The Limits of Large Language Models

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You know what I mean is that you can make the need for a neural net less and less. And there will still be some stuff that's kind of fuzzy just like you know they're things that it's like this question of what can we formalize into computational language. What is just sort of oh it happens that way just because brains are set up that way. So, you know, there are limitations of large language models just to make it explicit.

Stephen Wolfram is a computer scientist, mathematician, theoretical physicist, and the founder of Wolfram Research, a company behind Wolfram|Alpha, Wolfram Language, and the Wolfram Physics and Metamathematics projects. Please support this podcast by checking out our sponsors:
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OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(06:45) – WolframAlpha and ChatGPT
(26:26) – Computation and nature of reality
(53:18) – How ChatGPT works
(1:53:01) – Human and animal cognition
(2:06:20) – Dangers of AI
(2:14:39) – Nature of truth
(2:36:01) – Future of education
(3:12:03) – Consciousness
(3:21:02) – Second Law of Thermodynamics
(3:44:36) – Entropy
(3:57:36) – Observers in physics
(4:14:27) – Mortality