Groups | Search | Server Info | Keyboard shortcuts | Login | Register [http] [https] [nntp] [nntps]
Groups > sci.physics > #894493 > unrolled thread
| Started by | Mild Shock <janburse@fastmail.fm> |
|---|---|
| First post | 2025-10-31 11:16 +0100 |
| Last post | 2025-12-10 15:45 +0100 |
| Articles | 8 — 3 participants |
Back to article view | Back to sci.physics
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
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Date | 2025-10-31 11:16 +0100 |
| Subject | From Framing to Mirroring [AI Boom] |
| Message-ID | <10e229s$rr1b$4@solani.org> |
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
[toc] | [next] | [standalone]
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Date | 2025-12-08 15:54 +0100 |
| Subject | Tensor Logic "Unifies" AI Paradigms [Pedro Domingos] (Re: From Framing to Mirroring [AI Boom]) |
| Message-ID | <10h6or4$1b491$2@solani.org> |
| In reply to | #894493 |
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
[toc] | [prev] | [next] | [standalone]
| From | Ross Finlayson <ross.a.finlayson@gmail.com> |
|---|---|
| Date | 2025-12-08 12:51 -0800 |
| Subject | Re: Tensor Logic "Unifies" AI Paradigms [Pedro Domingos] (Re: From Framing to Mirroring [AI Boom]) |
| Message-ID | <z5-cnY1fO7fUp6r0nZ2dnZfqnPqdnZ2d@giganews.com> |
| In reply to | #894674 |
On 12/08/2025 06:54 AM, Mild Shock wrote: > 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 > Wittgenstein's an inconstant flake. He'll say anything. Tensors are a cop-out, it's like "what are tensors, really", and getting "what do you want them to be". Then, making all manner or projections and perspective and the affine and the linear and showing they implement tensors tends to get "I don't know those". "How about matroids, how about the convolutive, how about all these implementations of tensorial products and about their inner and outer forms", and getting "can you write it in squares and triangles". Then the linear quite simply and the various examples that bridge the analytical bridges the linear and non-linear, and real-valued and not-the-complete-ordered-field-real-valued, about the "un-linear", has Lagrange laughing up his sleeve, saying "my anti-reductionism is an effective reductionism". And it's like, yeah, Lagrange, here's a monomode process, now it's "tensors" and it's a Lagrangian. Then he's like "I can't not do that". Tensorial products just resulting the vectorial somehow, _that being their definition_, isn't that un-usual a thing.
[toc] | [prev] | [next] | [standalone]
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Date | 2025-12-10 14:55 +0100 |
| Subject | From Turing-Test to Birch++-Test [Professor Yang-Hui He] (Re: Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]) |
| Message-ID | <10hbu4e$1ckhe$2@solani.org> |
| In reply to | #894674 |
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 >
[toc] | [prev] | [next] | [standalone]
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Date | 2025-12-10 15:02 +0100 |
| Subject | Where did the Neuron in Turing Machine come from? (Re: From Turing-Test to Birch++-Test [Professor Yang-Hui He]) |
| Message-ID | <10hbugr$1ckmg$2@solani.org> |
| In reply to | #894683 |
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 >> >
[toc] | [prev] | [next] | [standalone]
| From | Maciej Woźniak <mlwozniak@wp.pl> |
|---|---|
| Date | 2025-12-10 15:06 +0100 |
| Subject | Re: From Turing-Test to Birch++-Test [Professor Yang-Hui He] (Re: Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]) |
| Message-ID | <187fdfb8d38b4b3f$9943643$2542420$c2265aab@news.newsdemon.com> |
| In reply to | #894683 |
On 12/10/2025 2:55 PM, Mild Shock wrote: > 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 30 years ago I didn't expect to see computers passing the test - well, it is passed. But leaving theorists speechless or rewriting the rules of pure math - is a bold exaggeration. Thinking is not a mathematical process, it never was and ai hasn't changed that.
[toc] | [prev] | [next] | [standalone]
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Date | 2025-12-10 15:16 +0100 |
| Subject | Famous Maciej Woźniak one liners (Was: From Turing-Test to Birch++-Test [Professor Yang-Hui He]) |
| Message-ID | <10hbvci$1clbs$1@solani.org> |
| In reply to | #894685 |
Hi, > Thinking is not a mathematical process, > it never was and ai hasn't changed that. Thats not very deep. Could you elobarate? Bye Maciej Woźniak schrieb: > On 12/10/2025 2:55 PM, Mild Shock wrote: >> 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 > > 30 years ago I didn't expect to see > computers passing the test - well, > it is passed. But leaving theorists > speechless or rewriting the rules > of pure math - is a bold exaggeration. > > Thinking is not a mathematical process, > it never was and ai hasn't changed that. >
[toc] | [prev] | [next] | [standalone]
| From | Maciej Woźniak <mlwozniak@wp.pl> |
|---|---|
| Date | 2025-12-10 15:45 +0100 |
| Subject | Re: Famous Maciej Woźniak one liners (Was: From Turing-Test to Birch++-Test [Professor Yang-Hui He]) |
| Message-ID | <187fe1dcb52ab383$9946102$2542420$c2265aab@news.newsdemon.com> |
| In reply to | #894686 |
On 12/10/2025 3:16 PM, Mild Shock wrote: > Hi, > > > Thinking is not a mathematical process, > > it never was and ai hasn't changed that. > > Thats not very deep. Could you elobarate? Generally thinking (in its usual, human specific meaning) is processing text, mathematics is a special case of thinking, only working with the simplest terms and simplified rules. Thanks to simplifying a single brain can both comprehend it and handle it successfully. With thinking it's not that easy, it's designed for parallel processing by many.
[toc] | [prev] | [standalone]
Back to top | Article view | sci.physics
csiph-web