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Hannah Fry

Join mathematician and broadcaster Professor Hannah Fry as she goes behind the scenes of the world-leading research lab to uncover the extraordinary ways AI is transforming our world. No hype. No spin, just compelling discussions and grand scientific ambition.

DeepMind: The Podcast

In this episode, Hannah is joined by Oriol Vinyals, VP of Drastic Research and Gemini co-lead. They discuss the evolution of agents from single-task models to more general-purpose models capable of broader applications, like Gemini. Vinyals guides Hannah through the two-step process behind multi modal models: pre-training (imitation learning) and post-training (reinforcement learning). They discuss the complexities of scaling and the importance of innovation in architecture and training processes. They close on a quick whirlwind tour of some of the new agentic capabilities recently released by Google DeepMind. 

Note: To see all of the full length demos, including unedited versions, and other videos related to Gemini 2.0 head to YouTube.

Future reading/watching: 

Gemini 2.0 • 
Decoding Google Gemini with Jeff DeanGaming, Goats & General Intelligence with Frederic Besse
Thanks to everyone who made this possible, including but not limited to: 

Presenter: Professor Hannah Fry

Series Producer: Dan Hardoon

Editor: Rami Tzabar, TellTale Studios 

Commissioner & Producer: Emma Yousif

Music composition: Eleni Shaw

Camera Director and Video Editor: Bernardo Resende

Audio Engineer: Perry Rogantin

Video Studio Production: Nicholas Duke

Video Editor: Bilal Merhi

Video Production Design: James Barton

Visual Identity and Design: Eleanor Tomlinson

Commissioned by Google DeepMind

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Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

Gemini 2.0 and the evolution of agentic AI with Oriol Vinyals

In our final episode for the year, we explore Project Astra, a research prototype exploring future capabilities of a universal AI assistant that can understand the world around you. Host Hannah Fry is joined by Greg Wayne, Director in Research at Google DeepMind. They discuss the inspiration behind the research prototype, its current strengths and limitations, as well as potential future use cases. Hannah even gets the chance to put Project Astra's multilingual skills to the test.

Further reading / listening:

Gemini 2.0Project Astra Decoding Google Gemini with Jeff DeanGaming, Goats & General Intelligence with Frederic Besse
Thanks to everyone who made this possible, including but not limited to: 

 • Presenter: Professor Hannah Fry
 • Series Producer: Dan Hardoon
 • Editor: Rami Tzabar, TellTale Studios
 • Commissioner & Producer: Emma Yousif
 • Music composition: Eleni Shaw
 • Camera Director and Video Editor: Bernardo Resende
 • Audio Engineer: Perry Rogantin
 • Video Studio Production: Nicholas Duke
 • Video Editor: Bilal Merhi
 • Video Production Design: James Barton
 • Visual Identity and Design: Eleanor Tomlinson
 • Commissioned by Google DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

Project Astra: Exploring a Universal AI Assistant with Greg Wayne

In this episode of Google DeepMind: The Podcast, VP of Reinforcement Learning, David Silver, describes his vision for the future of AI, exploring the concept of the "era of experience" versus the current "era of human data". Using AlphaGo and AlphaZero as examples, he highlights how these systems surpassed human capabilities by engaging in reinforcement learning without prior human knowledge. This approach contrasts with large language models, which depend on human data and feedback. Silver emphasizes the need to explore this path to drive AI progress and achieve artificial superintelligence.

Timestamps 

 • 00:00 Introduction
 • 01:50 Era of experience
 • 03:45 AlphaZero
 • 10:19 Move 37
 • 15:20 Reinforcement learning and human feedback
 • 24:30 AlphaProof
 • 29:50 Math Olympiads
 • 35:00 Experience based methods
 • 42:56 Hannah's reflections
 • 44:00 Fan Hui joins

___

Thanks to everyone who made this possible, including but not limited to: 

 • Presenter: Professor Hannah Fry
 • Series Producer: Dan Hardoon
 • Series Editor: Rami Tzabar
 • Commissioner & Producer: Emma Yousif
 • Music Composition: Eleni Shaw
 • Audio Engineer: Richard Courtice
 • Production Manager: Dan Lazard
 • Video Director and Editor: Bernardo Resende
 • Video Studio Production: Nicholas Duke
 • Video Editor: Bilal Merhi
 • Audio Engineer: Perry Rogantin
 • Camera and Lighting Operator: Robert Messere
 • Production Coordination: Zoey Roberts, Sarah Ellen Morton
 • Visual Identity and Design: Rob Ashley
 • Commissioned by Google DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

Is Human Data Enough? With David Silver

In this episode, Hannah is once again joined by Murray Shanahan, Professor of Cognitive Robotics at Imperial College London and Principal Scientist at Google DeepMind, for a philosophical deep dive on AI. They explore everything from consciousness and metacognition in animals, to symbolic AI and neural networks. Murray also shares insights into his involvement with the film 'Ex Machina' and discusses the idea of reasoning, anthropomorphism, and the future of AI.

Further reading / listening: 

 • Toward the future, S1 Ep 7: 
https://youtu.be/yf31XT1G1RQ?si=6mAEsQhKwKPWk9oH
___

Thanks to everyone who made this possible, including but not limited to: 

 • Presenter: Professor Hannah Fry
 • Series Producer: Dan Hardoon
 • Editor: Rami Tzabar
 • Commissioner & Producer: Emma Yousif
 • Music composition: Eleni Shaw
 • Audio engineer: Richard Courtice
 • Production Manager: Dan Lazard
 • Video Director: Bernardo Resende
 • Video Editor: Alex Baro Cayetano, Bilal Merhi
 • Audio Engineer: Richard Courtice
 • Camera and Lighting Operator: Robert Messere
 • Production Coordination: Zoey Roberts, Sarah Ellen Morton
 • Visual Identity and Design: Rob Ashley
 • Commissioned by Google DeepMind

___

 • Subscribe to our channel to watch every episode: https://www.youtube.com/@googledeepmind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

Consciousness, Reasoning and the Philosophy of AI with Murray Shanahan

Further reading:

Med-Gemini AMIE
Thanks to everyone who made this possible, including but not limited to: 

 • Presenter: Professor Hannah Fry
 • Series Producer: Dan Hardoon
 • Editor: Rami Tzabar
 • Commissioner & Producer: Emma Yousif
 • Music: Eleni Shaw
 • Audio Engineer: Richard Courtice
 • Production Manager: Dan Lazard
 • Video Studio Production: Nicholas Duke Video
 • Director: Bernardo Resende
 • Video Editor: Bilal Merhi
 • Audio Engineer: Perry Rogantin
 • Camera and Lighting Operator: Robert Messere
 • Production Coordination: Zoey Roberts, Sarah Ellen Morton
 • Visual Identity and Design: Rob Ashley
 • Commissioned by Google DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

AI and the Future of Health with Joelle Barral

Selected as “New and Noteworthy” by Apple Podcasts, the highly-praised, award-nominated first season of "DeepMind: The Podcast" explores the fascinating world of artificial intelligence (AI). Join mathematician and broadcaster Hannah Fry as she meets world-class scientists and thinkers as they explain the foundations of AI, explore some of the challenges the field is wrestling with, and dives into the research that's led to breakthroughs like AlphaGo and AlphaFold. Whether you’re a beginner or an experienced researcher, join our journey into the past, present, and future of AI.

“I hope what people are going to get out of this series is a better understanding of artificial intelligence, and I hope they also get a great feeling for how exhilarating an endeavour and a journey we’re on.” - Demis Hassabis, CEO and co-founder of DeepMind

If you have a question or feedback on the series, message us on Twitter @DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com. Please leave us a review on Spotify or Apple Podcasts if you enjoyed
this episode. We always want to hear from our audience whether that's in
the form of feedback, new idea or a guest recommendation!

DeepMind: The Podcast - trailer

What can the human brain teach us about AI? And what can AI teach us about our own intelligence? These questions underpin a lot of AI research. In this first episode, Hannah meets the DeepMind Neuroscience team to explore these connections and discovers how our brains are like birds’ wings, what training a dog and an AI agent have in common, and why the simplest things for people to do are, paradoxically, often the hardest for machines.

If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.

Further reading

BBC: An AI playlistWait But Why: The AI RevolutionCoursera: AI for everyoneMedium: Machine Learning for HumansGoogle Arts & Culture: 25 moments that have defined AIRoyal Society: What is Machine Learning?The Algorithm: A weeklyemail newsletter from MIT Tech ReviewDeepMind blog: neuroscience and AI: a virtuous circleNature: Far-sighted birds plan breakfast the evening before
Interviewees in this episode: Deepmind CEO and co-founder, Demis Hassabis; Matt Botvinick, Director of Neuroscience Research; research scientists Jess Hamrick and Greg Wayne; and Director of Research, Koray Kavukcuoglu.

Credits:
Presenter: Hannah Fry
Editor: David Prest
Senior Producer: Louisa Field
Producers: Amy Racs, Dan Hardoon
Binaural Sound: Lucinda Mason-Brown
Music composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)
Commissioned by DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

AI and Neuroscience: The virtuous circle

In March 2016, more than 200 million people watched AlphaGo become first computer program to defeat a professional human player at the game of Go, a milestone in AI research that was considered to be a decade ahead of its time. Since then the team has continued to develop the system and recently unveiled AlphaZero: a program that has taught itself how to play chess, Go, and shogi. Hannah explores the inside story of both with Lead Researcher David Silver and finds out why games are a useful proving ground for AI researchers. She also meets Chess Grandmaster Matthew Sadler and women’s international master Natasha Regan, who have written a book on AlphaZero and its unique gameplay.

If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.

Further reading

AlphaGo the documentary • 
The Surrounding Game: Documentary about the ancient game of GoDeepMind website: AlphaGoGarry Kasparov: Deep ThinkingAI: More than Human - Exhibition at the Barbican Centre • , 2019 and 
online exhibitDeepMind blog: AlphaZero: Shedding new light on chess, shogi, and GoMatthew Sadler and Natasha Regan: Game Changer - a book about chess and AI • 
WIRED: What the AI behind AlphaGo can teach us about being human
Interviewees: DeepMind CEO Demis Hassabis, Matthew Sadler, chess Grandmaster; Lead Researcher David Silver, Matt Botvinick, Director of Neuroscience Research; and Natasha Regan, women’s international chess master.

Credits:
Presenter: Hannah Fry
Editor: David Prest
Senior Producer: Louisa Field
Producers: Amy Racs, Dan Hardoon
Binaural Sound: Lucinda Mason-Brown
Music composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)
Commissioned by DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

Go to Zero

Video games have become a favourite tool for AI researchers to test the abilities of their systems. In this episode, Hannah sits down to play StarCraft II - a challenging video game that requires players to control the onscreen action with as many as 800 clicks a minute. She is guided by Oriol Vinyals, an ex-professional StarCraft player and research scientist at DeepMind, who explains how the program AlphaStar learnt to play the game and beat a top professional player. Elsewhere, she explores systems that are learning to cooperate in a digital version of the playground favourite ‘Capture the Flag’.

If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or emailing us at podcast@deepmind.com.

Further reading

The Economist: Why AI researchers like video games • DeepMind blogs: 
Capture the Flag • and 
AlphastarProfessional StarCraft II player MaNa gives his impressions of AlphaStar and DeepMindOpen AI’s work on Dota 2 The New York Times: DeepMind can now beat us at multiplayer games, tooRoyal Society: Machine Learning resourcesDeepMind: The Inside Story of AlphaStar Andrej Karpathy: Deep Reinforcement Learning: Pong from Pixels
Interviewees: Research scientists Max Jaderberg and Raia Hadsell; Lead researchers David Silver and Oriol Vinyals, and Director of Research Koray Kavukcuoglu.

Credits:
Presenter: Hannah Fry
Editor: David Prest
Senior Producer: Louisa Field
Producers: Amy Racs, Dan Hardoon
Binaural Sound: Lucinda Mason-Brown
Music composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)
Commissioned by DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

Life is like a game

Forget what sci-fi has told you about superintelligent robots that are uncannily human-like; the reality is more prosaic. Inside DeepMind’s robotics laboratory, Hannah explores what researchers call ‘embodied AI’: robot arms that are learning tasks like picking up plastic bricks, which humans find comparatively easy. Discover the cutting-edge challenges of bringing AI and robotics together, and learning from scratch how to perform tasks. She also explores some of the key questions about using AI safely in the real world.

If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.

Further reading:

 • Blogs on 
AI safety • and 
further resources • from Victoria Krakovna
The Future of Life Institute: The risks and benefits of AIThe Wall Street Journal: Protecting Against AI’s Existential ThreatTED Talks: Max Tegmark - How to get empowered, not overpowered, by AIRoyal Society lecture series sponsored by DeepMind: You & AINick Bostrom: Superintelligence: Paths, Dangers and Strategies • (book)
OpenAI: Learning from Human PreferencesDeepMind blog: Learning from human preferencesDeepMind blog: Learning by playing - how robots can tidy up after themselvesDeepMind blog: AI safety
Interviewees: Software engineer Jackie Kay and research scientists Murray Shanahan, Victoria Krakovna, Raia Hadsell and Jan Leike.

Credits:
Presenter: Hannah Fry
Editor: David Prest
Senior Producer: Louisa Field
Producers: Amy Racs, Dan Hardoon
Binaural Sound: Lucinda Mason-Brown
Music composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)
Commissioned by DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

AI, Robot

Games are a very good training ground for agents. Think about it. Perfectly packaged, neatly constrained environments where agents can run wild, work out the rules for themselves, and learn how to handle autonomy. In this episode, Research Engineering Team Lead, Frederic Besse, joins Hannah as they discuss important research like SIMA (Scalable Instructable Multiworld Agent) and what we can expect from future agents that can understand and safely carry out a wide range of tasks - online and in the real world.

Further reading:

SIMARTX & RT2Interactive Agents
Thanks to everyone who made this possible, including but not limited to: 

 • Presenter: Professor Hannah Fry
 • Series Producer: Dan Hardoon
 • Editor: Rami Tzabar, TellTale Studios 
 • Commissioner & Producer: Emma Yousif
 • Production support: Mo Dawoud 
 • Music composition: Eleni Shaw
 • Camera Director and Video Editor: Tommy Bruce
 • Audio Engineer: Perry Rogantin
 • Video Studio Production: Nicholas Duke
 • Video Editor: Bilal Merhi
 • Video Production Design: James Barton
 • Visual Identity and Design: Eleanor Tomlinson 
 • Commissioned by Google DeepMind

Please leave us a review on Spotify or Apple Podcasts if you enjoyed this episode. We always want to hear from our audience whether that's in the form of feedback, new idea or a guest recommendation!

Gaming, Goats & General Intelligence with Frederic Besse

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