Hannah meets DeepMind co-founder and chief scientist Shane Legg, the man who coined the phrase ‘artificial general intelligence’, and explores how it might be built. Why does Shane think AGI is possible? When will it be realised? And what could it look like? Hannah also explores a simple theory of using trial and error to reach AGI and takes a deep dive into MuZero, an AI system which mastered complex board games from chess to Go, and is now generalising to solve a range of important tasks in the real world.
For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.
Interviewees: DeepMind’s Shane Legg, Doina Precup, Dave Silver & Jackson Broshear
Credits
Presenter: Hannah Fry
Series Producer: Dan Hardoon
Production support: Jill Achineku
Sounds design: Emma Barnaby
Music composition: Eleni Shaw
Sound Engineer: Nigel Appleton
Editor: David Prest
Commissioned by DeepMind
Thank you to everyone who made this season possible!
Further reading:
Real-world challenges for AGI, DeepMind: https://deepmind.com/blog/article/real-world-challenges-for-agi
An executive primer on artificial general intelligence, McKinsey: https://www.mckinsey.com/business-functions/operations/our-insights/an-executive-primer-on-artificial-general-intelligence
Mastering Go, chess, shogi and Atari without rules, DeepMind: https://deepmind.com/blog/article/muzero-mastering-go-chess-shogi-and-atari-without-rules
What is AGI?, Medium: https://medium.com/intuitionmachine/what-is-agi-99cdb671c88e
A Definition of Machine Intelligence by Shane Legg, arXiv: https://arxiv.org/abs/0712.3329
Reward is enough by David Silver, ScienceDirect: https://www.sciencedirect.com/science/article/pii/S0004370221000862
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