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Christopher Summerfield, Department of Experimental Psychology, University of Oxford is a Professor of Cognitive Neuroscience at the University of Oxford and a Research Scientist at Deepmind UK. His work focusses on the neural and computational mechanisms by which humans make decisions.
Chris has just released an incredible new book on AI called "Natural General Intelligence". It's my favourite book on AI I have read so so far. 
The book explores the algorithms and architectures that are driving progress in AI research, and discusses intelligence in the language of psychology and biology, using examples and analogies to be comprehensible to a wide audience. It also tackles longstanding theoretical questions about the nature of thought and knowledge.
With Chris' permission, I read out a summarised version of Chapter 2 from his book on which was on Intelligence during the 30 minute MLST introduction.  
Buy his book here:
https://global.oup.com/academic/product/natural-general-intelligence-9780192843883?cc=gb&lang=en&

YT version: https://youtu.be/31VRbxAl3t0
Interviewer: Dr. Tim Scarfe

TOC:
[00:00:00] Walk and talk with Chris on Knowledge and Abstractions
[00:04:08] Intro to Chris and his book
[00:05:55] (Intro) Tim reads Chapter 2: Intelligence 
[00:09:28] Intro continued: Goodhart's law
[00:15:37] Intro continued: The "swiss cheese" situation  
[00:20:23] Intro continued: On Human Knowledge
[00:23:37] Intro continued: Neats and Scruffies
[00:30:22] Interview kick off 
[00:31:59] What does it mean to understand?
[00:36:18] Aligning our language models
[00:40:17] Creativity 
[00:41:40] "Meta" AI and basins of attraction 
[00:51:23] What can Neuroscience impart to AI
[00:54:43] Sutton, neats and scruffies and human alignment
[01:02:05] Reward is enough
[01:19:46] Jon Von Neumann and Intelligence
[01:23:56] Compositionality

References:

The Language Game (Morten H. Christiansen, Nick Chater
https://www.penguin.co.uk/books/441689/the-language-game-by-morten-h-christiansen-and--nick-chater/9781787633483
Theory of general factor (Spearman)
https://www.proquest.com/openview/7c2c7dd23910c89e1fc401e8bb37c3d0/1?pq-origsite=gscholar&cbl=1818401
Intelligence Reframed (Howard Gardner)
https://books.google.co.uk/books?hl=en&lr=&id=Qkw4DgAAQBAJ&oi=fnd&pg=PT6&dq=howard+gardner+multiple+intelligences&ots=ERUU0u5Usq&sig=XqiDgNUIkb3K9XBq0vNbFmXWKFs#v=onepage&q=howard%20gardner%20multiple%20intelligences&f=false
The master algorithm (Pedro Domingos)
https://www.amazon.co.uk/Master-Algorithm-Ultimate-Learning-Machine/dp/0241004543
A Thousand Brains: A New Theory of Intelligence (Jeff Hawkins)
https://www.amazon.co.uk/Thousand-Brains-New-Theory-Intelligence/dp/1541675819
The bitter lesson (Rich Sutton)
http://www.incompleteideas.net/IncIdeas/BitterLesson.html