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Groups > sci.physics > #894684
| 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.
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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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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