Marcus Hutter is a senior research scientist at DeepMind and professor at Australian National University. Throughout his career of research, including with Jürgen Schmidhuber and Shane Legg, he has proposed a lot of interesting ideas in and around the field of artificial general intelligence, including the development of the AIXI model which is a mathematical approach to AGI that incorporates ideas of Kolmogorov complexity, Solomonoff induction, and reinforcement learning.

EPISODE LINKS:

Hutter Prize: http://prize.hutter1.net (http://prize.hutter1.net)

Marcus web: http://www.hutter1.net (http://www.hutter1.net)

Books mentioned:

– Universal AI: https://amzn.to/2waIAuw (https://amzn.to/2waIAuw)

– AI: A Modern Approach: https://amzn.to/3camxnY (https://amzn.to/3camxnY)

– Reinforcement Learning: https://amzn.to/2PoANj9 (https://amzn.to/2PoANj9)

– Theory of Knowledge: https://amzn.to/3a6Vp7x (https://amzn.to/3a6Vp7x)

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Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

OUTLINE:

00:00 – Introduction

03:32 – Universe as a computer

05:48 – Occam’s razor

09:26 – Solomonoff induction

15:05 – Kolmogorov complexity

20:06 – Cellular automata

26:03 – What is intelligence?

35:26 – AIXI – Universal Artificial Intelligence

1:05:24 – Where do rewards come from?

1:12:14 – Reward function for human existence

1:13:32 – Bounded rationality

1:16:07 – Approximation in AIXI

1:18:01 – Godel machines

1:21:51 – Consciousness

1:27:15 – AGI community

1:32:36 – Book recommendations

1:36:07 – Two moments to relive (past and future)