cover of episode 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

2023/8/15
logo of podcast Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)

Frequently requested episodes will be transcribed first

Shownotes Transcript

Please check out Numerai - our sponsor @ 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