>>> two different ways, which in of itself has not be proven. >>>>>>>>>>>>>>
may be able to compute some values of an uncomputable >>>>>>>>>>>>>> function but you
can't know that you can compute for arguments that will be >>>>>>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, >>>>>>>>>>>>> and how the algorithm differs from all the partial
classifiers found in the turing computable space, and why >>>>>>>>>>>>> no turing machine can truly implement the objective total >>>>>>>>>>>>> algorithm even if it is mechanically computable.
You havn't posted a pointer to your article so we can't >>>>>>>>>>>> comment.
But in this discussion you have posted no evidence that you can >>>>>>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as >>>>>>>>>>> "evidence"?
Usually I wouldn't but it is possible to do so. One just need to >>>>>>>>>> understand what it is evidence about.
i might be the first to realize: algorithms exist
independently in abstract from the more concrete mechanical >>>>>>>>>>>>> implementations found in turing machine constructions, >>>>>>>>>>>>> which are inherently more limited by their formally >>>>>>>>>>>>> addressable nature.
THe concept of algorithm comtains that an algorithm can be >>>>>>>>>>>> described.
But there is no known way to describe an anlgorithm that >>>>>>>>>>>> cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine >>>>>>>>>>> model directly to express algorithms, we use it as a
fundamental basis for mechanical computation, but the way we >>>>>>>>>>> discuss algorithms is far more high level
Yes, a Turing machine is not a practical way of doing things. >>>>>>>>>> It is
a mathematicial model that is useful when one wants to probe that >>>>>>>>>> some function is or is not computable. But being computable >>>>>>>>>> does not
mean that the computation can be performed quickly enough. The >>>>>>>>>> theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs
complexity. i'm address the theoretical domain of
computability, not complexity
the only difference between the agent's algorithm and the >>>>>>>>>>> partial classifiers that exist in turing machines, is that a >>>>>>>>>>> partial classifier must deal with self-references, whereas >>>>>>>>>>> the agent does not have to logically reckon about that
because it's not possible to create a direct reference to >>>>>>>>>>> computational process, again my paper will go into more >>>>>>>>>>> detail here specifically
Whether something is a self-reference is a matter of
interpretation.
an true self-reference is not a matter of interpretation. for a >>>>>>>>> running machine this is an exact copy of the source code for >>>>>>>>> the running machine
Whithout any interpretation there are no references, only synbols. >>>>>>>> Without references there are no self-references.
a self-reference is a finite length value of data that encodes
the exact transition table for the running machine
That's not a reference, it is a self-description. Though the running >>>>>
reference itself by an exact copy
It is not a copy, it is a description. A copy of a Turing machine is a >>>> Turing machine, which is as unaccessible as self.
it's a copy (in some encoding) of the transition table the we use to
define and then refer to a particular machine, and what it
specifically computes.
The same behaviour can be presented with different transition tables in
those are different machines even if they have the same behavior.
machine identity is defined by the /exact/ same transition table.
i get that machine equivalence can be tricky, but let me define some language to specify the various relations:
identical/self-equivalence: this is when two descriptions are the /
exact/ same transition table and therefore the same string
isomorphic equivalence: this is when two machines may not have the same transition table, but produce the /exact/ same series of steps in the computations they produce. to be more precise because for example state names can still differ between isomorphic machines, i define this more precisely as the same output bits being written at the same steps in the computation.
functional/turing equivalence: this is when two machines produce the
same output even if not thru the exact same series of steps.
to clarify how "output" is defined here for turing machines (which can
just write to a tape), i'm reusing turing's convention from his paper:
the tape is programmatically divided into cells of F-cells and E-cells. F-cells are write only, done so in order, and consist of the defined "output" for what the machine is computing. E-cells are for all the temporary tape state that is not the direct output of the machine.
turing wrote the very first turing machine description with this
convention in mind.
the same language. Trivial changes include the order of the rules and
the naming of the states. In addition tape symbols that are not used for
input nor output can be replaced. THerefore it is not tirivial to
determine whether the table describes self. And in any case, it does not
refer to self instead of a similar one as both are described by the same
table.
it's how machines reference to each other. it's how a machine can
reference itself, including referencing any particular value it can
computes
Machines can describe themselves or other machines but a description
is not a reference: another machine similar to self is not self but
is described by the same description.
u seem to be arguing that self-references don't actually exist... uhhh
ok, i don't care for things that don't actually exist, so i'm not going
to use a label for them
i'm using the term self-reference to label when a machines are referring
to their own exact description, as that description is semantically equivalent when simulated within another machine as it is when run on
it's own. idk why ur arguing about this, it seems kinda pointless.
classic usenet, eh???
A description does not refer to a partuclar machine. A description that >>>> describes a machine also describes copies of that machine.
machine does not care and hardly knows whether the description is a >>>>>> self-descriptipn.
it matters for certain algos like partial semantic deciders that
must be aware of when they are deciding on a self-reference
For that they need to be able to identify a self-description. That is
not a trivial problem.
i never said it was trivial, just that it matters.
You never proved that it is possible.
sure the encoding is up to "interpretation", but given a
specified (and correct) method of encoding machines, the self-
reference is exact and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
A string that is an exact self-reference in some interprete|ition may
refer to something else or hothing in another interpretation. An
uninterpreted string does not refer.
we can stick to handling one particular encoding of machines when it
comes how to reckon about undecidability within computing.
Does it matter that a problem can be solvable if presented one way
but unsolvable if preneted in another way?
because all turing-computable sequences can be found computed by some machine within the total enumeration of all machines in a single turing- complete language, and therefore covers everything that is possibly computable by a turing machine
are there infinite ways of expressing that same thing becuase there are infinite ways of encoding turing machines? sure, but the point is
addressing undecidability within a complete expression of everything
that is computable, not trying to address the complexity involved with translating the infinite ways of expressing the same thing
those are different issues and i'm addressing the undecidability part,
not the translation part. and yes you'll prolly keep insisting it
matters but when enumerating over all machines, it is only necessary to
do so in one turing-complete language. we do this so it's possible to
grasp at what exactly are the limits of computability. throwing a bunch
of arbitrarily complexity in there muddles the more fundamental issue
and makes it unreasonable to reckon about ... and therefore is counter productive
i think we agree on this
An algrithm does not interprete, it just specifies computational >>>>>>>>>> actions.
What does "mechanical discontinuity" mean? How is anything >>>>>>>>>> mechanicalthis isn't like a bad thing either, turing machines are >>>>>>>>>>>>> great and incredibly useful. i'm trying to increase their >>>>>>>>>>>>> productivity by resolving their limitations more accurately >>>>>>>>>>>>> so we stop tripping over the halting problem as excuse to >>>>>>>>>>>>> not be proving correctness for every single program we >>>>>>>>>>>>> deploy...A finite or countable address space is fully discontinuous >>>>>>>>>>>> anyway butthat does not prevent a simulation of full
no, testing isn't good enough bro, nor is the braindead way >>>>>>>>>>>>> we go about producing and maintaining computing
infrastructure. the dumb fucking corpo ratrace to nowhere >>>>>>>>>>>>> instead of producing the systems we not only need but >>>>>>>>>>>>> deserve is just so ungodly
the agent can compute something outside the bounds of >>>>>>>>>>>>>>> turing computability due to an issue of addressability, >>>>>>>>>>>>>>> or lack thereof, which can't be simulated by a turing >>>>>>>>>>>>>>> machine because any value computed by a turing machine is >>>>>>>>>>>>>>> necessarily addressable
That has not been proven. There is no way to implement an >>>>>>>>>>>>>> uncountably
infinite address space and any finite or countably >>>>>>>>>>>>>> infinite is
accessible.
it's not uncountability that prevents the addressing, it's >>>>>>>>>>>>> a mechanical discontinuity, and i can only explain by >>>>>>>>>>>>> properly describing the justifying thought experiment >>>>>>>>>>>>
accessibility. Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one >>>>>>>>>>
relevant to algorithms?
a halting classifier/decider, even if only partial, needs
genuine access to it's own source code in order to function >>>>>>>>> optimally
If you want to talk about optimization you must not talk about >>>>>>>> Turing
machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to >>>>>>> optimal functionality, ei deciding some maximal subset of
machines within a given semantic set (like set of halting
machine, or set of circle-free machine)
Then you should use some other word. Words derived from "optimum" are >>>>>> understood to refer performance and resource consumption aspectes of >>>>>> computation.
i explained my usage
Even with an explanation it is confusing. Another word or phrase could >>>> be better.
thank you for ur input
You are welcome.
yes it does. it has a head. and a tape. and various commands it canThere are problems where every partial algorithm fails to compute for >>>>>> some argument that another partial agorithm computes. One example is >>>>>> the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect >>>>>>> you to accept that without reading the proof i have to yet to post. >>>>>>THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of >>>>>>> turing machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Ordinary computers perform quite well without any ability to access >>>>>>>> their own "source code".
sure, the point is there exist some algos that require a self-
reference
Not proven.
while this can be implemented programmatically using a quine, >>>>>>>>> it's not by default a mechanism of turing machines, so any
random program does not have access to their own source code, >>>>>>>>> only ones implemented with quines have definitive access to >>>>>>>>> that. the rest struggle from a mechanical limitation, and
that's the point of the example
sure, many/most algos may not need it, but some do, and unless >>>>>>>>> they have a programmatic solution they struggle from a what is >>>>>>>>> a mechanical discontinuity
it's like trying to program a random turing machine to
directly access it's own source code ... the information >>>>>>>>>>> exists in abstract, but the turing machine model does not >>>>>>>>>>> have a mechanical means of accessing it (barring a program >>>>>>>>>>> implemented with a genuine quine, but those are exceptions >>>>>>>>>>> stemming from programmatic solutions, not the fundamental >>>>>>>>>>> mechanics of the machine)
An algorithm cannot and need not access its "source code". It >>>>>>>>>> knows
the argument and that fully determines the value of the function. >>>>>>>>>>> or it's like asking a turing machine being simulated by >>>>>>>>>>> another to arbitrarily access values from the machine that is >>>>>>>>>>> simulating it... that's just not mechanically possible.
The simulating machine can use any value it can access. But >>>>>>>>>> the process
is not a simulation if those values are not present in the >>>>>>>>>> real thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical
limitation.
No, it is an essential aspect of the meanings of the words.
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world >>>>>> whereas "algorithm" refers to a mathematical concept. The real world >>>>>> does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
An idealized machine does not have specific mechanics. The idealization >>>
process in accordance with a transition table that then has
mechanical effects on that head and tape. those are the mechanics of
the idealized computing machine, and that's how i'm using the word
Those are mathematical descriptions. Perhaps you mean systematic?
i call it a mechanical discontinuity because of a lack of specified mechanism within the mathematical model
i explained my usage
omits unimprtant implementation details. It may avoid some constraints >>>> of real computers like the requiremt that every machine instruction
must perform a Turing-computable function. Or it may have additional
restrictins that real computers have not. But neither restrictins are
"mechanical", only functional.
but what i'm trying to convey is that a mechanical discontinuity >>>>>>> happens when a computation run on a turing machine lacks a
mechanism to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it.
That is an unavoidable consequence of bad presentation.
it can also be the consequence of bad listening, which is really
quite endemic in online discussion
In case of bad listening the cause and consequences are on the same side
so the other side needn't care.
i'm definitely affects, however indirectly, by all the ignorance
sustained thru poor listening skills
communication is a two way street
Not always. A can read what for example Turing has written but I can't >>>> ask Turing about the exact meanings of his words. Unless you can write >>>> a preentation that can be understood by readers who can't or don't ask >>>> questions it doesn't matter whether you have discovered something. But >>>> if it is useful or otherwise interesting someone with better skills of >>>> presentation will discover it and publish.
jeez sentiments like that make me wonder if this god-forsaking
species is even worthy of further progress tbh ...
Worthy or not, it is able.
growth isn't the same thing as progress
but i'm not doing it for the rest of ya'll. i'm doing it to build a
better world for my kid, so that he doesn't need to suffer thru a
world floundering around in a rather asinine implementation of
general computing that even remotely do what we need it do, to be frank
On 9/4/26 1:37 AM, Mikko wrote:
On 03/09/2026 19:39, dart200 wrote:
On 9/3/26 1:06 AM, Mikko wrote:
On 02/09/2026 17:56, dart200 wrote:
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:that's what a self-reference is for turing machines, it can only
On 8/31/26 11:44 PM, Mikko wrote:
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:There is no known method to compute what is not Turing >>>>>>>>>>>>>> computable. You
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda >>>>>>>>>>>>>>>>>>> liking it. yes i'm quite serious about refuting the >>>>>>>>>>>>>>>>>>> church turing thesis. i demonstrate how an idealized >>>>>>>>>>>>>>>>>>> human agent can compute that which is not turing >>>>>>>>>>>>>>>>>>> computable.
Is there any way to prove that humans can compute >>>>>>>>>>>>>>>>>> anyhing not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>>>>>> compute a function that is strictly outside the bounds >>>>>>>>>>>>>>>>> of turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>>>>>> computer you
cant use it for any computation. If you can you can >>>>>>>>>>>>>>>> compute the same
with a Turing machine.
that's just asserting the church-turing thesis at me in >>>>>>>>>>>>>>> two different ways, which in of itself has not be proven. >>>>>>>>>>>>>>
may be able to compute some values of an uncomputable >>>>>>>>>>>>>> function but you
can't know that you can compute for arguments that will be >>>>>>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, >>>>>>>>>>>>> and how the algorithm differs from all the partial
classifiers found in the turing computable space, and why >>>>>>>>>>>>> no turing machine can truly implement the objective total >>>>>>>>>>>>> algorithm even if it is mechanically computable.
You havn't posted a pointer to your article so we can't >>>>>>>>>>>> comment.
But in this discussion you have posted no evidence that you can >>>>>>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as >>>>>>>>>>> "evidence"?
Usually I wouldn't but it is possible to do so. One just need to >>>>>>>>>> understand what it is evidence about.
i might be the first to realize: algorithms exist
independently in abstract from the more concrete mechanical >>>>>>>>>>>>> implementations found in turing machine constructions, >>>>>>>>>>>>> which are inherently more limited by their formally >>>>>>>>>>>>> addressable nature.
THe concept of algorithm comtains that an algorithm can be >>>>>>>>>>>> described.
But there is no known way to describe an anlgorithm that >>>>>>>>>>>> cannot be
described as a Turing machine.
on the flip side we never actually use the turing machine >>>>>>>>>>> model directly to express algorithms, we use it as a
fundamental basis for mechanical computation, but the way we >>>>>>>>>>> discuss algorithms is far more high level
Yes, a Turing machine is not a practical way of doing things. >>>>>>>>>> It is
a mathematicial model that is useful when one wants to probe that >>>>>>>>>> some function is or is not computable. But being computable >>>>>>>>>> does not
mean that the computation can be performed quickly enough. The >>>>>>>>>> theory
of complexity of computation nees a different model.
i'm aware of the difference between computability vs
complexity. i'm address the theoretical domain of
computability, not complexity
the only difference between the agent's algorithm and the >>>>>>>>>>> partial classifiers that exist in turing machines, is that a >>>>>>>>>>> partial classifier must deal with self-references, whereas >>>>>>>>>>> the agent does not have to logically reckon about that
because it's not possible to create a direct reference to >>>>>>>>>>> computational process, again my paper will go into more >>>>>>>>>>> detail here specifically
Whether something is a self-reference is a matter of
interpretation.
an true self-reference is not a matter of interpretation. for a >>>>>>>>> running machine this is an exact copy of the source code for >>>>>>>>> the running machine
Whithout any interpretation there are no references, only synbols. >>>>>>>> Without references there are no self-references.
a self-reference is a finite length value of data that encodes
the exact transition table for the running machine
That's not a reference, it is a self-description. Though the running >>>>>
reference itself by an exact copy
It is not a copy, it is a description. A copy of a Turing machine is a >>>> Turing machine, which is as unaccessible as self.
it's a copy (in some encoding) of the transition table the we use to
define and then refer to a particular machine, and what it
specifically computes.
The same behaviour can be presented with different transition tables in
those are different machines even if they have the same behavior.
machine identity is defined by the /exact/ same transition table.
i get that machine equivalence can be tricky, but let me define some language to specify the various relations:
identical/self-equivalence: this is when two descriptions are the /
exact/ same transition table and therefore the same string
isomorphic equivalence: this is when two machines may not have the same transition table, but produce the /exact/ same series of steps in the computations they produce. to be more precise because for example state names can still differ between isomorphic machines, i define this more precisely as the same output bits being written at the same steps in the computation.
functional/turing equivalence: this is when two machines produce the
same output even if not thru the exact same series of steps.
to clarify how "output" is defined here for turing machines (which can
just write to a tape), i'm reusing turing's convention from his paper:
the tape is programmatically divided into cells of F-cells and E-cells. F-cells are write only, done so in order, and consist of the defined "output" for what the machine is computing. E-cells are for all the temporary tape state that is not the direct output of the machine.
turing wrote the very first turing machine description with this
convention in mind.
the same language. Trivial changes include the order of the rules and
the naming of the states. In addition tape symbols that are not used for
input nor output can be replaced. THerefore it is not tirivial to
determine whether the table describes self. And in any case, it does not
refer to self instead of a similar one as both are described by the same
table.
it's how machines reference to each other. it's how a machine can
reference itself, including referencing any particular value it can
computes
Machines can describe themselves or other machines but a description
is not a reference: another machine similar to self is not self but
is described by the same description.
u seem to be arguing that self-references don't actually exist... uhhh
ok, i don't care for things that don't actually exist, so i'm not going
to use a label for them
i'm using the term self-reference to label when a machines are referring
to their own exact description, as that description is semantically equivalent when simulated within another machine as it is when run on
it's own. idk why ur arguing about this, it seems kinda pointless.
classic usenet, eh???
A description does not refer to a partuclar machine. A description that >>>> describes a machine also describes copies of that machine.
machine does not care and hardly knows whether the description is a >>>>>> self-descriptipn.
it matters for certain algos like partial semantic deciders that
must be aware of when they are deciding on a self-reference
For that they need to be able to identify a self-description. That is
not a trivial problem.
i never said it was trivial, just that it matters.
You never proved that it is possible.
sure the encoding is up to "interpretation", but given a
specified (and correct) method of encoding machines, the self-
reference is exact and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
A string that is an exact self-reference in some interprete|ition may
refer to something else or hothing in another interpretation. An
uninterpreted string does not refer.
we can stick to handling one particular encoding of machines when it
comes how to reckon about undecidability within computing.
Does it matter that a problem can be solvable if presented one way
but unsolvable if preneted in another way?
because all turing-computable sequences can be found computed by some machine within the total enumeration of all machines in a single turing- complete language, and therefore covers everything that is possibly computable by a turing machine
are there infinite ways of expressing that same thing becuase there are infinite ways of encoding turing machines? sure, but the point is
addressing undecidability within a complete expression of everything
that is computable, not trying to address the complexity involved with translating the infinite ways of expressing the same thing
those are different issues and i'm addressing the undecidability part,
not the translation part. and yes you'll prolly keep insisting it
matters but when enumerating over all machines, it is only necessary to
do so in one turing-complete language. we do this so it's possible to
grasp at what exactly are the limits of computability. throwing a bunch
of arbitrarily complexity in there muddles the more fundamental issue
and makes it unreasonable to reckon about ... and therefore is counter productive
i think we agree on this
An algrithm does not interprete, it just specifies computational >>>>>>>>>> actions.
What does "mechanical discontinuity" mean? How is anything >>>>>>>>>> mechanicalthis isn't like a bad thing either, turing machines are >>>>>>>>>>>>> great and incredibly useful. i'm trying to increase their >>>>>>>>>>>>> productivity by resolving their limitations more accurately >>>>>>>>>>>>> so we stop tripping over the halting problem as excuse to >>>>>>>>>>>>> not be proving correctness for every single program we >>>>>>>>>>>>> deploy...A finite or countable address space is fully discontinuous >>>>>>>>>>>> anyway butthat does not prevent a simulation of full
no, testing isn't good enough bro, nor is the braindead way >>>>>>>>>>>>> we go about producing and maintaining computing
infrastructure. the dumb fucking corpo ratrace to nowhere >>>>>>>>>>>>> instead of producing the systems we not only need but >>>>>>>>>>>>> deserve is just so ungodly
the agent can compute something outside the bounds of >>>>>>>>>>>>>>> turing computability due to an issue of addressability, >>>>>>>>>>>>>>> or lack thereof, which can't be simulated by a turing >>>>>>>>>>>>>>> machine because any value computed by a turing machine is >>>>>>>>>>>>>>> necessarily addressable
That has not been proven. There is no way to implement an >>>>>>>>>>>>>> uncountably
infinite address space and any finite or countably >>>>>>>>>>>>>> infinite is
accessible.
it's not uncountability that prevents the addressing, it's >>>>>>>>>>>>> a mechanical discontinuity, and i can only explain by >>>>>>>>>>>>> properly describing the justifying thought experiment >>>>>>>>>>>>
accessibility. Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one >>>>>>>>>>
relevant to algorithms?
a halting classifier/decider, even if only partial, needs
genuine access to it's own source code in order to function >>>>>>>>> optimally
If you want to talk about optimization you must not talk about >>>>>>>> Turing
machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to >>>>>>> optimal functionality, ei deciding some maximal subset of
machines within a given semantic set (like set of halting
machine, or set of circle-free machine)
Then you should use some other word. Words derived from "optimum" are >>>>>> understood to refer performance and resource consumption aspectes of >>>>>> computation.
i explained my usage
Even with an explanation it is confusing. Another word or phrase could >>>> be better.
thank you for ur input
You are welcome.
yes it does. it has a head. and a tape. and various commands it canThere are problems where every partial algorithm fails to compute for >>>>>> some argument that another partial agorithm computes. One example is >>>>>> the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect >>>>>>> you to accept that without reading the proof i have to yet to post. >>>>>>THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of >>>>>>> turing machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Ordinary computers perform quite well without any ability to access >>>>>>>> their own "source code".
sure, the point is there exist some algos that require a self-
reference
Not proven.
while this can be implemented programmatically using a quine, >>>>>>>>> it's not by default a mechanism of turing machines, so any
random program does not have access to their own source code, >>>>>>>>> only ones implemented with quines have definitive access to >>>>>>>>> that. the rest struggle from a mechanical limitation, and
that's the point of the example
sure, many/most algos may not need it, but some do, and unless >>>>>>>>> they have a programmatic solution they struggle from a what is >>>>>>>>> a mechanical discontinuity
it's like trying to program a random turing machine to
directly access it's own source code ... the information >>>>>>>>>>> exists in abstract, but the turing machine model does not >>>>>>>>>>> have a mechanical means of accessing it (barring a program >>>>>>>>>>> implemented with a genuine quine, but those are exceptions >>>>>>>>>>> stemming from programmatic solutions, not the fundamental >>>>>>>>>>> mechanics of the machine)
An algorithm cannot and need not access its "source code". It >>>>>>>>>> knows
the argument and that fully determines the value of the function. >>>>>>>>>>> or it's like asking a turing machine being simulated by >>>>>>>>>>> another to arbitrarily access values from the machine that is >>>>>>>>>>> simulating it... that's just not mechanically possible.
The simulating machine can use any value it can access. But >>>>>>>>>> the process
is not a simulation if those values are not present in the >>>>>>>>>> real thing
the simulation itendes to simulate.
the point is dude that this is an example of mechanical
limitation.
No, it is an essential aspect of the meanings of the words.
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world >>>>>> whereas "algorithm" refers to a mathematical concept. The real world >>>>>> does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
An idealized machine does not have specific mechanics. The idealization >>>
process in accordance with a transition table that then has
mechanical effects on that head and tape. those are the mechanics of
the idealized computing machine, and that's how i'm using the word
Those are mathematical descriptions. Perhaps you mean systematic?
i call it a mechanical discontinuity because of a lack of specified mechanism within the mathematical model
i explained my usage
omits unimprtant implementation details. It may avoid some constraints >>>> of real computers like the requiremt that every machine instruction
must perform a Turing-computable function. Or it may have additional
restrictins that real computers have not. But neither restrictins are
"mechanical", only functional.
but what i'm trying to convey is that a mechanical discontinuity >>>>>>> happens when a computation run on a turing machine lacks a
mechanism to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it.
That is an unavoidable consequence of bad presentation.
it can also be the consequence of bad listening, which is really
quite endemic in online discussion
In case of bad listening the cause and consequences are on the same side
so the other side needn't care.
i'm definitely affects, however indirectly, by all the ignorance
sustained thru poor listening skills
communication is a two way street
Not always. A can read what for example Turing has written but I can't >>>> ask Turing about the exact meanings of his words. Unless you can write >>>> a preentation that can be understood by readers who can't or don't ask >>>> questions it doesn't matter whether you have discovered something. But >>>> if it is useful or otherwise interesting someone with better skills of >>>> presentation will discover it and publish.
jeez sentiments like that make me wonder if this god-forsaking
species is even worthy of further progress tbh ...
Worthy or not, it is able.
growth isn't the same thing as progress
--but i'm not doing it for the rest of ya'll. i'm doing it to build a
better world for my kid, so that he doesn't need to suffer thru a
world floundering around in a rather asinine implementation of
general computing that even remotely do what we need it do, to be frank
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a function that is strictly outside the bounds of turing computability
computable? Much can be computed with a Turing computable partial
method.
at this point i suspect there to be machines which may not be
"computable" by any partial decider, but even that is just not quite
equal to what an idealized agent can mechanically prove in a finite
amount of steps (which is necessarily not computable by any turing machine)
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:
On 8/31/26 11:44 PM, Mikko wrote:th
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking >>>>>>>>>>>>>>> it. yes i'm quite serious about refuting the church turing >>>>>>>>>>>>>>> thesis. i demonstrate how an idealized human agent can >>>>>>>>>>>>>>> compute that which is not turing computable.
Is there any way to prove that humans can compute anyhing >>>>>>>>>>>>>> not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>> compute a function that is strictly outside the bounds of >>>>>>>>>>>>> turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>> computer you
cant use it for any computation. If you can you can compute >>>>>>>>>>>> the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two >>>>>>>>>>> different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing
computable. You
may be able to compute some values of an uncomputable function >>>>>>>>>> but you
can't know that you can compute for arguments that will be >>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, and how >>>>>>>>> the algorithm differs from all the partial classifiers found in >>>>>>>>> the turing computable space, and why no turing machine can truly >>>>>>>>> implement the objective total algorithm even if it is
mechanically computable.
You havn't posted a pointer to your article so we can't comment. >>>>>>>> But in this discussion you have posted no evidence that you can >>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as
"evidence"?
Usually I wouldn't but it is possible to do so. One just need to
understand what it is evidence about.
i might be the first to realize: algorithms exist independently >>>>>>>>> in abstract from the more concrete mechanical implementations >>>>>>>>> found in turing machine constructions, which are inherently more >>>>>>>>> limited by their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be
described.
But there is no known way to describe an anlgorithm that cannot be >>>>>>>> described as a Turing machine.
on the flip side we never actually use the turing machine model >>>>>>> directly to express algorithms, we use it as a fundamental basis >>>>>>> for mechanical computation, but the way we discuss algorithms is >>>>>>> far more high level
Yes, a Turing machine is not a practical way of doing things. It is >>>>>> a mathematicial model that is useful when one wants to probe that
some function is or is not computable. But being computable does not >>>>>> mean that the computation can be performed quickly enough. The theory >>>>>> of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. i'm >>>>> address the theoretical domain of computability, not complexity
an true self-reference is not a matter of interpretation. for a
the only difference between the agent's algorithm and the partial >>>>>>> classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does >>>>>>> not have to logically reckon about that because it's not possible >>>>>>> to create a direct reference to computational process, again my >>>>>>> paper will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation. >>>>>
running machine this is an exact copy of the source code for the
running machine
Whithout any interpretation there are no references, only synbols.
Without references there are no self-references.
a self-reference is a finite length value of data that encodes the
exact transition table for the running machine
That's not a reference, it is a self-description. Though the running
that's what a self-reference is for turing machines, it can only
reference itself by an exact copy
machine does not care and hardly knows whether the description is a
self-descriptipn.
it matters for certain algos like partial semantic deciders that must be aware of when they are deciding on a self-reference
sure the encoding is up to "interpretation", but given a specified
(and correct) method of encoding machines, the self-reference is exact
and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
i think we agree on this
An algrithm does not interprete, it just specifies computational
actions.
this isn't like a bad thing either, turing machines are great >>>>>>>>> and incredibly useful. i'm trying to increase their productivity >>>>>>>>> by resolving their limitations more accurately so we stop
tripping over the halting problem as excuse to not be proving >>>>>>>>> correctness for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we >>>>>>>>> go about producing and maintaining computing infrastructure. the >>>>>>>>> dumb fucking corpo ratrace to nowhere instead of producing the >>>>>>>>> systems we not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing >>>>>>>>>>> computability due to an issue of addressability, or lack >>>>>>>>>>> thereof, which can't be simulated by a turing machine because >>>>>>>>>>> any value computed by a turing machine is necessarily addressable >>>>>>>>>>That has not been proven. There is no way to implement an >>>>>>>>>> uncountably
infinite address space and any finite or countably infinite is >>>>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a >>>>>>>>> mechanical discontinuity, and i can only explain by properly >>>>>>>>> describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway >>>>>>>> butthat does not prevent a simulation of full accessibility.
Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical >>>>>> relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine
access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing
machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to
optimal functionality, ei deciding some maximal subset of machines
within a given semantic set (like set of halting machine, or set of
circle-free machine)
Then you should use some other word. Words derived from "optimum" are
understood to refer performance and resource consumption aspectes of
computation.
i explained my usage
There are problems where every partial algorithm fails to compute for
some argument that another partial agorithm computes. One example is
the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect you
to accept that without reading the proof i have to yet to post.
THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of turing
machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Ordinary computers perform quite well without any ability to access
their own "source code".
sure, the point is there exist some algos that require a self-reference
Not proven.
while this can be implemented programmatically using a quine, it's
not by default a mechanism of turing machines, so any random program >>>>> does not have access to their own source code, only ones implemented >>>>> with quines have definitive access to that. the rest struggle from a >>>>> mechanical limitation, and that's the point of the example
sure, many/most algos may not need it, but some do, and unless they >>>>> have a programmatic solution they struggle from a what is a
mechanical discontinuity
it's like trying to program a random turing machine to directly >>>>>>> access it's own source code ... the information exists in
abstract, but the turing machine model does not have a mechanical >>>>>>> means of accessing it (barring a program implemented with a
genuine quine, but those are exceptions stemming from programmatic >>>>>>> solutions, not the fundamental mechanics of the machine)
An algorithm cannot and need not access its "source code". It knows >>>>>> the argument and that fully determines the value of the function. >>>>>>> or it's like asking a turing machine being simulated by another to >>>>>>> arbitrarily access values from the machine that is simulating
it... that's just not mechanically possible.
The simulating machine can use any value it can access. But the
process
is not a simulation if those values are not present in the real thing >>>>>> the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation.
No, it is an essential aspect of the meanings of the words.
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world
whereas "algorithm" refers to a mathematical concept. The real world
does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
but what i'm trying to convey is that a mechanical discontinuity
happens when a computation run on a turing machine lacks a mechanism
to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it. communication is a two
way street dud, and if u don't accept ur half the responsibility i won't care to explain myself further to someone who doesn't care
i gave you two examples of where a lack of mechanism creates aYour examples were not clear. And examples are not very good for the
mechanical discontinuity, and if u don't want to consider them then i
cannot help you further here
purpose. Or at least, for a rough idea, you need counter-examples, too.
But complete definitions are clearer.
dart200 <user7160@newsgrouper.org.invalid> wrote:
On 9/2/26 1:04 AM, Mikko wrote:
On 01/09/2026 22:50, dart200 wrote:
On 8/31/26 11:44 PM, Mikko wrote:th
On 01/09/2026 00:35, dart200 wrote:
On 8/31/26 2:55 AM, Mikko wrote:
On 31/08/2026 04:17, dart200 wrote:
On 8/30/26 1:17 AM, Mikko wrote:
On 30/08/2026 09:51, dart200 wrote:
On 8/29/26 1:05 AM, Mikko wrote:
On 28/08/2026 10:40, dart200 wrote:
On 8/28/26 12:27 AM, Mikko wrote:
On 27/08/2026 22:50, dart200 wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking >>>>>>>>>>>>>>>> it. yes i'm quite serious about refuting the church turing >>>>>>>>>>>>>>>> thesis. i demonstrate how an idealized human agent can >>>>>>>>>>>>>>>> compute that which is not turing computable.
Is there any way to prove that humans can compute anyhing >>>>>>>>>>>>>>> not Turing
yes, i use the concept of an idealized human agent to >>>>>>>>>>>>>> compute a function that is strictly outside the bounds of >>>>>>>>>>>>>> turing computability
If you can't simulate that agent with a Turing-complete >>>>>>>>>>>>> computer you
cant use it for any computation. If you can you can compute >>>>>>>>>>>>> the same
with a Turing machine.
that's just asserting the church-turing thesis at me in two >>>>>>>>>>>> different ways, which in of itself has not be proven.
There is no known method to compute what is not Turing
computable. You
may be able to compute some values of an uncomputable function >>>>>>>>>>> but you
can't know that you can compute for arguments that will be >>>>>>>>>>> given later
unless you have a method.
my paper specifically details how that method can exist, and how >>>>>>>>>> the algorithm differs from all the partial classifiers found in >>>>>>>>>> the turing computable space, and why no turing machine can truly >>>>>>>>>> implement the objective total algorithm even if it is
mechanically computable.
You havn't posted a pointer to your article so we can't comment. >>>>>>>>> But in this discussion you have posted no evidence that you can >>>>>>>>> compute somthing that a Turing machine cannot.
i'm just serious: would you consider a thought experiment as
"evidence"?
Usually I wouldn't but it is possible to do so. One just need to >>>>>>> understand what it is evidence about.
i might be the first to realize: algorithms exist independently >>>>>>>>>> in abstract from the more concrete mechanical implementations >>>>>>>>>> found in turing machine constructions, which are inherently more >>>>>>>>>> limited by their formally addressable nature.
THe concept of algorithm comtains that an algorithm can be
described.
But there is no known way to describe an anlgorithm that cannot be >>>>>>>>> described as a Turing machine.
on the flip side we never actually use the turing machine model >>>>>>>> directly to express algorithms, we use it as a fundamental basis >>>>>>>> for mechanical computation, but the way we discuss algorithms is >>>>>>>> far more high level
Yes, a Turing machine is not a practical way of doing things. It is >>>>>>> a mathematicial model that is useful when one wants to probe that >>>>>>> some function is or is not computable. But being computable does not >>>>>>> mean that the computation can be performed quickly enough. The theory >>>>>>> of complexity of computation nees a different model.
i'm aware of the difference between computability vs complexity. i'm >>>>>> address the theoretical domain of computability, not complexity
an true self-reference is not a matter of interpretation. for a
the only difference between the agent's algorithm and the partial >>>>>>>> classifiers that exist in turing machines, is that a partial
classifier must deal with self-references, whereas the agent does >>>>>>>> not have to logically reckon about that because it's not possible >>>>>>>> to create a direct reference to computational process, again my >>>>>>>> paper will go into more detail here specifically
Whether something is a self-reference is a matter of interpretation. >>>>>>
running machine this is an exact copy of the source code for the
running machine
Whithout any interpretation there are no references, only synbols.
Without references there are no self-references.
a self-reference is a finite length value of data that encodes the
exact transition table for the running machine
That's not a reference, it is a self-description. Though the running
that's what a self-reference is for turing machines, it can only
reference itself by an exact copy
Nope, the problem is rCLTuring MachinesrCY are incapable of handling rCLreferencesrCY of any form, let alone rCLself-referencesrCY.
machine does not care and hardly knows whether the description is a
self-descriptipn.
it matters for certain algos like partial semantic deciders that must be
aware of when they are deciding on a self-reference
Nope, the problem is you rCLgrammarrCY is just invalid. Note that part of your
problem is that you want to express questions that use self-references when that is NOT in the allowed problem space. Part of the issue is that the
class of problems under concern are required to be rCLObjectiverCY, and thus have the same answer to any machine you pose it to, and thus it canrCOt refer to the machine the problem is being given to.
As to machines being able to detect that an input contains a machine based
on itself, that has been proven to be uncomputable. A fact you assume to
not be correct.
sure the encoding is up to "interpretation", but given a specified
(and correct) method of encoding machines, the self-reference is exact >>>> and not up to interpretation.
The meaning of "exact" also depends on interpretation.
it does not
i think we agree on this
An algrithm does not interprete, it just specifies computational >>>>>>> actions.
this isn't like a bad thing either, turing machines are great >>>>>>>>>> and incredibly useful. i'm trying to increase their productivity >>>>>>>>>> by resolving their limitations more accurately so we stop
tripping over the halting problem as excuse to not be proving >>>>>>>>>> correctness for every single program we deploy...
no, testing isn't good enough bro, nor is the braindead way we >>>>>>>>>> go about producing and maintaining computing infrastructure. the >>>>>>>>>> dumb fucking corpo ratrace to nowhere instead of producing the >>>>>>>>>> systems we not only need but deserve is just so ungodly
the agent can compute something outside the bounds of turing >>>>>>>>>>>> computability due to an issue of addressability, or lack >>>>>>>>>>>> thereof, which can't be simulated by a turing machine because >>>>>>>>>>>> any value computed by a turing machine is necessarily addressable >>>>>>>>>>>That has not been proven. There is no way to implement an >>>>>>>>>>> uncountably
infinite address space and any finite or countably infinite is >>>>>>>>>>> accessible.
it's not uncountability that prevents the addressing, it's a >>>>>>>>>> mechanical discontinuity, and i can only explain by properly >>>>>>>>>> describing the justifying thought experiment
A finite or countable address space is fully discontinuous anyway >>>>>>>>> butthat does not prevent a simulation of full accessibility. >>>>>>>>> Restrictions
in accessibility can also be simulated.
it's not a numerical discontinuity, it's a mechanical one
What does "mechanical discontinuity" mean? How is anything mechanical >>>>>>> relevant to algorithms?
a halting classifier/decider, even if only partial, needs genuine
access to it's own source code in order to function optimally
If you want to talk about optimization you must not talk about Turing >>>>> machines. They are never optimal.
by optimally i don't mean speed/time complexity, i'm referring to
optimal functionality, ei deciding some maximal subset of machines
within a given semantic set (like set of halting machine, or set of
circle-free machine)
Then you should use some other word. Words derived from "optimum" are
understood to refer performance and resource consumption aspectes of
computation.
i explained my usage
Typical technique of scammers send liars.
There are problems where every partial algorithm fails to compute for
some argument that another partial agorithm computes. One example is
the halting problem.
this maximal subset may be turing-complete, but i wouldn't expect you
to accept that without reading the proof i have to yet to post.
THat's right. Without a proof there is nothing.
actually, even correctly deciding a less-than-maximal subset of turing >>>> machines requires a true self-reference
In particular, that cannot be accepted without a proof.
Not proven.Ordinary computers perform quite well without any ability to access
their own "source code".
sure, the point is there exist some algos that require a self-reference >>>
while this can be implemented programmatically using a quine, it's >>>>>> not by default a mechanism of turing machines, so any random program >>>>>> does not have access to their own source code, only ones implemented >>>>>> with quines have definitive access to that. the rest struggle from a >>>>>> mechanical limitation, and that's the point of the exampleNo, it is an essential aspect of the meanings of the words.
sure, many/most algos may not need it, but some do, and unless they >>>>>> have a programmatic solution they struggle from a what is a
mechanical discontinuity
it's like trying to program a random turing machine to directly >>>>>>>> access it's own source code ... the information exists in
abstract, but the turing machine model does not have a mechanical >>>>>>>> means of accessing it (barring a program implemented with a
genuine quine, but those are exceptions stemming from programmatic >>>>>>>> solutions, not the fundamental mechanics of the machine)
An algorithm cannot and need not access its "source code". It knows >>>>>>> the argument and that fully determines the value of the function. >>>>>>>> or it's like asking a turing machine being simulated by another to >>>>>>>> arbitrarily access values from the machine that is simulating
it... that's just not mechanically possible.
The simulating machine can use any value it can access. But the
process
is not a simulation if those values are not present in the real thing >>>>>>> the simulation itendes to simulate.
the point is dude that this is an example of mechanical limitation. >>>>>
idk what ur arguing,
Meanings of the words. The word "mechanical" refers to the real world
whereas "algorithm" refers to a mathematical concept. The real world
does not limit mathematics in any way.
we're discussing the mechanics of an idealized computing machine
Something you need to actually DEFINE, and if not compatible with the rules of the field you claim to be working in just admits you donrCOt know what you are talking about.
This has been part of you problem, that you donrCOt actually understand the field you are talking about, or its rules, and you just prove that you donrCOt seem actually capable of understanding it.
but what i'm trying to convey is that a mechanical discontinuity
happens when a computation run on a turing machine lacks a mechanism
to directly access some specific information.
Whatever you were trying to comvay you failed. No other result is
possible without without a respect of the meanings of the words.
well you then similarly failed to understand it. communication is a two
way street dud, and if u don't accept ur half the responsibility i won't
care to explain myself further to someone who doesn't care
i gave you two examples of where a lack of mechanism creates aYour examples were not clear. And examples are not very good for the
mechanical discontinuity, and if u don't want to consider them then i
cannot help you further here
purpose. Or at least, for a rough idea, you need counter-examples, too.
But complete definitions are clearer.
dart200 <user7160@newsgrouper.org.invalid> wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a function
that is strictly outside the bounds of turing computability
But your rCLidealized human agentrCY doesnrCOt exist, and that number not on the
diagonal canrCOt be computed by an actual existing idealized human agent, they can only create a symbol for something that is actually unknown.
computable? Much can be computed with a Turing computable partial
method.
at this point i suspect there to be machines which may not be
"computable" by any partial decider, but even that is just not quite
equal to what an idealized agent can mechanically prove in a finite
amount of steps (which is necessarily not computable by any turing machine) >>
Your problem is you donrCOt understand that the rCLrulesrCY require you to be looking at things that can actually exist under the basic rules.
Your idealization is just a smoke screen to hide that you are trying to imagine things that are outside the allowable domain of machines.
It is well known in the field of Hyper Computability that there exist an infinite number of rCLLevel 0rCY problems that canrCOt be solved by machines limited to the normal rules of computability (being limited to finite rule sets and finite time) that can actually be solved by Level 1 Hyper Computation machines that relax those limits. Of course, the reason we
number the levels is because with level 1 computation machines, we can
create problem that these level 1 machines canrCOt compute, needing a level 2 machine, and so on and so forth. A Level N machine can solve problems using no more that level N-1 computation as their input.
Of course, one problem with Hyper Computation machines is they can not actually be made in a physical rCLlevel 0rCY universe like we live in, so are only theoretical/mathematical constructs.
dart200 <user7160@newsgrouper.org.invalid> wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm
quite serious about refuting the church turing thesis. i demonstrate
how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a function
that is strictly outside the bounds of turing computability
But your rCLidealized human agentrCY doesnrCOt exist, and that number not on the
diagonal canrCOt be computed by an actual existing idealized human agent, they can only create a symbol for something that is actually unknown.
computable? Much can be computed with a Turing computable partial
method.
at this point i suspect there to be machines which may not be
"computable" by any partial decider, but even that is just not quite
equal to what an idealized agent can mechanically prove in a finite
amount of steps (which is necessarily not computable by any turing machine) >>
Your problem is you donrCOt understand that the rCLrulesrCY require you to be looking at things that can actually exist under the basic rules.
Your idealization is just a smoke screen to hide that you are trying to imagine things that are outside the allowable domain of machines.
It is well known in the field of Hyper Computability that there exist an infinite number of rCLLevel 0rCY problems that canrCOt be solved by machines limited to the normal rules of computability (being limited to finite rule sets and finite time) that can actually be solved by Level 1 Hyper Computation machines that relax those limits. Of course, the reason we
number the levels is because with level 1 computation machines, we can
create problem that these level 1 machines canrCOt compute, needing a level 2 machine, and so on and so forth. A Level N machine can solve problems using no more that level N-1 computation as their input.
Of course, one problem with Hyper Computation machines is they can not actually be made in a physical rCLlevel 0rCY universe like we live in, so are only theoretical/mathematical constructs.
On 9/7/26 1:17 PM, Richard Damon wrote:
dart200 <user7160@newsgrouper.org.invalid> wrote:
On 8/27/26 12:49 AM, Mikko wrote:
On 27/08/2026 08:40, dart200 wrote:
title of my next paper is tentative, but i'm kinda liking it. yes i'm >>>>> quite serious about refuting the church turing thesis. i demonstrate >>>>> how an idealized human agent can compute that which is not turing
computable.
Is there any way to prove that humans can compute anyhing not Turing
yes, i use the concept of an idealized human agent to compute a function >>> that is strictly outside the bounds of turing computability
But your rCLidealized human agentrCY doesnrCOt exist, and that number not on
the
they exist as much as a turing machine does, which to say in theory they
can ...
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