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

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

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

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

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

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

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

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 FrySeries Producer: Dan HardoonEditor: Rami Tzabar Commissioner & Producer: Emma YousifMusic composition: Eleni ShawAudio 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 FrySeries Producer: Dan HardoonEditor: Rami TzabarCommissioner & Producer: Emma YousifMusic composition: Eleni ShawAudio engineer: Richard CourticeVideo editor: Anthony LeAudio engineer: Perry RogantinVisual identity: Rob AshleyCommissioned 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 FrySeries Producer: Dan HardoonEditor: Rami TzabarCommissioner & Producer: Emma YousifMusic composition: Eleni ShawAudio engineer: Richard CourticeVideo editor: Anthony LeAudio engineer: Perry RogantinVisual identity: Rob AshleyCommissioned 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 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-aiThanks 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 3SIMA, A generalist AI agent for 3D virtual environmentsSIMA, Google DeepMind: The PodcastxLand 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.

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 FrySeries Producer: Dan HardoonEditor: Rami TzabarCommissioner & Producer: Emma YousifMusic composition: Eleni ShawAudio engineer: Richard CourticeProduction Manager: Dan LazardStudio Manager: Nicholas DukeVideo Director: Bernardo ResendeVideo Editor: Bilal MerhiAudio Engineer: Perry RogantinCamera and Lighting Operator: Robert MessereProduction Coordination: Zoey Roberts, Sarah Ellen MortonVisual Identity and Design: Rob AshleyCommissioned 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 benchmarksForest loss drivers: paper, summary from WRI, and blog from GFWForest loss drivers code: Google Earth Engine; at WRI; at GFW; or Zenodo. Deep learning based remote sensing (open source): Jeo, GeeFlowSpecies mapping paper: ArxivGoogle resources: Google Earth Engine. Agri with Google, wildlife camerasPerch: code, paperPerch x coral reefs: BlogAgile Modelling: paper, codeDolphinGemma: 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.