The Nature of AI: Solving the Planet's Data Gap with Drew Purves

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 readingGenie 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!  

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!  

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!  

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/alphafold3Thanks 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!  

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 RoboticsAdvances in robot dexterityGemini Robotics x YouTube Thanks to everyone who made this possible, including but not limited to:Presenter: Professor Hannah FrySeries Producer: Dan HardoonEditor: Rami TzabarCommissioner & Producer: Emma YousifMusic: Eleni ShawAudio Engineer: Richard CourticeProduction Manager: Dan LazardVideo Studio Production: Nicholas Duke VideoDirector: 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 DeepMindPlease 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!  

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 AMIEThanks to everyone who made this possible, including but not limited to: Presenter: Professor Hannah FrySeries Producer: Dan HardoonEditor: Rami TzabarCommissioner & Producer: Emma YousifMusic: Eleni ShawAudio Engineer: Richard CourticeProduction Manager: Dan LazardVideo Studio Production: Nicholas Duke VideoDirector: 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!  

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 FrySeries Producer: Dan HardoonEditor: Rami TzabarCommissioner & Producer: Emma YousifMusic composition: Eleni ShawAudio engineer: Richard CourticeProduction Manager: Dan LazardVideo Director: Bernardo ResendeVideo Editor: Alex Baro Cayetano, Bilal MerhiAudio Engineer: Richard CourticeCamera and Lighting Operator: Robert MessereProduction Coordination: Zoey Roberts, Sarah Ellen MortonVisual Identity and Design: Rob AshleyCommissioned 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!  

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 Introduction01:50 Era of experience03:45 AlphaZero10:19 Move 3715:20 Reinforcement learning and human feedback24:30 AlphaProof29:50 Math Olympiads35:00 Experience based methods42:56 Hannah's reflections44:00 Fan Hui joins___Thanks to everyone who made this possible, including but not limited to: Presenter: Professor Hannah FrySeries Producer: Dan HardoonSeries Editor: Rami TzabarCommissioner & Producer: Emma YousifMusic Composition: Eleni ShawAudio Engineer: Richard CourticeProduction Manager: Dan LazardVideo Director and Editor: Bernardo ResendeVideo Studio Production: Nicholas DukeVideo 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!  

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 BesseThanks to everyone who made this possible, including but not limited to: Presenter: Professor Hannah FrySeries Producer: Dan HardoonEditor: Rami Tzabar, TellTale StudiosCommissioner & Producer: Emma YousifMusic composition: Eleni ShawCamera Director and Video Editor: Bernardo ResendeAudio Engineer: Perry RogantinVideo Studio Production: Nicholas DukeVideo Editor: Bilal MerhiVideo Production Design: James BartonVisual Identity and Design: Eleanor TomlinsonCommissioned 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!  

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 BesseThanks to everyone who made this possible, including but not limited to: Presenter: Professor Hannah FrySeries Producer: Dan HardoonEditor: Rami Tzabar, TellTale Studios Commissioner & Producer: Emma YousifMusic composition: Eleni ShawCamera Director and Video Editor: Bernardo ResendeAudio Engineer: Perry RogantinVideo Studio Production: Nicholas DukeVideo Editor: Bilal MerhiVideo Production Design: James BartonVisual Identity and Design: Eleanor TomlinsonCommissioned by Google DeepMind— Subscribe to our YouTube channel Find us on XFollow us on InstagramAdd us on Linkedin 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!