What exactly is novel about doubting how statistical models (aka, deep learning/ML) can never really replicate the underlying system its modeling? It's well known in the math, physics, and philosophy communities that statistical models will never fully replicate an analytical model of the system no matter the various linear algebra structures and optimizations you add (in fact, statistical modeling and numerical computation were always considered "easy" fields relative to theory). Find, you converge to some local minimum that minimizes some error function or metric for a large input, you've still just produced a really good statistical model and not discovered the formal model.
Sorry, your statistical models are finding the extrema of some abstract problem space and just because you improve the finding of these local extrema doesn't mean you've reproduced the analytical form of the problem space your model is attempting to "learn".
> Waiting for cognitive models and reasoning to magically emerge from larger and larger [language] training corpora is like waiting for a miracle
I've been working on it for twenty years and now my symbolic language model is on this level - coherent conceptual model of the world - t.me/thematrixcom
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Unified Theory of Consciousness - World Model - Language Model
DNA, Knowledge, Intuition, NLU - RNA, Consciousness, Thinking, Multi-language NLP - Protein, Understanding, Sensing, Multi-modal AI - Signal Transduction to DNA, Memory via Epigenetic Modifications, Feeling, Human-in-the-Loop (RL)
Knowledge - Consciousness - Understanding - Memory via Epigenetic Modifications = Basic psychological functions according to Carl Jung = Intuition - Thinking - Sensing - Feeling = DNA - RNA - Protein - Signal Transduction to DNA
System 1 is signal transduction (NLU) and System 2 is a DNA-RNA-Protein way (NLP).
Language Model = Epistemological AGI = NLU - Multi-language NLP - Multi-modal AI - Human-in-the-Loop (RL)
World Model = Universal Laws = Nature is a fractal that repeats in structure - atom, cell, organism, planet, solar system, galaxy, universe. All cells in an organism just work in parallel.
Very well [described, supported, argued], Gary. Congratulations. To me, your thinking hits at a haunting return to Chomsky's universal grammar, and the stunning lack of publications on "instinct" in this community (I haven't checked [biology, genetics, neuroscience] for a couple of decades).
If it's not working, try something different. That's the hallmark of intelligence, eh?
Fantastic as usual. Thanks for posting!
What exactly is novel about doubting how statistical models (aka, deep learning/ML) can never really replicate the underlying system its modeling? It's well known in the math, physics, and philosophy communities that statistical models will never fully replicate an analytical model of the system no matter the various linear algebra structures and optimizations you add (in fact, statistical modeling and numerical computation were always considered "easy" fields relative to theory). Find, you converge to some local minimum that minimizes some error function or metric for a large input, you've still just produced a really good statistical model and not discovered the formal model.
Sorry, your statistical models are finding the extrema of some abstract problem space and just because you improve the finding of these local extrema doesn't mean you've reproduced the analytical form of the problem space your model is attempting to "learn".
> Waiting for cognitive models and reasoning to magically emerge from larger and larger [language] training corpora is like waiting for a miracle
I've been working on it for twenty years and now my symbolic language model is on this level - coherent conceptual model of the world - t.me/thematrixcom
-
Unified Theory of Consciousness - World Model - Language Model
DNA, Knowledge, Intuition, NLU - RNA, Consciousness, Thinking, Multi-language NLP - Protein, Understanding, Sensing, Multi-modal AI - Signal Transduction to DNA, Memory via Epigenetic Modifications, Feeling, Human-in-the-Loop (RL)
Foundational Model of Intelligence
RNA Processing = Transcription - Splicing - Translation (biology) = Analysis - Search - Synthesis (science) = Intelligence
Knowledge - Consciousness - Understanding - Memory via Epigenetic Modifications = Basic psychological functions according to Carl Jung = Intuition - Thinking - Sensing - Feeling = DNA - RNA - Protein - Signal Transduction to DNA
System 1 is signal transduction (NLU) and System 2 is a DNA-RNA-Protein way (NLP).
Language Model = Epistemological AGI = NLU - Multi-language NLP - Multi-modal AI - Human-in-the-Loop (RL)
World Model = Universal Laws = Nature is a fractal that repeats in structure - atom, cell, organism, planet, solar system, galaxy, universe. All cells in an organism just work in parallel.
Plagiarism is a form of flattery.
Existing versions of "AI" cannot serve as the basis for the AI that those who started using this term had in mind.
Very well [described, supported, argued], Gary. Congratulations. To me, your thinking hits at a haunting return to Chomsky's universal grammar, and the stunning lack of publications on "instinct" in this community (I haven't checked [biology, genetics, neuroscience] for a couple of decades).