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Where did the Neuron in Turing Machine come from? (Re: From Turing-Test to Birch++-Test [Professor Yang-Hui He])

From Mild Shock <janburse@fastmail.fm>
Newsgroups sci.physics, sci.physics.relativity
Subject Where did the Neuron in Turing Machine come from? (Re: From Turing-Test to Birch++-Test [Professor Yang-Hui He])
Date 2025-12-10 15:02 +0100
Message-ID <10hbugr$1ckmg$2@solani.org> (permalink)
References <10e229s$rr1b$4@solani.org> <10h6or4$1b491$2@solani.org> <10hbu4e$1ckhe$2@solani.org>

Cross-posted to 2 groups.

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Hi,

Its seems I shocked people when I was talking about
neurons on the head of a Turing Machine. Did
I go mad? Halcuinating like on LSD?

Unfortunately not:

A provably stable neural network Turing Machine
https://arxiv.org/abs/2006.03651

Currently I would like to be able to add a simple
stack to a NPU, for a problem I have. Somehow
I have the feeling its doable via softmax,

in a limited way. Any ideas?

Bye

P.S.: A stack is possibly the simples form
of a turing machine tape. The turing machine
would be restricted so that head movements

only correspond to push and pop. Quiet amazing!

Mild Shock schrieb:
> Hi,
> 
> Since AI passed the Turing Test in 2022.
> Mathematician are devicing the Birch++-Test:
> 
> Professor Yang-Hui He discusses the murmuration
> conjecture, shows how DeepMind, OpenAI, and EpochAI
> are rewriting the rules of pure math, and reveals
> what happens when machines start making research-
> level discoveries faster than any human could. AI
> is taking us beyond proof straight into the future
> of discovery. Get ready to witness a turning point
> in mathematical history: in this episode, we dive
> into the AI breakthroughs that stunned number
> theorists worldwide.
> 
> The AI Math That Left Number Theorists Speechless
> https://www.youtube.com/watch?v=spIquD_mBFk
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Current AI is split between two worlds that don't play well together:
>>
>> Deep Learning (neural networks, transformers, ChatGPT) - great at 
>> learning from data, terrible at logical reasoning
>> Symbolic AI (logic programming, expert systems) - great at logical 
>> reasoning, terrible at learning from messy real-world data
>>
>> Tensor Logic unifies both. It's a single language where you can:
>> Write logical rules that the system can actually learn and modify
>> Do transparent, verifiable reasoning (no hallucinations)
>> Mix "fuzzy" analogical thinking with rock-solid deduction
>>
>> The Killer Feature: The Temperature Knob
>>
>> https://www.youtube.com/watch?v=4APMGvicmxY
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> The English had Aristoteles (*), the French had
>>> Descartes, and the Dutch have their national
>>> Flag. The culmination of the Enlighment was
>>>
>>> the distinction between analytic and synthetic
>>> truth. But this doesn't help to understand
>>> Generative AI, which produces a mish mash
>>>
>>> of the factual and the plausible. But the logical
>>> and non-logical distinction lead to abominations
>>> like ascribing to Wittgenstein the maxim,
>>>
>>> "All logical differences are big differences", with
>>> the even worse conjecture "All nonlogical differences
>>> are small differences". But an early conceptual
>>>
>>> prototype of ChatGPT was given by:
>>>
>>> "Mirror (**) Mirror on the Wall who is the Fairest of them All?"
>>> - Snow White, Brothers Grim
>>>
>>> So its all about retrieving mirror texts and images and
>>> transforming them, the retrieval having good old metrics like
>>> recall and precision, and the transformation having also metrics,
>>>
>>> metrics all relative to a group preferences assumption of
>>> the end-user, so that the end-user can more cost effictively
>>> and more market penetratingly act, in a totally
>>>
>>> new AI Boom infected environment.
>>>
>>> Bye
>>>
>>> (*)
>>> we have powers and faculties fitted to deal with
>>> them, and are **happy or miserable** in proportion
>>> as we know how to **frame** a right judgment of things
>>> The elements of logic. In four books
>>> by Duncan, William, 1717-1760
>>> https://archive.org/details/elementsoflogic00dunc/page/n5/mode/2up
>>>
>>> (**)
>>>
>>> An earlier version of "Mirrors" (Chapter 7) was written for a
>>> volume in honor of Thomas A. Sebeok (He was among the
>>> founders of biosemiotics, and coined the term "zoosemiotics"
>>> in 1963 to describe the development of signals and signs by
>>> non-human animal species) for his sixty-fifth birthday.
>>> Umberto Eco, ''Semiotics and the Philosophy of Language'',
>>> Bloomington: Indiana U.P., 1984
>>> https://monoskop.org/images
>>> /b/b3/Eco_Umberto_Semiotics_and_the_Philosophy_of_Language_1986.pdf
>>
> 

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Thread

From Framing to Mirroring [AI Boom] Mild Shock <janburse@fastmail.fm> - 2025-10-31 11:16 +0100
  Tensor Logic "Unifies" AI Paradigms [Pedro Domingos] (Re: From Framing to Mirroring [AI Boom]) Mild Shock <janburse@fastmail.fm> - 2025-12-08 15:54 +0100
    Re: Tensor Logic "Unifies" AI Paradigms [Pedro Domingos] (Re: From Framing to Mirroring [AI Boom]) Ross Finlayson <ross.a.finlayson@gmail.com> - 2025-12-08 12:51 -0800
    From Turing-Test to Birch++-Test [Professor Yang-Hui He] (Re: Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]) Mild Shock <janburse@fastmail.fm> - 2025-12-10 14:55 +0100
      Where did the Neuron in Turing Machine come from? (Re: From Turing-Test to Birch++-Test [Professor Yang-Hui He]) Mild Shock <janburse@fastmail.fm> - 2025-12-10 15:02 +0100
      Re: From Turing-Test to Birch++-Test [Professor Yang-Hui He] (Re: Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]) Maciej Woźniak <mlwozniak@wp.pl> - 2025-12-10 15:06 +0100
        Famous Maciej Woźniak one liners (Was: From Turing-Test to Birch++-Test [Professor Yang-Hui He]) Mild Shock <janburse@fastmail.fm> - 2025-12-10 15:16 +0100
          Re: Famous Maciej Woźniak one liners (Was: From Turing-Test to Birch++-Test [Professor Yang-Hui He]) Maciej Woźniak <mlwozniak@wp.pl> - 2025-12-10 15:45 +0100

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