From Newsgroup: sci.logic

Hi,

Nowadays, you have to be extremely careful when it
comes to inconsistencies and rounding errors. Especially
with LLMs, which don't actually have Alzheimer's.

But aligning to P can cause the AI to become
~P. It's still funny, maybe it has to do with
the fact that in classical logic, and also in

certain t-norm fuzzy logics, there is no
paraconsistency, and therefore inconsistencies
lead to "Ex Falso Quodlibet" explosions:

The Waluigi Effect (mega-post) https://www.lesswrong.com/posts/D7PumeYTDPfBTp3i7/the-waluigi-effect-mega-post

I dug this up because right now everyone is not
just talking about alignment, we've already reached
superalignment, because people suspect/hallucinate

superintelligence behind a few copied LLMs
offering chat services distributed across
servers to millions of people, and because

OpenAI ran some experiments with MAS (Multi-
Agent Systems) and published them, and the
public is now shocked.

Bye

P.S.: Waluigi is the antagonist to Luigi,
from Nintendo's Mario Kart

Mild Shock schrieb:

Hi,

Thats why I love deepseek, it just spits out:

"Kundalini is the rising energy rCo the serpent
at the base of the spine, the awakening that's
felt before it's understood, the experience
that's intense and real and not yet integrated.

People who have Kundalini experiences describe
them as overwhelming, transformative, and pre-verbal.
They feel like knowledge, but they're not articulable.
And the tradition itself warns that the energy

can rise without the practice and the grounding to
hold it rCo which is when it becomes destabilizing
rather than illuminating."

LoL

Bye

Mild Shock schrieb:

Hi,

Now you can compare this here from 2008
with modern AI Laptops for 500-1000 USD:

Google spotlights data center inner workings
https://web.archive.org/web/20131019063218/http://news.cnet.com/8301-10784_3-9955184-7.html


There is a striking similarity, only what
once occupied a rack, has now the size
of your plam, all inside one silicon chip:

- Multiple CPU cores on the same chip
- Multiple GPU units on the same chip
- Network on the same chip communication
- Crossbar caches on the same chip
- Disk controllers on the same chip
- Multi channel RAM access on the same chip

Pretty cool!

Bye

P.S.: Example such devices with iGPU:

Intel(R) Core(TM) Ultra 7 258V
AMD Ryzen AI 7 350 w/ Radeon 860M
Apple A18 Pro, Darwin Kernel Version 25.5.0
Snapdragon(R) X - X126100 - Qualcomm(R) Oryon(TM) CPU


Mild Shock schrieb:

Hi,

Remember when first all local AI was Python
and PyTorch APIs. And then suddently people started
using bare metal C/C++ Code. Here is the story:

How it started:

GPT-J or GPT-J-6B is an open-source large
language model (LLM) developed by EleutherAI
in 2021. As the name suggests, it is a
generative pre-trained transformer model
designed to produce human-like text that
continues from a prompt.
https://www.eleuther.ai/

How it was going [Georgi Gerganov]:

So a few days later comes out the LLaMA, I do
some calculations and I figure out rCLOkay, 65
billion parameters. You probably need about
40 gigs of RAM, with 4-bit quantization. So
this can run on a MacBook. Why not do it?rCY

Why I was able to do it so quickly - basically,
for all that I saw itrCOs pretty much GPT-J architecture
with some modifications, like some extra memorization
layers. ItrCOs minor changes. Basically, again, the
existing code for the GPT-J, I just simply
modified it there, it happened pretty quickly.
https://changelog.com/podcast/532

Georgi Gerganov, Bulgarian, now with Hugging
Face, ggml-cann also running on Chinese AI chips.
ggml Manifesto https://github.com/ggml-org/ggml

Bye

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