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
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
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
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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