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/  

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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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

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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 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 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 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 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 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 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 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 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 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!

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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 pcm.adswizz.com for information about our collection and use of personal data for advertising.

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 2.0
• Project Astra
• Decoding Google Gemini with Jeff Dean
• Gaming, 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!

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

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 Dean
• Gaming, 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!

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There is broad consensus across the tech industry, governments and society, that as artificial intelligence becomes more embedded in every aspect of our world, regulation will be essential. But what does this look like? Can it be adopted without stifling innovation? Are current frameworks presented by government leaders headed in the right direction?

Join host Hannah Fry as she discusses these questions and more with Nicklas Lundblad, Director of Public Policy at Google DeepMind. Nicklas emphasises the importance of a nuanced approach to regulation, focusing on adaptability and evidence-based policymaking. He highlights the complexities of assessing risk and reward in emerging technologies, advocating for a focus on harm reduction.

Further reading/watching:

• AI Principles: https://ai.google/responsibility/principles/
• Frontier Model Forum: https://blog.google/outreach-initiatives/public-policy/google-microsoft-openai-anthropic-frontier-model-forum/
• Ethics of AI assistants with Iason Gabriel https://youtu.be/aaZc-as-soA?si=0ThbYY30FlO31kKQ

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!

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

NotebookLM is a research assistant powered by Gemini that draws on expertise from storytelling to present information in an engaging way. It allows users to upload their own documents and generate insights, explanations, and—more recently—podcasts. This feature, also known as audio overviews, has captured the imagination of millions of people worldwide, who have created thousands of engaging podcasts ranging from personal narratives to educational explainers using source materials like CVs, personal journals, sales decks, and more.

Join Raiza Martin and Steven Johnson from Google Labs, Google’s testing ground for products, as they guide host Hannah Fry through the technical advancements that have made NotebookLM possible. In this episode they'll explore what it means to be interesting, the challenges of generating natural-sounding speech, as well as exciting new modalities on the horizon.

Further reading

• Try NotebookLM here
• Read about the speech generation technology behind Audio Overveiws: https://deepmind.google/discover/blog/pushing-the-frontiers-of-audio-generation/

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: Daniel Lazard

Audio Engineer: Perry Rogantin

Video Studio Production: Nicholas Duke

Video Editor: Alex Baro Cayetano, Daniel Lazard

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!

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

Join Professor Hannah Fry at the AI for Science Forum for a fascinating conversation with Google DeepMind CEO Demis Hassabis. They explore how AI is revolutionizing scientific discovery, delving into topics like the nuclear pore complex, plastic-eating enzymes, quantum computing, and the surprising power of Turing machines. The episode also features a special 'ask me anything' session with Nobel Laureates Sir Paul Nurse, Jennifer Doudna, and John Jumper, who answer audience questions about the future of AI in science.

Watch the episode here, and catch up on all of the sessions from the AI for Science Forum here.

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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Imagine a future where we interact regularly with a range of advanced artificial intelligence (AI) assistants — and where millions of assistants interact with each other on our behalf. These experiences and interactions may soon become part of our everyday reality.

In this episode, host Hannah Fry and Google DeepMind Senior Staff Research Scientist Iason Gabriel discuss the ethical implications of advanced AI assistants. Drawing from Iason's recent paper, they examine value alignment, anthropomorphism, safety concerns, and the potential societal impact of these technologies.

Timecodes:

• 00:00 Intro
• 01:13 Definition of AI assistants
• 04:05 A utopic view
• 06:25 Iason’s background
• 07:45 The Ethics of Advanced AI Assistants paper
• 13:06 Anthropomorphism
• 14:07 Turing perspective
• 15:25 Anthropomorphism continued
• 20:02 The value alignment question
• 24:54 Deception
• 27:07 Deployed at scale
• 28:32 Agentic inequality
• 31:02 Unfair outcomes
• 34:10 Coordinated systems
• 37:10 A new paradigm
• 38:23 Tetradic value alignment
• 41:10 The future
• 42:41 Reflections from Hannah

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: Daniel Lazard
• Audio Engineer: Perry Rogantin
• Video Studio Production: Nicholas Duke
• Video Editor: Bilal Merhi
• Video Production Design: James Barton
• Visual Identity and Design: Eleanor Tomlinson
• Production support: Mo Dawoud
• 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 pcm.adswizz.com for information about our collection and use of personal data for advertising.

How human should an AI tutor be? What does ‘good’ teaching look like? Will AI lead in the classroom, or take a back seat to human instruction? Will everyone have their own personalized AI tutor? Join research lead, Irina Jurenka, and Professor Hannah Fry as they explore the complicated yet exciting world of AI in education.

Further reading:

• Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach

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: Daniel Lazard
• Audio Engineer: Perry Rogantin
• Video Studio Production: Nicholas Duke
• Video Editor: Bilal Merhi
• Video Production Design: James Barton
• Visual Identity and Design: Eleanor Tomlinson
• Production support: Mo Dawoud
• 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 pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Professor Hannah Fry sits down with Pushmeet Kohli, VP of Research at Google DeepMind to discuss AI’s impact on scientific discovery. They go on a whirlwind tour of scientific projects, touching on recent breakthroughs in AlphaFold, material science, weather forecasting, and mathematics to better understand how AI can enhance our scientific understanding of the world.

Further reading:

• Millions of new materials discovered with deep learning
• GraphCast: AI model for faster and more accurate global weather forecasting
• AlphaFold: A breakthrough unfolds (S2,E1)
• AlphaGeometry: An Olympiad-level AI system for geometry
• AI achieves silver-medal standard solving International Mathematical Olympiad problems

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: 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
• Production support: Mo Dawoud
• 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 pcm.adswizz.com for information about our collection and use of personal data for advertising.

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:

• SIMA
• RTX & RT2
• Interactive 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!

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

Professor Hannah Fry is joined by Jeff Dean, one of the most legendary figures in computer science and chief scientist of Google DeepMind and Google Research. Jeff was instrumental to the field in the late 1990s, writing the code that transformed Google from a small startup into the multinational company it is today. Hannah and Jeff discuss it all - from the early days of Google and neural networks, to the long term potential of multi-modal models like Gemini.

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!

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