Hannah wraps up the series by meeting DeepMind co-founder and CEO, Demis Hassabis. In an extended interview, Demis describes why he believes AGI is possible, how we can get there, and the problems he hopes it will solve. Along the way, he highlights the important role of consciousness and why he’s so optimistic that AI can help solve many of the world’s major challenges. As a final note, Demis shares the story of a personal meeting with Stephen Hawking to discuss the future of AI and discloses Hawking’s parting message.

For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.

Interviewee: Deepmind co-founder and CEO, Demis Hassabis

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:

DeepMind, The Podcast: https://deepmind.com/blog/article/welcome-to-the-deepmind-podcast

DeepMind’s Demis Hassabis on its breakthrough scientific discoveries, WIRED: https://www.youtube.com/watch?v=2WRow9FqUbw

Riemann hypothesis, Wikipedia: https://en.wikipedia.org/wiki/Riemann_hypothesis

Using AI to accelerate scientific discovery by Demis Hassabis, Kendrew Lecture 2021: https://www.youtube.com/watch?v=sm-VkgVX-2o

Protein Folding & the Next Technological Revolution by Demis Hassabis, Bloomberg: https://www.youtube.com/watch?v=vhd4ENh5ON4

The Algorithm, MIT Technology Review: https://forms.technologyreview.com/newsletters/ai-the-algorithm/

Machine learning resources, The Royal Society: https://royalsociety.org/topics-policy/education-skills/teacher-resources-and-opportunities/resources-for-teachers/resources-machine-learning/

How to get empowered, not overpowered, by AI, TED: https://www.youtube.com/watch?v=2LRwvU6gEbA

AI needs to benefit everyone, not just those who build it. But fulfilling this promise requires careful thought before new technologies are built and released into the world. In this episode, Hannah delves into some of the most pressing and difficult ethical and social questions surrounding AI today. She explores complex issues like racial and gender bias and the misuse of AI technologies, and hears why diversity and representation is vital for building technology that works for all.

For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. 

Interviewees: DeepMind’s Sasha Brown, William Isaac, Shakir Mohamed, Kevin Mckee & Obum Ekeke

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: 

What a machine learning tool that turns Obama white can (and can’t) tell us about AI bias, The Verge: https://www.theverge.com/21298762/face-depixelizer-ai-machine-learning-tool-pulse-stylegan-obama-bias

Tuskegee Syphilis Study, Wikipedia: https://en.wikipedia.org/wiki/Tuskegee_Syphilis_Study

Ethics & Society, DeepMind: https://deepmind.com/about/ethics-and-society

Row over AI that 'identifies gay faces', BBC: https://www.bbc.co.uk/news/technology-41188560

The Trevor Project: https://www.thetrevorproject.org/

AI takes root, helping farmers identify diseased plants, Google: https://www.blog.google/technology/ai/ai-takes-root-helping-farmers-identity-diseased-plants/

How Can You Use Technology to Support a Culture of Inclusion and Diversity?, myHRfuture: https://www.myhrfuture.com/blog/2019/7/16/how-can-you-use-technology-to-support-a-culture-of-inclusion-and-diversity

Scholarships at DeepMind: https://www.deepmind.com/scholarships

AI, Ain’t I a Woman? Joy Buolamwini, YouTube:  https://www.youtube.com/watch?v=QxuyfWoVV98

How to be Human in the Age of the Machine, Hannah Fry: https://royalsociety.org/grants-schemes-awards/book-prizes/science-book-prize/2018/hello-world/

AI doesn’t just exist in the lab, it’s already solving a range of problems in the real world. In this episode, Hannah encounters a realistic recreation of her voice by WaveNet, the voice synthesising system that powers the Google Assistant and helps people with speech difficulties and illnesses regain their voices. Hannah also discovers how ‘deepfake’ technology can be used to improve weather forecasting and how DeepMind researchers are collaborating with Liverpool Football Club, aiming to take sports to the next level.

For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. 

Interviewees: DeepMind’s Demis Hassabis, Raia Hadsell, Karl Tuyls, Zach Gleicher & Jackson Broshear; Niall Robinson of the UK Met Office

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: 

A generative model for raw audio, DeepMind: https://deepmind.com/blog/article/wavenet-generative-model-raw-audio

WaveNet case study, DeepMind: https://deepmind.com/research/case-studies/wavenet

Using WaveNet technology to reunite speech-impaired users with their original voices, DeepMind:| https://deepmind.com/blog/article/Using-WaveNet-technology-to-reunite-speech-impaired-users-with-their-original-voices

Project Euphonia, Google Research: https://sites.research.google/euphonia/about/

Nowcasting the next hour of rain, DeepMind: https://deepmind.com/blog/article/nowcasting

Now DeepMind is using AI to transform football, WIRED: https://www.wired.co.uk/article/deepmind-football-liverpool-ai

Advancing sports analytics through AI, DeepMind: https://deepmind.com/blog/article/advancing-sports-analytics-through-ai

MetOffice, BBC: https://www.metoffice.gov.uk/

The village ‘washed on to the map’, BBC: https://www.bbc.co.uk/news/uk-england-cornwall-28523053

Michael Fish got the storm of 1987 wrong, Sky News: 

https://news.sky.com/story/michael-fish-got-the-storm-of-1987-wrong-but-modern-supercomputers-may-have-missed-it-too-11076659#:~:text=In%20a%20lunchtime%20broadcast%20on,%2C%22%20he%20confidently%20told%20viewers

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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

Do you need a body to have intelligence? And can one exist without the other? Hannah takes listeners behind the scenes of DeepMind's robotics lab in London where she meets robots that are trying to independently learn new skills, and explores why physical intelligence is a necessary part of intelligence. Along the way, she finds out how researchers trained their robots at home during lockdown, uncovers why so many robotics demonstrations are faking it, and what it takes to train a robotic football team. 

For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. 

Interviewees: DeepMind’s Raia Hadsell, Viorica Patraucean, Jan Humplik, Akhil Raju & Doina Precup

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: 

Stacking our way to more general robots, DeepMind: https://deepmind.com/blog/article/stacking-our-way-to-more-general-robots

Researchers Propose Physical AI As Key To Lifelike Robots, Forbes: ​​https://www.forbes.com/sites/simonchandler/2020/11/11/researchers-propose-physical-ai-as-key-to-lifelike-robots/

The robots going where no human can, BBC: https://www.bbc.co.uk/news/av/technology-41584738

The Robot Assault On Fukushima, WIRED: https://www.wired.com/story/fukushima-robot-cleanup/

Leaps, Bounds, and Backflips, Boston Dynamics: http://blog.bostondynamics.com/atlas-leaps-bounds-and-backflips

Now DeepMind is using AI to transform football, WIRED: 

https://www.wired.co.uk/article/deepmind-football-liverpool-ai

Cooperation is at the heart of our society. Inventing the railway, giving birth to the Renaissance, and creating the Covid-19 vaccine all required people to combine efforts. But cooperation is so much more. It governs our education systems, healthcare, and food production. In this episode, Hannah meets the researchers working on cooperative AI, and hears about their work and influences from the famous American psychologist - and pigeon trainer -  BF Skinner to the strategic board game Diplomacy.

For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com

Interviewees: DeepMind’s Thore Graepel, Kevin Mckee, Doina Precup & Laura Weidinger

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: 

Machines must learn to find common ground, Nature: https://www.nature.com/articles/d41586-021-01170-0

Introduction to Reinforcement Learning, DeepMind: https://www.youtube.com/watch?v=2pWv7GOvuf0

B.F. Skinner, Wikipedia: https://en.wikipedia.org/wiki/B._F._Skinner

The Tragedy of the Commons, Wikipedia: https://en.wikipedia.org/wiki/Tragedy_of_the_commons

Staving Off The Ultimate Tragedy Of The Commons, Forbes: https://www.forbes.com/sites/georgebradt/2021/11/02/staving-off-the-ultimate-tragedy-of-the-commons-by-making-better-complex-decisions-cooperatively-in-glasgow/

Understanding Agent Cooperation, DeepMind: https://deepmind.com/blog/article/understanding-agent-cooperation

The emergence of complex cooperative agents, DeepMind: https://deepmind.com/blog/article/capture-the-flag-science

Hannah explores the potential of language models, the questions they raise, and if teaching a computer about language is enough to create artificial general intelligence (AGI). Beyond helping us communicate ideas, language plays a crucial role in memory, cooperation, and thinking – which is why AI researchers have long aimed to communicate with computers using natural language. Recently, there has been extraordinary progress using large-language models (LLM), which learn how to speak by processing huge amounts of data from the internet. The results can be very convincing, but pose significant ethical challenges. 

For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. 

Interviewees: DeepMind’s Geoffrey Irving, Chris Dyer, Angeliki Lazaridou, Lisa-Anne Hendriks & Laura Weidinger 

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: 

GPT-3 Powers the Next Generation of Apps, OpenAI: https://openai.com/blog/gpt-3-apps/

https://web.stanford.edu/class/linguist238/p36-weizenabaum.pdf

Never Mind the Computer 1983 about the ELIZA program, BBC: https://www.bbc.co.uk/programmes/p023kpf8

How Large Language Models Will Transform Science, Society, and AI, Stanford University: https://hai.stanford.edu/news/how-large-language-models-will-transform-science-society-and-ai

Challenges in Detoxifying Language Models, DeepMind: https://deepmind.com/research/publications/2021/Challenges-in-Detoxifying-Language-Models

Extending Machine Language Models toward Human-Level Language Understanding, DeepMind: https://deepmind.com/research/publications/2020/Extending-Machine-Language-Models-toward-Human-Level-Language-Understanding

Language modelling at scale, DeepMind: https://deepmind.com/blog/article/language-modelling-at-scale

Artificial general intelligence, Technology Review: https://www.technologyreview.com/2020/10/15/1010461/artificial-general-intelligence-robots-ai-agi-deepmind-google-openai/

A Definition of Machine Intelligence by Shane Legg, arXiv: https://arxiv.org/abs/0712.3329

Stuart Russell - Living With Artificial Intelligence, BBC: https://www.bbc.co.uk/programmes/m001216k/episodes/player