Google DeepMind: The Podcast

Learn how invisible, mathematical watermarks help trace AI provenance, protect against misuse, and safeguard protein sequence design without impacting biological function.

Timecodes:

00:00 Introduction

00:34 What is a watermark?

04:35 SynthID

15:16 Images and video

19:28 SynthID Bio

28:00 Future of resilience

Learn more about SynthID Bio: https://deepmind.google/blog/introducing-synthid-bio/

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Can artificial intelligence solve one of science’s most chaotic physics puzzles? In this episode, Professor Hannah Fry sits down with Peter Battaglia, Senior Director of Research at Google DeepMind, to explore how machine learning is transforming global weather forecasting. From providing critical early warnings for Category 5 storms like Hurricane Melissa to predicting renewable energy supply and agricultural impacts, see how models like GraphCast and WeatherNext 3 are building upon decades of numerical physics to reshape our understanding of the atmosphere.

Learn more about WeatherNext 3, our most advanced global weather AI model yet: https://deepmind.google/science/weathernext/

Timestamps:

00:00 Introduction

00:38 Hurricane Melissa

11:50 Why weather forecasting is hard

14:13 Traditional models vs AI models

21:55 Probabilistic forecasting

26:00 WeatherNext 3

33:00 Future outlook

43:44 Hannah's reflections

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!

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Now, if you ask an AI a question, it will usually give you an absolute answer with unwavering authority, even if that answer turns out to be wrong. In fact, today's AI seems to be missing a fundamental human trait: self-doubt. Long before the current wave of large language models, one academic researcher was trying to give machines a sense of their own limitations. Zoubin Ghahramani has spent the last 30 years pioneering a type of intelligence built on the mathematics of uncertainty. Today, as a professor at Cambridge and VP of Research at Google DeepMind, Zoubin finds himself at the heart of another interesting debate: will improving machine uncertainty be one of the missing pieces to ever improving AI?

Timecodes:

• 00:00 Introduction
• 01:06 The role of uncertainty
• 07:45 Correctness vs confidence
• 09:40 Historical perspectives
• 16:10 Bayesian thinking in AI
• 26:30 Uncertainty in the real world
• 36:42 Future research and AGI

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!

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Neel and his team are trying to do something phenomenally difficult: understand an intelligence that didn't come with a manual. Together, they explore the cutting-edge "neuroscience" of artificial intelligence—revealing the surprising, elegant structures being discovered inside these networks (like spare autoencoders), the inherent limits of looking under the hood, and why interpretability is absolutely essential if we are to build safe, aligned and trustworthy AI as we move towards AGI. Learn more about this area of research via https://deepmind.google/

Timecodes

• 00:00 Introduction
• 02:41 Motivation for interpretability research
• 04:01 Mechanistic interpretability
• 08:14 Chain of thought monitoring
• 18:14 Interpretability techniques
• 35:00 Auditing models for safety
• 48:53 What comes next for interpretability

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!

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Timecodes:

• 00:00 Intro
• 1:07 Defining AI agents
• 4:44 Agentic exploration in science and research
• 15:46 Delegation between agents
• 22:46 Agentic security and traps
• 29:31 Building an agentic economy
• 33:22 Cognitive monoculture
• 36:29 Distributed intelligence

To read the research, search for: Distributional AGI Safety, May 2026 Intelligent AI Delegation, February 2026 Virtual Agent Economies, September 2025

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!

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Seoul, March 2016. Two players sit hunched over a 19x19 grid covered in a sea of black and white stones. They are playing the ancient game of Go - a game of unimaginable complexity long thought impossible for a machine to master. On one side is Lee Sedol (Sae Dol), a legendary 18-time Go world champion. On the other, AlphaGo, a neural network based AI system built on a powerful technique called reinforcement learning. In the blink of an eye, the world changed. Exactly one decade later, we look back at the match that sparked the modern AI revolution. From algorithmic discovery to the solving of scientific grand challenges like protein folding, the foundation was laid right there on that wooden board.

Join Hannah Fry, Pushmeet Kohli (VP, Science) and Thore Graepel (AlphaGo team & Distinguished Research Scientist) as they unpick the legacy of AlphaGo.

🎥 AlphaGo https://youtu.be/WXuK6gekU1Y

🎥 The Thinking Game: https://youtu.be/d95J8yzvjbQ

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!

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Thanks for joining us this year.

🔔 Subscribe to stay updated on our return in 2026, and revisit our episode library to catch up on everything from driverless cars to drug discovery: https://www.youtube.com/playlist?list=PLqYmG7hTraZBiUr6_Qf8YTS2Oqy3OGZEj

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!

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Further reading

Levels of AGI paper: https://arxiv.org/abs/2311.02462

The road to AGI (Google DeepMind Podcast, S2): https://youtu.be/Uy4OYU7PQYA

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

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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Learn more about AlphaFold: https://deepmind.google/science/alphafold/

Watch the story behind AlphaFold in The Thinking Game, now available for free: https://youtu.be/d95J8yzvjbQ

Thank you 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
• Video editor: Anthony Le
• Audio engineer: Perry Rogantin
• Visual identity: 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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Learn more about Waymo: https://waymo.com/

Thank you 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
• Video editor: Anthony Le
• Audio engineer: Perry Rogantin
• Visual identity: 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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In part two, Hannah and Four tackle the human element at the heart of cybersecurity: Who are the bad actors, and what motivates them? They dissect the evolving strategies designed to stop social engineering attacks - like passkeys and risk-based authentication - and confront the complex security and privacy challenges that may be introduced by autonomous agents. 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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com
for information about our collection and use of personal data for
advertising.

Further reading:

• CodeMender: https://deepmind.google/discover/blog/introducing-codemender-an-ai-agent-for-code-security/
• Cybersecurity at Google: https://blog.google/technology/safety-security/ai-security-frontier-strategy-tools/
• Threat intelligence report: https://cloud.google.com/blog/topics/threat-intelligence/adversarial-misuse-generative-ai

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
• Video editor: Bilal Merhi
• Audio engineer: Perry Rogantin
• Visual identity: 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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Professor Hannah Fry speaks with Jack Parker-Holder and Shlomi Fruchter about Genie 3, a general-purpose world model that can generate an unprecedented diversity of interactive environments. The conversation covers how this model's auto-regressive nature allows for the creation of consistent, explorable worlds from text or image prompts, and how its capabilities differ from video generation models like Veo.

Further reading

• Genie 3
• SIMA, A generalist AI agent for 3D virtual environments
• SIMA, Google DeepMind: The Podcast
• xLand

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!

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This week's episode is a slight departure from our usual deep dives. Join Paige Bailey, DevRel lead, as she guides Hannah Fry though some of her favorite AI tools. Having spent years understanding the 'what' of these models, Hannah finally gets to experience the 'how’ – from generating prompts and 'vibe coding', to creating her own version of the infamous spaghetti meme.

Learn more and try the tools yourself:

• Gemini: https://gemini.google.com/
• Google Labs: https://labs.google/
• AI Studio: https://aistudio.google.com/
• Veo 3: https://deepmind.google/models/veo/
• Flow: https://labs.google/flow/

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
• Studio Manager: 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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Further reading:

• Natural forests of the world: paper, data and benchmarks
• Forest loss drivers: paper, summary from WRI, and blog from GFW
• Forest loss drivers code: Google Earth Engine; at WRI; at GFW; or Zenodo.
• Deep learning based remote sensing (open source): Jeo, GeeFlow
• Species mapping paper: Arxiv
• Google resources: Google Earth Engine. Agri with Google, wildlife cameras
• Perch: code, paper
• Perch x coral reefs: Blog
• Agile Modelling: paper, code
• DolphinGemma: blog

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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, host Hannah Fry is joined by Max Jaderberg and Rebecca Paul of Isomorphic Labs to explore the future of drug discovery in the age of AI. They discuss how new technology, particularly AlphaFold 3, is revolutionizing the field by predicting the structure of life’s molecules, paving the way for faster and more efficient drug discovery.

They dig into the immense complexities of designing new drugs: How do you find the right molecular key for the right biological lock? How can AI help scientists understand disease better and overcome challenges like drug toxicity? And what about the diseases that are currently considered “undruggable”? Finally, they explore the ultimate impact of this technology, from the future of personalised medicine to the ambitious goal of being able to eventually design treatments for all diseases.

Further reading:

• AlphaFold 3: https://www.nature.com/articles/s41586-024-07487-w
• AlphaFold Server: https://alphafoldserver.com/
• Isomorphic Labs: https://www.isomorphiclabs.com/
• AlphaFold 3 code and weights: https://github.com/google-deepmind/alphafold3

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
• Studio Manager: 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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Hannah is joined by Carolina Parada, Senior Director and Head of Robotics at Google DeepMind. They explore the recent leap forward in robotic capabilities, highlighting advancements in multimodal understanding and embodied reasoning, which enable robots to interact with the physical world with unprecedented generality.

They dig into the two-system approach - ‘slow and fast thinking‘ - that enables both complex reasoning and rapid, reactive movements. Using examples from robots learning dexterous tasks such as tying shoelaces to adapting to entirely new scenarios in real-time, Parada highlights how key breakthroughs in understanding, dexterity, and control are now coming together to rapidly advance robotics unlike ever before.

Further reading/viewing:

• Gemini Robotics
• Advances in robot dexterity
• Gemini Robotics x YouTube

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!

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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Professor Hannah Fry interviews Joelle Barral, Senior Director of Research at Google DeepMind, about AI in healthcare. They discuss existing AI applications including image analysis for diabetic retinopathy and the expansion of diagnostic tools as a result of multi-modal models. The conversation highlights AI's potential to improve healthcare delivery, personalize treatment, expand access worldwide, and ultimately, bring back the joy of practicing medicine.

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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

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!

Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.