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Stephen Wolfram Papers
computationsinadequatesymbolic
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11 September
10 September
3 September
10 August
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Their words
Coding isn't yet another application domain -- it's the meta-skill required for AI to automatically develop its own training material, via symbolic world models. That's how the RSI loop actually kicks off.
7 August
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korrents.com
Future AI, say in fifteen years, will not be built on the LLM stack; it will have to move to symbolic learning.Their words
However, looking ahead, I still do not believe that future AI (say, in 15 years) will be based on the LLM stack. I believe it will necessarily have to move closer to its optimal, final form -- symbolic learning. Obviously this is a risky and contrarian belief -- the safe bet would be LRMs. But let's see.
2 August
26 July
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Their words
in an intellectually dead field, AI will just produce worthless junk. If what you feed it is decades of complicated and meaningless computations, it will just produce even more complicated and meaningless ones.
27 April
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Their words
The forty-page PDF used to feel intolerable. The well-designed web form will start to feel that way too, and faster than the last transition did.
28 December 2025
10 June 2025
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korrents.com
The success of large language models vindicates semantic inferentialism over symbolic, rule-based approaches to AI.Their words
The success of LLMs can thus be seen as vindicating semantic inferentialism against earlier, symbolic approaches to AI that tried and failed to explicate the rules of ordinary language using formal logic.
21 May 2025
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Their words
We live in the era of the symbolic executive, when "being good at stuff" matters far less than the appearance of doing stuff, where "what's useful" is dictated not by outputs or metrics that one can measure but rather the vibes passed between managers and executives that have worked their entire careers to escape the world of work.
29 June 2024
16 November 2017
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Lovedrcmnd.app
Inadequate EquilibriaTheir words
I do have two criticisms of the book, both relatively minor compared to what I loved about it.
10 June 2014
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Their words
Deep generative models have had less of an impact, due to the difficulty of approximating many intractable probabilistic computations that arise in maximum likelihood estimation and related strategies, and due to difficulty of leveraging the benefits of piecewise linear units in the generative context.
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