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#106 - Prof. KARL FRISTON 3.0 - Collective Intelligence [Special Edition]

#106 - Prof. KARL FRISTON 3.0 - Collective Intelligence [Special Edition]

FromMachine Learning Street Talk (MLST)


#106 - Prof. KARL FRISTON 3.0 - Collective Intelligence [Special Edition]

FromMachine Learning Street Talk (MLST)

ratings:
Length:
179 minutes
Released:
Mar 11, 2023
Format:
Podcast episode

Description

This show is sponsored by Numerai, please visit them here with our sponsor link (we would really appreciate it) http://numer.ai/mlst 
Prof. Karl Friston recently proposed a vision of artificial intelligence that goes beyond machines and algorithms, and embraces humans and nature as part of a cyber-physical ecosystem of intelligence. This vision is based on the principle of active inference, which states that intelligent systems can learn from their observations and act on their environment to reduce uncertainty and achieve their goals. This leads to a formal account of collective intelligence that rests on shared narratives and goals. 
To realize this vision, Friston suggests developing a shared hyper-spatial modelling language and transaction protocol, as well as novel methods for measuring and optimizing collective intelligence. This could harness the power of artificial intelligence for the common good, without compromising human dignity or autonomy. It also challenges us to rethink our relationship with technology, nature, and each other, and invites us to join a global community of sense-makers who are curious about the world and eager to improve it.

YT version: https://www.youtube.com/watch?v=V_VXOdf1NMw
Support us! https://www.patreon.com/mlst 
MLST Discord: https://discord.gg/aNPkGUQtc5

TOC: 
Intro [00:00:00]
Numerai (Sponsor segment) [00:07:10]
Designing Ecosystems of Intelligence from First Principles (Friston et al) [00:09:48]
Information / Infosphere and human agency [00:18:30]
Intelligence [00:31:38]
Reductionism [00:39:36]
Universalism [00:44:46]
Emergence [00:54:23]
Markov blankets [01:02:11]
Whole part relationships / structure learning [01:22:33]
Enactivism [01:29:23]
Knowledge and Language [01:43:53]
ChatGPT [01:50:56]
Ethics (is-ought) [02:07:55]
Can people be evil? [02:35:06]
Ethics in Al, subjectiveness [02:39:05]
Final thoughts [02:57:00]

References:
Designing Ecosystems of Intelligence from First Principles (Friston et al)
https://arxiv.org/abs/2212.01354

GLOM - How to represent part-whole hierarchies in a neural network (Hinton)
https://arxiv.org/pdf/2102.12627.pdf

Seven Brief Lessons on Physics (Carlo Rovelli)
https://www.amazon.co.uk/Seven-Brief-Lessons-Physics-Rovelli/dp/0141981725

How Emotions Are Made: The Secret Life of the Brain (Lisa Feldman Barrett)
https://www.amazon.co.uk/How-Emotions-Are-Made-Secret/dp/B01N3D4OON

Am I Self-Conscious? (Or Does Self-Organization Entail Self-Consciousness?) (Karl Friston)
https://www.frontiersin.org/articles/10.3389/fpsyg.2018.00579/full

Integrated information theory (Giulio Tononi)
https://en.wikipedia.org/wiki/Integrated_information_theory
Released:
Mar 11, 2023
Format:
Podcast episode

Titles in the series (100)

This is the audio podcast for the ML Street Talk YouTube channel at https://www.youtube.com/c/MachineLearningStreetTalk Thanks for checking us out! We think that scientists and engineers are the heroes of our generation. Each week we have a hard-hitting discussion with the leading thinkers in the AI space. Street Talk is unabashedly technical and non-commercial, so you will hear no annoying pitches. Corporate- and MBA-speak is banned on street talk, "data product", "digital transformation" are banned, we promise :) Dr. Tim Scarfe, Dr. Yannic Kilcher and Dr. Keith Duggar.