AI/Machine Learning, Bharat and Bhartiya IT Industry

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Vayutuvan
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Re: AI/Machine Learning, Bharat and Bhartiya IT Industry

Post by Vayutuvan »

Just to be complete, teorth is Terence Tao's ghithub page.

https://github.com/teorth
Vayutuvan
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Re: AI/Machine Learning, Bharat and Bhartiya IT Industry

Post by Vayutuvan »

https://google-deepmind.github.io/forma ... s/397.html

The formal definition of eRDOS #397 is above. It is machine-readable, I suppose. Never mind. It is a Lean description of the problem. I am more familiar with HOL Light (which is written in Ocaml). I learnt Ocaml to follow some of the proofs in the HOL Light database. I found that syntax to be natural. Currently, Lean and Rocq (previously Coq) offer all the features and are the most popular.

Terence Tao made a post on Mathsodon on how LLMs can be useful in theorem proving (the end goal is to have a full-fledged automatic theorem provers - ATPs for short) using Interactive Theorem Provers, AKA Proof Assistants, coupled with LLMs. The important and key difference between ITPs and ATPs is that an ITP requires a human to guide it to prove/disprove a conjecture, whereas an ATP can prove/disprove a conjecture on its own.
Vayutuvan
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Re: AI/Machine Learning, Bharat and Bhartiya IT Industry

Post by Vayutuvan »

jatin
@jatinkrmalik
·
Jan 9
The reason why RAM has become four times more expensive is that a huge amount of RAM that has not yet been produced was purchased with non-existent money to be installed in GPUs that also have not yet been produced, in order to place them in data centers that have not yet been built, powered by infrastructure that may never appear, to satisfy demand that does not actually exist and to obtain profit that is mathematically impossible.
https://x.com/jatinkrmalik/status/20096 ... 18887?s=20

Also, jatin posted a graphic of the same.

Image
Amber G.
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Re: AI/Machine Learning, Bharat and Bhartiya IT Industry

Post by Amber G. »

For those who like to test or play with their favorite AI, there are a few problems in the math thread—you can use them to see how the AI approaches and solves them.
sanjaykumar
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Re: AI/Machine Learning, Bharat and Bhartiya IT Industry

Post by sanjaykumar »

sanjaykumar wrote: 12 Jan 2026 07:51 The mirror neurons is really short hand for circuits that act as an epigram of relevant external processes on consciousness.
That should be engram. Not epigram.
Vayutuvan
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Re: AI/Machine Learning, Bharat and Bhartiya IT Industry

Post by Vayutuvan »

I checked what an engram is on Wikipedia. My eyes glazed over. When I hear the term mirror, I think of something like mirror image symmetry. IOW, when we look at ourselves in a mirror, we see only left/right reversal but not up/down reversal. Maybe that has something to do with the bisymmetry of our eyes. VS Ramachandran posited that the ghost limb phenomenon is due to the existence of mirror neurons.

Could you please write a summary of how mirror neurons act as engrams? TIA.

(If folks feel it is off topic in this thread, we can continue in another thread.)
sanjaykumar
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Re: AI/Machine Learning, Bharat and Bhartiya IT Industry

Post by sanjaykumar »

Mirror neurons may be part of the circuitry of engrams involved in empathy. If not themselves some closely conceptual cousins.

There are many questions. How does theory of mind arise?

What is the evolutionary advantage of empathy to non kin?
Although we know mirror neurons involved in kinematic actions are not so responsive to different races.


The neuro circuitry is still mostly a black box. Sure one can trace circuits electrophysiologically or through fMRI, but that is not the same as a mechanistic understanding.

It is postulated that mirror circuits form with neurons that are more excitable. That seems to me to be begging the question.

At any rate, binary code is linear but the genetic code fundamentally is not. It is actually space time four dimensional. That is enzymes are meaningless without the temporal properties in addition to three dimensionality of proteins.

Perhaps a network of computer coding could simulate the genetic code. One advantage machines have is they do not have to code for the housekeeping functions to support cognition i.e. the human body.

It is possible that cognition will arise in machines as an emergent phenomenon, of course.
Some random thoughts.
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