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 CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned 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-agiAn executive primer on artificial general intelligence, McKinsey: https://www.mckinsey.com/business-functions/operations/our-insights/an-executive-primer-on-artificial-general-intelligenceMastering Go, chess, shogi and Atari without rules, DeepMind: https://deepmind.com/blog/article/muzero-mastering-go-chess-shogi-and-atari-without-rulesWhat is AGI?, Medium: https://medium.com/intuitionmachine/what-is-agi-99cdb671c88eA Definition of Machine Intelligence by Shane Legg, arXiv: https://arxiv.org/abs/0712.3329Reward is enough by David Silver, ScienceDirect: https://www.sciencedirect.com/science/article/pii/S0004370221000862