Google DeepMind: The Podcast

How do you know if what you're seeing is real? Professor Hannah Fry sits down with Pushmeet Kohli (VP of Science) and Jeremy Ratcliffe (RS) to break down SynthID, the watermarking technology expanding from text, images, and video straight into biology.

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.

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. As a professor at Cambridge and VP of Research at Google DeepMind, Zoubin finds himself at the heart of an interesting debate: will improving machine uncertainty be one of the missing pieces to ever improving AI?

What if you were to peer inside the ‘mind’ of AI? You wouldn't find fully formed thoughts, just vast arrays of numbers. In this episode, Professor Hannah Fry is joined by Neel Nanda, to shine a light on an ongoing open area of research, interpretability.

The conversation of the moment is focused on one topic: AI agents. Unlike traditional language models that simply respond to a prompt, autonomous agents can execute multi-step plans and perform complex tasks on your behalf. But what happens when millions of these agents are not just working for us, but transacting, negotiating, and delegating to one another? Nenad Tomašev, Senior Staff Research Scientist at Google DeepMind, joins host Hannah Fry to discuss the theoretical framework of a future "agentic economy." Together, they discuss the operational shift from single systems to a cooperative "society of specialists," the psychological risk of human automation bias, and the complex cybersecurity landscape—from dynamic cloaking to agentic traps—required to keep distributed intelligence secure.

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

In our final episode of the season, Professor Hannah Fry sits down with Google DeepMind co-founder and CEO Demis Hassabis for their annual check-in. Together, they look beyond the product launches to the scientific and technological questions that will define the next decade. Demis shares his vision for the path to AGI - from solving "root node" problems in fusion energy and material science to the rise of world models and simulations. They also explore what's beyond the frontier and the importance of balancing scientific rigor amid the competitive dynamics of AI advancement.

Shane Legg, Chief AGI Scientist and co-founder of Google DeepMind, has been talking about artificial general intelligence, or AGI, for more than a decade. So what’s changed? According to Shane, now is the time to take it seriously. In this episode, Shane walks Professor Hannah Fry through his AGI framework, breaking down the levels from minimal to full AGI, and his timelines for each. They discuss the economic and societal shifts AGI will bring, the potential impact on work, and the extraordinary possibilities for human flourishing.

Five years ago, AlphaFold 2 solved the protein structure prediction problem, unlocking new avenues of biological research and providing our first major proof point that AI can be a powerful tool to advance science. The profound scientific and societal value of this work was even recognized in 2024 with the Nobel Prize in Chemistry. In this episode, Hannah is joined by John Jumper, one of the most instrumental scientists behind AlphaFold. He shares stories about his Nobel win, the tool's unexpected applications, and the shift in architecture from AlphaFold 2 to the more comprehensive AlphaFold 3.

How do you train an AI to drive safer than a human? Professor Hannah Fry sits down with Waymo Distinguished Engineer Vincent Vanhoucke to break down the complexities of autonomous driving—from the "closed loop" problem of real-world traffic to using generative AI for simulation. Plus, Hannah moves from theory to practice, taking a Waymo for a spin in California to experience it firsthand.

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.

Social engineering, cyberattacks, and the fog of war - all topics covered in this interview with the VP of Security and Privacy at Google DeepMind. Hannah Fry and Four Flynn take us behind the scenes of Operation Aurora, the monumental 2009 attack on Google that forever changed the landscape of cybersecurity. They discuss the defender's dilemma, the constant battle between attackers and defenders in the digital world, and how AI can potentially help mitigate some of the most complex vulnerabilities. As Hannah said, there was just too much to fit into one episode, so keep an eye on your feed for part 2. If you’re worried about missing it, why not subscribe and turn on notifications for new episodes. Until next time!

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.

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.

Could we use the sound of a coral reef to determine its health? Do we know where all the world's natural forests are? And are we on the verge of using AI to decode animal communication? In this episode, Professor Hannah Fry is joined by Drew Purves, Nature Lead at Google DeepMind. They explore how AI is helping ecologists map forests and species for the first time in history and how this data can be used to better understand the root causes of deforestation. They also explore bioaoustics and how sound is playing a pivotal role in tracking species on land and underwater —providing a powerful new way for us to understand and protect the environment.

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.

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.

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.

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.

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.

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.

In this episode, Hannah is joined by Oriol Vinyals, VP of Drastic Research and Gemini co-lead. They discuss the evolution of AI agents, the complexity of scaling, and some of the new agentic capabilities recently released by Google DeepMind.

Join host Hannah Fry as she discusses the complexities of regulating artificial intelligence with Nicklas Lundblad, Director of Public Policy at Google DeepMind, who emphasizes the importance of a nuanced approach focused on adaptability and evidence-based policymaking.

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. They'll explore the challenges of generating natural-sounding speech and maintaining listener engagement, as well as exciting new modalities on the horizon.

Hear Google DeepMind CEO Demis Hassabis and Nobel Laureates Sir Paul Nurse, Jennifer Doudna, and John Jumper discuss AI's impact on scientific discovery with Professor Hannah Fry.

In this episode, host Hannah Fry and Google DeepMind Senior Staff Research Scientist Iason Gabriel discuss the ethical implications of advanced AI assistants.

What does the future of AI in the classroom look like? Join research lead, Irina Jurenka, and Professor Hannah Fry as they explore the complicated yet exciting world of AI in education.

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.

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.

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.

Join Professor Hannah Fry as she delves into critical questions on safety with Anca Dragan, lead for AI safety and alignment at Google DeepMind.

Professor Hannah Fry is joined by Google DeepMind's senior research director Doug Eck to explore AI's capacity for true creativity.

It has been a few years since Google DeepMind CEO and co-founder, Demis Hassabis, and Professor Hannah Fry caught up. In that time, the world has caught on to artificial intelligence—in a big way.

Hannah wraps up the series by meeting DeepMind co-founder and CEO, Demis Hassabis. In an extended interview, Demis describes why he believes AGI is possible, how we can get there, and the problems he hopes it will solve. Along the way, he highlights the important role of consciousness and why he’s so optimistic that AI can help solve many of the world’s major challenges. As a final note, Demis shares the story of a personal meeting with Stephen Hawking to discuss the future of AI and discloses Hawking’s parting message.

AI needs to benefit everyone, not just those who build it. But fulfilling this promise requires careful thought before new technologies are built and released into the world. In this episode, Hannah delves into some of the most pressing and difficult ethical and social questions surrounding AI today. She explores complex issues like racial and gender bias and the misuse of AI technologies, and hears why diversity and representation is vital for building technology that works for all.

AI doesn’t just exist in the lab, it’s already solving a range of problems in the real world. In this episode, Hannah encounters a realistic recreation of her voice by WaveNet, the voice synthesising system that powers the Google Assistant and helps people with speech difficulties and illnesses regain their voices. Hannah also discovers how ‘deepfake’ technology can be used to improve weather forecasting and how DeepMind researchers are collaborating with Liverpool Football Club, aiming to take sports to the next level.

Step inside DeepMind's laboratories and you'll find researchers studying DNA to understand the mysteries of life, seeking new ways to use nuclear energy, or putting AI to the test in mind-bending areas of maths. In this episode, Hannah meets Pushmeet Kohli, the head of science at DeepMind, to understand how AI is accelerating scientific progress. Listeners also join Hannah on a [virtual] safari in the Serengeti in East Africa to find out how researchers are using AI to conserve wildlife in one of the world’s most spectacular ecosystems.

Hannah meets DeepMind co-founder and chief scientist Shane Legg, the man who coined the phrase ‘artificial general intelligence’, and explores how it might be built. Why does Shane think AGI is possible? When will it be realised? And what could it look like? Hannah also explores a simple theory of using trial and error to reach AGI and takes a deep dive into MuZero, an AI system which mastered complex board games from chess to Go, and is now generalising to solve a range of important tasks in the real world.

Do you need a body to have intelligence? And can one exist without the other? Hannah takes listeners behind the scenes of DeepMind's robotics lab in London where she meets robots that are trying to independently learn new skills, and explores why physical intelligence is a necessary part of intelligence. Along the way, she finds out how researchers trained their robots at home during lockdown, uncovers why so many robotics demonstrations are faking it, and what it takes to train a robotic football team.

Cooperation is at the heart of our society. Inventing the railway, giving birth to the Renaissance, and creating the Covid-19 vaccine all required people to combine efforts. But cooperation is so much more. It governs our education systems, healthcare, and food production. In this episode, Hannah meets the researchers working on cooperative AI, and hears about their work and influences from the famous American psychologist - and pigeon trainer - BF Skinner to the strategic board game Diplomacy. CTA: For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. Interviewees: DeepMind’s Thore Graepel, Kevin Mckee, Doina Precup & Laura Weidinger Credits Presenter: Hannah Fry Series Producer: Dan Hardoon Production support: Jill Achineku Sounds design: Emma Barnaby Music composition: Eleni Shaw Sound Engineer: Nigel Appleton Editor: David Prest Commissioned by DeepMind Thank you to everyone who made this season possible! Further reading: Machines must learn to find…

Hannah explores the potential of language models, the questions they raise, and if teaching a computer about language is enough to create artificial general intelligence (AGI). Beyond helping us communicate ideas, language plays a crucial role in memory, cooperation, and thinking – which is why AI researchers have long aimed to communicate with computers using natural language. Recently, there has been extraordinary progress using large-language models (LLM), which learn how to speak by processing huge amounts of data from the internet. The results can be very convincing, but pose significant ethical challenges.

In December 2019, DeepMind’s AI system, AlphaFold, solved a 50-year-old grand challenge in biology, known as the protein-folding problem. A headline in the journal Nature read, “It will change everything” and the President of the UK's Royal Society called it a “stunning advance [that arrived] decades before many in the field would have predicted”. In this episode, Hannah uncovers the inside story of AlphaFold from the people who made it happen and finds out how it could help transform the future of healthcare and medicine.

The chart-topping podcast which uncovers the extraordinary ways artificial intelligence (AI) is transforming our world is back for a second season. Join mathematician and broadcaster Professor Hannah Fry behind the scenes of world-leading AI research lab DeepMind to get the inside story of how AI is being created – and how it can benefit our lives and the society we live in.

In this special extended episode, Hannah Fry meets Demis Hassabis, the CEO and co-founder of DeepMind. She digs into his former life as a chess player, games designer and neuroscientist and explores how his love of chess helped him to get start-up funding, what drives him and his vision, and why AI keeps him up at night. 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.

AI researchers around the world are trying to create a general purpose learning system that can learn to solve a broad range of problems without being taught how. Koray Kavukcuoglu, DeepMind’s Director of Research, describes the journey to get there, and takes Hannah on a whistle-stop tour of DeepMind’s HQ and its research. 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.

While there is a lot of excitement about AI research, there are also concerns about the way it might be implemented, used and abused. In this episode Hannah investigates the more human side of the technology, some ethical issues around how it is developed and used, and the efforts to create a future of AI that works for everyone. 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.

The ambition of much of AI research is to create systems that can help to solve problems in the real world. In this episode, Hannah meets the people building systems that could be used to save the sight of thousands, help us solve one of the most fundamental problems in biology and reduce energy consumption in an effort to combat climate change. But whilst there is great potential, there are also important obstacles that will need to be tackled for AI to be used effectively, safely and fairly. 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.

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.

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.

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.