154 min listen
STEPHEN WOLFRAM 2.0 - Resolving the Mystery of the Second Law of Thermodynamics
STEPHEN WOLFRAM 2.0 - Resolving the Mystery of the Second Law of Thermodynamics
ratings:
Length:
84 minutes
Released:
Aug 15, 2023
Format:
Podcast episode
Description
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The Second Law: Resolving the Mystery of the Second Law of Thermodynamics
Buy Stephen's book here - https://tinyurl.com/2jj2t9wa
The Language Game: How Improvisation Created Language and Changed the World by Morten H. Christiansen and Nick Chater
Buy here: https://tinyurl.com/35bvs8be
Stephen Wolfram starts by discussing the second law of thermodynamics - the idea that entropy, or disorder, tends to increase over time. He talks about how this law seems intuitively true, but has been difficult to prove. Wolfram outlines his decades-long quest to fully understand the second law, including failed early attempts to simulate particles mixing as a 12-year-old. He explains how irreversibility arises from the computational irreducibility of underlying physical processes coupled with our limited ability as observers to do the computations needed to "decrypt" the microscopic details.
The conversation then shifts to discussing language and how concepts allow us to communicate shared ideas between minds positioned in different parts of "rule space." Wolfram talks about the successes and limitations of using large language models to generate Wolfram Language code from natural language prompts. He sees it as a useful tool for getting started programming, but one still needs human refinement.
The final part of the conversation focuses on AI safety and governance. Wolfram notes uncontrolled actuation is where things can go wrong with AI systems. He discusses whether AI agents could have intrinsic experiences and goals, how we might build trust networks between AIs, and that managing a system of many AIs may be easier than a single AI. Wolfram emphasizes the need for more philosophical depth in thinking about AI aims, and draws connections between potential solutions and his work on computational irreducibility and physics.
Show notes: https://docs.google.com/document/d/1hXNHtvv8KDR7PxCfMh9xOiDFhU3SVDW8ijyxeTq9LHo/edit?usp=sharing
Pod version: TBA
https://twitter.com/stephen_wolfram
TOC:
00:00:00 - Introduction
00:02:34 - Second law book
00:14:01 - Reversibility / entropy / observers / equivalence
00:34:22 - Concepts/language in the ruliad
00:49:04 - Comparison to free energy principle
00:53:58 - ChatGPT / Wolfram / Language
01:00:17 - AI risk
Panel: Dr. Tim Scarfe @ecsquendor / Dr. Keith Duggar @DoctorDuggar
http://numer.ai/mlst
Patreon: https://www.patreon.com/mlst
Discord: https://discord.gg/ESrGqhf5CB
The Second Law: Resolving the Mystery of the Second Law of Thermodynamics
Buy Stephen's book here - https://tinyurl.com/2jj2t9wa
The Language Game: How Improvisation Created Language and Changed the World by Morten H. Christiansen and Nick Chater
Buy here: https://tinyurl.com/35bvs8be
Stephen Wolfram starts by discussing the second law of thermodynamics - the idea that entropy, or disorder, tends to increase over time. He talks about how this law seems intuitively true, but has been difficult to prove. Wolfram outlines his decades-long quest to fully understand the second law, including failed early attempts to simulate particles mixing as a 12-year-old. He explains how irreversibility arises from the computational irreducibility of underlying physical processes coupled with our limited ability as observers to do the computations needed to "decrypt" the microscopic details.
The conversation then shifts to discussing language and how concepts allow us to communicate shared ideas between minds positioned in different parts of "rule space." Wolfram talks about the successes and limitations of using large language models to generate Wolfram Language code from natural language prompts. He sees it as a useful tool for getting started programming, but one still needs human refinement.
The final part of the conversation focuses on AI safety and governance. Wolfram notes uncontrolled actuation is where things can go wrong with AI systems. He discusses whether AI agents could have intrinsic experiences and goals, how we might build trust networks between AIs, and that managing a system of many AIs may be easier than a single AI. Wolfram emphasizes the need for more philosophical depth in thinking about AI aims, and draws connections between potential solutions and his work on computational irreducibility and physics.
Show notes: https://docs.google.com/document/d/1hXNHtvv8KDR7PxCfMh9xOiDFhU3SVDW8ijyxeTq9LHo/edit?usp=sharing
Pod version: TBA
https://twitter.com/stephen_wolfram
TOC:
00:00:00 - Introduction
00:02:34 - Second law book
00:14:01 - Reversibility / entropy / observers / equivalence
00:34:22 - Concepts/language in the ruliad
00:49:04 - Comparison to free energy principle
00:53:58 - ChatGPT / Wolfram / Language
01:00:17 - AI risk
Panel: Dr. Tim Scarfe @ecsquendor / Dr. Keith Duggar @DoctorDuggar
Released:
Aug 15, 2023
Format:
Podcast episode
Titles in the series (100)
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