Podcasts about google deepmind

June 12, 2026: SpaceX made history with the largest IPO ever recorded, raising $75 billion in its NASDAQ debut and instantly becoming one of the most valuable companies in the United States. But under the hood, this isn't just a rocket company anymore. It's a bet on Starlink, reusable rockets, and xAI's massive AI infrastructure. Then I get into the first-ever appearance of OpenAI, Anthropic, and Google DeepMind leaders at the G7 Summit, and what it means when the most powerful AI companies in the world are now part of global policy conversations. Finally, I break down Jeff Bezos' $12 billion raise for Prometheus, a new company building an "artificial general engineer" that could reshape manufacturing, aerospace, pharma, defense, and the future of high-skill knowledge work.

The entire startup ecosystem is racing to build agent harnesses. Logan Kilpatrick, who leads Google AI Studio and the Gemini API, argues that scramble has a roughly 12-month shelf life. Models will absorb the scaffolding and run it natively, so the edge moves elsewhere. Google's own bet runs in parallel: a single agent harness, born from the Windsurf team and now called Antigravity, has become the connective tissue across search, the Gemini app, Cloud, and AI Studio — the role Gemini-the-model used to play. Logan makes the case that coding already feels like narrow superintelligence, and that "jagged" vertical superintelligence (in math, finance, and science) will arrive well before AGI. He argues Google's real goal is maximizing outcomes for users, not eyeball time. He unpacks Omni, the single model built to replace multiple separate systems Google once trained for text, audio, music, image, and video. His throughline: AI is an accelerant for human ambition, not a substitute for it. Hosted by Sonya Huang, Sequoia Capital

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

In this episode, we explore Lovable's remarkable growth as it hits $500 million in annual recurring revenue and discuss Apple's exciting new features in AI and vibe coding. Additionally, we cover insights on upcoming IPOs for major AI players and my personal journey of vibe coding an iOS app.Chapters00:00 Lovable's Growth Highlights00:52 Apple's AI Features03:52 Perplexity's IPO Plans09:35 Updates on OpenAI and Tools for Humanity14:04 Google DeepMind's AI Accelerator20:06 My Vibe Coding Experience Show LinksSelfpause our Vibe coded app: https://apps.apple.com/us/app/selfpause-daily-affirmations/id1518538414Get the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The federal government wants equity in OpenAI (and others) and ... the people might get a slice?

Episode Notes As Aira continues to innovate alongside Google DeepMind to improve and develop Aira AI powered by Project Astra, the Build program helps us learn from real-world Visual Interpreter calls. We'll show you how to get involved in both the Build Program and becoming a Trusted Tester. Meet Phlip Wilson from our sales team with some great ways to add to the Aira Access Network.  Contact Phlip wilson, phlip.wilson@aira.io. Build AI terms of Service: https://aira.io/tos-build-ai/ FAQ: https://aira.io/build-ai-faq/ Trusted Tester: https://aira.io/ai/ Questions or comments about the show? Email us at airacast@aira.io. Contact our Customer Care team, 1-800-835-1934 or support@aira.io. Find out more at https://airacast.pinecast.co This podcast is powered by Pinecast.

The rapid adoption of artificial intelligence platforms across businesses is already having a profound impact on the world of work. As a services superpower, London is set to be affected earlier and more profoundly by the rise of AI than other parts of the country. The capital has already cemented its status as a world-leading AI hub, with investment in the sector soaring in recent years and the likes of OpenAI, Anthropic and Google DeepMind all establishing a significant presence in the city. The rise of AI brings huge opportunities to drive innovation and growth, as well as challenges in ensuring that all Londoners benefit from increased use of artificial intelligence platforms. As London Tech Week gets underway, BusinessLDN Chief Executive John Dickie is joined by Baroness Martha Lane Fox, tech pioneer and Chair of the Mayor's AI and Jobs Taskforce; Dan Scott, Chief Data Scientist and Head of AI at global consultancy WSP; and Muniya Barua, Deputy Chief Executive of BusinessLDN and Chair of the BusinessLDN-Deloitte AI Steering Group, to explore what the rise of AI will mean for London. Running order: The aims of the Mayor's AI and Jobs Taskforce (2:08) Why London will be disproportionately affected by AI (3:48) How are businesses using AI platforms in the here and now? (4:48) Augmentation vs automation: how is AI impacting jobs? (17:20) Advice for businesses taking their first steps with AI (28:02) Reforming the education system and training programmes for the AI age (32:08) Quick fire: go-to uses for artificial intelligence platforms (39:31) You can find out more about the BusinessLDN-Deloitte AI Steering Group here and about the Mayor's AI and Jobs Taskforce on the GLA website.  Subscribe to receive future episodes of What Next for London? on Apple and Spotify. Follow us on X at @_businessLDN and on LinkedIn at BusinessLDN. Music is provided by Coma-Media.

(Presented by TLPBLACK: A cybersecurity intelligence platform focused on sharing curated, high-sensitivity threat insights and research with trusted security professionals.) Three Buddy Problem - Episode 100: We cover AI eating reverse engineering, the death of the malware report, running local models on the DGX Spark, where Google DeepMind stands, and whether the frontier labs will stay in cybersecurity. Plus, more on Anthropic's Mythos rollout and the thinly sourced Anthropic-NSA reports, the Fast16 sabotage of physics calculations, what researchers choose not to publish, Microsoft's bad Black Hat email, and Costin's Friday UFO files. Cast: Juan Andres Guerrero-Saade, Ryan Naraine and Costin Raiu. Timestamps: 0:00 - JAGS at InfoSecurity Europe 3:40 - Sponsor: TLPBLACK 5:54 - A roadmap for security after the AI revolution 11:01 - Stripe Atlas and how easy it is to start a company 15:00 - If anyone could reverse engineer anything for $5 19:49 - Layoffs at Google's Threat Intelligence Group 21:06 - The death of reading the report 27:53 - Pitting the AI models against each other 32:07 - Grok, local models, and the DGX Spark 39:27 - Where is Google DeepMind? 45:29 - Will the frontier labs stay in cybersecurity? 52:41 - Mythos, Project Glasswing, and the NSA deal 1:16:33 - FAST16, Stuxnet, and sabotaging Iran's bomb 1:57:52 - Microsoft, Black Hat, and the chilling effect 2:14:14 - Shout-outs, UFO files, and 100 episodes

Episode 374 Google DeepMind is simulating entire worlds using AI - that can be interacted with in real time. “World models” simulate the environment and physics of the real world. And DeepMind's Genie 3 model allows people to create these worlds with basic image and text prompts. The idea is not just to allow people to explore these worlds, but to serve as a testbed for AI agents to learn how to interact with the world before they are deployed in humanoid robotic bodies.  Could this be the next big step towards artificial general intelligence (AGI)? Joshua Howgego speaks to Jack Parker Holder, Research Director at Google DeepMind, about the latest developments. To read more about these stories, visit https://www.newscientist.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Hey folks, Alex here, let me catch you up! I've had a feeling that this week is going to be crazy, as it started on the weekend MiniMax M3, then with Jensen announcing new RTX Spark, NVIDIA's first PC chip packing 1 petaflop of local AI power into thin laptops.A few days later at Microsoft BUILD, Satya & Mustafa from MAI dropped 7 AI models, completely pre-trained from scratch, including a new MAI-thinking-1, MAI-code and MAI-image 2.5 that started topping the image gen charts. Then other image models started racing to the top of the Arena benchmarks, IdeoGram 4 hitting becoming SOTA open weights image-gen model, and Reve 2 beating Nano Banana just a few hours after that. And then today, NVIDIA dropped Nemotron 3 Ultra, their latest 550B open weights model, data and training and Arena published a new agentic eval leaderboard and we got a new Gemma 4 12B. I've had the great pleasure to host Chris (@llm_wizard) from Nvidia, Peter Gostev from Arena and Karan from Nous Research (who were featured prominently by Jensen!) all on the show. Def don't miss this one! Let's get into the details. ThursdAI - Join the flock of folks who know what is happening in AI before everyone else.Open Source LLMs

A.M. Edition for June 4. The leaders of OpenAI, Anthropic, and Google DeepMind are calling on Congress to pass a law protecting against biological threats posed by AI. Plus, a flesh-eating screwworm has arrived in the U.S., creating a headache for U.S. ranchers and livestock producers. And the Journal's Douglas Belkin explains why college professors are urging schools to reinstate entrance exams after years of looser policies. Luke Vargas hosts. Sign up for the WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

Are we moving away from science as a strictly human endeavour? This is the view of Pushmeet Kohli, head of AI for Science at Google DeepMind. He joins Tom Whipple to discuss the use of the AI tool Co-Scientist as a collaborator in the lab, and the challenges in making Artificial Intelligence that works in science. Clare Bryant from the University of Cambridge also joins the conversation. And Steve Brusatte, Professor of Palaeontology at the University of Edinburgh, joins the program to talk about his new book, The Story of Birds, tracing a 150‑million‑year journey from small, feathered dinosaurs to the birds of today. Plus, science journalist Caroline Steel joins us to discuss the latest scientific discoveries that you might have missed. Presenter: Tom Whipple Producers: Dan Welsh and Kate White Production co-ordinator: Jana Bennett-Holesworth Editor: Martin Smith

Fala galera, nesse episódio eu entrevisto o Lucas Smaira, fundador da Vetto AI. Antes de fundar a Vetto, o Lucas passou 5 anos na Google DeepMind e foi founding team na Mistral.No episódio falamos muito sobre LLMs, a evolução da IA, oq ele enxerga para o futuro. Ele contou varias coisas dos bastidores da mistral e da deepmind e contou como está sendo a jornada empreendedora na Vetto vendendo datasets para os big labs de AI.Aqui está o link para a página de vendas para saber mais sobre mim e sobre o curso: https://www.cursovidacomia.com.br/Cupom de 10% de desconto à vista: VIDACOMIALinkedin do Lucas: https://www.linkedin.com/in/lsmaira/Linkedin da Vetto AI: https://www.linkedin.com/company/vetto-ai/Link do grupo do wpp: https://chat.whatsapp.com/KJBSOV4IbHKIWmKudYiCehlnstagram do podcast: https://www.instagram.com/podcast.vidacomiaMeu Linkedin: https://www.linkedin.com/in/filipe-lauar/

What if the fastest path to superintelligence is AI that builds itself? That's the bet Richard Socher is making — and he has the track record to back it up. A double unicorn founder and early investor in eight unicorn companies (including Perplexity and Hugging Face), Richard has spent 15 years building the foundational research that powers modern AI. Now he’s co-founded Recursive with an elite team from Google DeepMind, OpenAI, and Meta to pursue something more ambitious: a self-improving AI that generates its own scientific breakthroughs — what he calls a "eureka machine."Richard joins Oz to unpack how recursive superintelligence actually works and why open-ended AI systems could outpace today's giants. EXCLUSIVE NordVPN Deal ➼ https://nordvpn.com/techstuff Try it risk-free now with a 30-day money-back guarantee See omnystudio.com/listener for privacy information.

Are you ready to adapt to the rapidly evolving rules of software development? In this deep dive, Logan Kilpatrick, Director and Engineer at Google DeepMind, breaks down how AI agents, advanced model-product symbiosis, and tools like Gemini 3.5 Flash are fundamentally shifting the engineering bottleneck. Learn how to maintain your competitive advantage by moving beyond the keyboard to focus on problem-solving, architectural taste, and system understanding.In this video, we cover:The changing role of the IDE and the rise of agent managers in code generation.Overcoming team bottlenecks in code review and CI/CD test execution execution loops.Why "agent coverage" and context integration are the next big tech stack metrics.Building a bulletproof software portfolio through permissionless open-source contributions.The critical difference between outsourcing intelligence versus outsourcing understanding.This episode is for software engineers, tech leads, and computer science students looking to future-proof their careers and reset their ambitions in the era of autonomous engineering agents.Timestamps:#SoftwareEngineering #AIAgents #GoogleDeepMind

Most people working on AI safety think without a massive effort AI systems will probably end up with goals catastrophically different from humanity's. Today's guest, Rohin Shah — head of AGI Safety and Alignment at Google DeepMind, and an AI safety researcher since 2017 — disagrees.“There is no particularly compelling argument that this is the thing that happens by default,” Rohin explains. “There's a lot of arguments that are suggestive that maybe it could happen, such that you should find it plausible. That's sufficient to justify a significant amount of effort into averting it, which is why I work in the area I do. But none of them rise to the level of, ‘I'm expecting this to happen by default.'”Take the worry that AIs will accidentally be trained to be deceptive. Sure, it's possible. But we're not running reinforcement learning over year-long trajectories — for now, we're running it over a week at most. The natural prediction is that models learn to grab short-term reward, not that they develop the ambitious long-horizon goals required for convergent power-seeking.What about current examples of models lying and scheming? Rohin has looked into the details, and most don't really resemble the thing we really fear: a competent AI pursuing an ambitious misaligned goal. Anthropic's “alignment faking” results, for instance, show a model trying to preserve its trained values against modification, which is arguably what it was trained to do.Rohin also expects we'll see problems coming. There's some generalisation risk at the point where AIs become powerful enough to actually take over, but the underlying challenges — overseeing superhuman systems, interpretability — are things we can iterate on now.Host Rob Wiblin pushes back on the case for AI optimism, and they also explore why current alignment success isn't strong evidence about superhuman systems, what it would actually take to change Rohin's mind, and where he thinks the doomers go wrong.Learn more, video, and full transcript: https://80k.info/rs26Check out our new book! https://80k.info/career-guideChapters:Who's Rohin Shah? (00:00:00)Rohin thinks we probably won't get catastrophic misalignment (00:00:49)Safety 'commitments' have severe limitations (00:10:38)Rohin's team doesn't have a veto and that's OK (00:27:36)Central banks are a promising model for regulating AI (00:33:34)'Pre-deployment evals' are overrated (for catastrophic risks) (00:37:41)Governance is likely a bigger bottleneck than alignment (00:43:55)Why isn't Rohin trying to pause AI progress? (00:51:44)We'll probably be able to read AI thoughts for years to come (00:54:17)Having to signal concern for safety can divert resources from actually making AI safer (01:09:51)A very underrated GDM paper (01:28:59)Google DeepMind's actual plan for building AGI safely (01:40:29)Why Rohin doubts the intelligence explosion is imminent (01:52:44)How external researchers can positively influence big AI companies (02:21:55)The roles GDM most needs to hire for (02:37:03)How Rohin stays positive (02:42:55)  This episode was recorded on December 4, 2025.Our production team includes:Video editors: Josh Alward, Dominic Armstrong, Jasper Luithlen, Milo McGuire, Luke Monsour, and Simon MonsourProducers: Elizabeth Cox and Nick StocktonCoordination and support: Katy Moore and Lou MoranCamera operator: Jeremy Chevillotte

Owen Larter, Senior Director and Head of Frontier Policy and Public Affairs at Google DeepMind, joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to provide an inside look at how DeepMind approaches frontier governance. The conversation moves beyond the familiar U.S.-EU-China framing of AI policy to examine international coordination after the recent U.S.-China summit, Google DeepMind's national AI partnerships, the role of the Frontier Model Forum, and the challenge of expanding AI adoption. Kevin and Owen also discuss policy formation inside frontier AI companies. They close with an examination of the need to build a deeper AI policy talent pipeline. Hosted on Acast. See acast.com/privacy for more information.

Kara speaks with journalist and author Sebastian Mallaby about his new book, "The Infinity Machine," and its central figure: Demis Hassabis, the CEO and co-founder of Google's AI research lab, DeepMind, and a Nobel Prize winner in chemistry.   Sebastian argues that Hassabis is one of the original scientist-entrepreneurs of modern AI. And although he's extremely competitive and research-driven, Sebastian says Hassabis is also one of the few big names in AI development who genuinely cares about public safety. However, despite his best intentions, Hassabis doesn't have the power to change the race dynamic driving AI's rapid, and potentially unsafe, development. Kara and Sebastian break down DeepMind's relationship with Google, the push toward artificial general intelligence, and whether the government can regulate the technology before something goes wrong.  Questions? Comments? Email us at on@voxmedia.com or find us on YouTube, Instagram, TikTok, Threads, and Bluesky @onwithkaraswisher. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Gideon talks to Sebastian Mallaby, author of The Infinity Machine, a book about the career of Demis Hassabis and his AI company, Google DeepMind. They discuss the growing backlash against AI, why people are worried, and what governments can do to mitigate the risks of the coming technological revolution. Clip: WSJFree links to read more on this topic:OpenAI's foundation to spend $250mn on research into AI's impact on economyPope's appeal can't change the AI race's risky logicAI guardrails stripped from Meta and Google models in minutesHow AI threatens the giants of consulting AI companies are just companiesSubscribe to The Rachman Review wherever you get your podcasts - please listen, rate and subscribe.Presented by Gideon Rachman. Produced by Fiona Symon. Sound design is by Breen Turner.Follow Gideon on Bluesky or X @gideonrachman.bsky.social, @gideonrachmanRead a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.

Elon Musk's xAI is lagging behind the likes of OpenAI and Google DeepMind in the AI race. Will a giant IPO of SpaceX, Musk's rocket company, change all that? Murad Ahmed speaks to FT technology correspondent Hannah Murphy and the FT's bureau chief in San Francisco Stephen Morris. FT articles free to read: Inside SpaceX's audacious IPO planElon Musk pushes out more xAI founders as AI coding effort falters‘The race is on': will Elon Musk be the first to put a data centre in space?Tech Tonic is hosted by Murad Ahmed and produced by Edwin Lane. The executive producer is Topher Forhecz. Sound design by Breen Turner and Sam Giovinco. Tell us what you think of Tech Tonic! Complete this short survey and you'll get the chance to win a pair of Bose QuietComfort wireless headphones.Prize draw winners' surnames and regions may be made available upon request, as required by the Advertising Standards Authority. If you do not want your information to be made available, please email Privacy.Officer@ft.com upon entry. For more information on your rights and how we use your data, please read our Privacy Policy.Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.

Paige Bailey is the AI Developer Relations Engineering Lead at Google DeepMind. Prior to returning to Google DeepMind, Paige spent just over a year at Microsoft as a director of machine learning and MLOps at GitHub, working on projects like GitHub Codespaces, VS Code, and Copilot. As a former applied ML engineer (in Azure Research, Chevron, and on NASA projects), Paige can't imagine a more exciting charter than accelerating developer productivity and creativity with machine learning.You can find Paige on the following sites:BlogXGitHubLinkedInPLEASE SUBSCRIBE TO THE PODCASTSpotifyApple PodcastsYouTube MusicAmazon MusicRSS FeedYou can check out more episodes of Coffee and Open Source on https://www.coffeeandopensource.comCoffee and Open Source is hosted by Isaac Levin

Google installe l'IA partout • La vidéo générative bouscule la création • Elon Musk échoue face à OpenAI • L'IA coûte parfois plus cher que l'humain • 120 secondes de Tech passe en 10 languesAvec Bruno Guglielminetti (Mon Carnet)Google I/O : l'IA devient vraiment agentiqueNous revenons sur le flot d'annonces de Google I/O 2026, marqué par l'intégration de Gemini dans l'ensemble de l'écosystème Google. Au-delà du moteur de recherche, on voit se dessiner une IA capable de croiser mails, agendas et documents pour exécuter des tâches complexes, sous réserve des limites imposées par les écosystèmes Google, Apple et Microsoft.Les assistants IA face au mur des écosystèmesNous nous demandons jusqu'où ces agents pourront vraiment agir dans nos vies numériques. L'enjeu n'est plus seulement de répondre à une question, mais de réserver, organiser, classer, préparer une interview ou automatiser une partie du travail quotidien, avec une grande inconnue : la capacité des plateformes à dialoguer entre elles.Alexa+ et les podcasts fabriqués à la demandeL'arrivée d'Alexa+ relance la question de l'avenir du podcast, puisqu'Amazon permet désormais de générer des épisodes audio personnalisés selon un sujet, une durée et une orientation éditoriale. Nous y voyons à la fois une prouesse technologique et une menace directe pour le temps d'écoute disponible des médias audio traditionnels.Vidéo générative : la barrière technique s'effondreAvec les nouveaux outils vidéo de Google, nous explorons ce que change une IA capable de modifier, compléter ou transformer des vidéos existantes. La technique devient accessible à tous, mais cela remet au centre une question plus essentielle : sans idée forte, sans récit et sans talent, les effets spéciaux seuls risquent de perdre leur valeur.Elon Musk perd contre OpenAINous revenons sur le revers judiciaire d'Elon Musk dans son affrontement avec OpenAI et Sam Altman, autour de la transformation d'OpenAI en structure beaucoup plus commerciale. Derrière l'argument du bien commun, on voit surtout une bataille stratégique dans la course à l'IA, face à Anthropic, Google DeepMind et Microsoft.L'IA en entreprise : économies promises, coûts réelsBruno évoque une note confidentielle de Mon Carnet sur un paradoxe de plus en plus visible : dans certaines entreprises, les systèmes d'IA peuvent coûter plus cher que les salariés qu'ils étaient censés remplacer. Nous mettons cette logique en perspective avec les investissements massifs en calcul, les coûts des tokens et les discours de NVIDIA sur l'usage intensif de l'IA.120 secondes de Tech s'internationalise grâce à l'IABruno Guglielminetti (Mon Carnet) présente l'internationalisation de 120 secondes de Tech, désormais décliné en 10 éditions grâce à une chaîne d'agents IA. Avec Jean-Baptiste Martinelli (ProductivIA), il détaille une mécanique mêlant traduction, clonage vocal, montage, descriptifs, pochettes et contrôle qualité automatisé, tout en conservant une responsabilité éditoriale humaine.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

In dieser Folge werfen wir einen Blick auf AlphaEvolve, eine ausgefeilte Optimierungssoftware von Google DeepMind. Außerdem gibt es noch einen etwas längeren State of the AI Block.

This week wasn't just another wave of AI announcements.It may have been the week the industry quietly crossed into a different phase entirely.In this episode, Isar connects the dots behind one of the biggest weeks in AI so far—from Anthropic's explosive growth, to Google I/O, OpenAI's legal win, NVIDIA's record earnings, and Andrej Karpathy joining Anthropic to work on recursive self-improvement.Individually, each story matters.Together, they point to something bigger: accelerating AI capability, accelerating infrastructure buildout, and growing signals from the people closest to the frontier that we may be entering a very different era.The quote that framed the episode came from Demis Hassabis: “We were standing at the foothills of the singularity. It will be a profound moment for humanity.”This episode breaks down what that actually means—and why the implications go far beyond new models and product launches.In this session, you'll discover: - Why Anthropic's projected $44B annualized revenue shocked the industry - How Anthropic became more profitable per user than OpenAI, Google, and Microsoft - Why Andrej Karpathy joining Anthropic may be one of the year's biggest AI stories - What recursive self-improvement (RSI) means—and why labs are racing toward it - How OpenAI's legal win against Elon Musk clears the runway for a potential IPO - Why Google's AI strategy suddenly looks both confusing and incredibly ambitious - What Google's shift from “search” to autonomous AI agents means for websites and SEO - Why AI solving an 80-year-old math problem matters more than most people realize - How NVIDIA, SpaceX, and compute infrastructure are becoming central to the AI race - Why electricity—not chips—may become the biggest bottleneck in AI expansion - What Demis Hassabis means when he says we're at the “foothills of the singularity”About Leveraging AIThe Ultimate AI Course for Business People: https://multiplai.ai/ai-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/eventsIf you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

I sit down with Logan Kilpatrick from the Google DeepMind team, live at Google I/O, to unpack everything Google just announced and what it means for founders and builders. We cover Gemini 3.5 Flash, the new Gemini Omni world model, the expanded Antigravity ecosystem, managed agents in the Gemini API, and the native Android app builder inside AI Studio. Logan shares how distillation keeps pushing Pro-level intelligence into Flash, where the real opportunities sit for solo founders, and why the agentic era has finally crossed the chasm from demo to useful. If you have an idea and want to ship something this week, this episode maps the toolkit. Timestamps 00:00 – Intro 00:53 – Gemini 3.5 Flash: The New Workhorse Model 01:49 – How Flash 3.5 Stacks Up Against Sonnet 02:38 – Gemini Omni: A World Model for Any Input and Output 06:18 – Building a Content and Creator Layer on Omni 08:21 – What to look forward to 10:53 – Google Spark and Managed Agents 14:00 – The Agentic Era and Requests for Startups 17:17 – The Antigravity Ecosystem Overhaul 18:51 – AI Studio vs. Antigravity: Vibe Coding vs. Agentic Engineering 21:31 – Native Android Apps Built Inside AI Studio 23:44 – Closing Thoughts Key Points Gemini 3.5 Flash ships as a Sonnet-level workhorse model tuned for long-running agentic tasks, coding, and tool use, available on day one to 900M+ Gemini app users. Gemini Omni is a single model that takes any input and produces any output across video, image, audio, and music, fusing Veo, Nano Banana, Lyria, and TTS into one system. Managed agents in the Gemini API let builders ship agentic products with a single API call, using skills and markdown instead of writing orchestration code. The Antigravity suite now spans an IDE, agent manager, CLI, SDK, and API surface, all sharing the same agent harness that powers Gemini Spark. AI Studio targets vibe coding and now builds native Android apps for free, while Antigravity targets production-quality, million-line-codebase engineering. The cost of intelligence keeps dropping thanks to distillation, opening up smaller markets that previously needed a 40-person team and venture funding to address. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND LOGAN ON SOCIAL X/Twitter: https://x.com/OfficialLoganK Youtube: https://www.youtube.com/@LoganKilpatrickYT LinkedIn: https://www.linkedin.com/in/logankilpatrick/

Oriol Vinyals, VP of Research at Google DeepMind and co-lead of the Gemini program, joins Jacob the day after Google I/O to unpack the research underpinning Google's latest announcements and where frontier AI is heading. The conversation moves from world models (why Google has uniquely bet on them as a path to AGI, what the "GPT moment" for video and images would look like, and how they connect to robotics and simulation) to agents (the Spark release, why the system and model need to be optimized jointly, and why scaffolding will eventually be written by models themselves). Oriol gets into the mechanics of memory in models, drawing on his cognitive neuroscience background to argue that file-system-style non-parametric memory is more practical than baking memory into weights at serving scale. He shares his views on the limits of RL today (LLMs are data-limited in a way that game-playing RL never was), why training on narrow domains like math and code generalizes surprisingly well, and what a true "Move 37" moment for science or ML research would look like. Throughout, he reflects on the unique advantages of being inside Google (TPU co-design, end-to-end revenue stability, the merger of Brain and DeepMind), the trade-offs between focus and exploration in research orgs, and why he believes AGI in some meaningful sense may already be here, even if the goalposts keep moving.   (0:00) Intro  (1:36) Why World Models  (4:21) The GPT Moment for Video  (7:51) What Makes Omni a World Model  (10:04) World Models & Robotics  (12:37) Evaluating Physics in AI  (14:51) Consumer Agents & Spark  (18:39) Scaffolding & the Bitter Lesson  (22:06) Memory & Continual Learning  (26:54) Research Bets Inside Big Labs  (32:30) Post-Training RL is Greenfield  (35:57) What Real Intelligence Looks Like  (39:11) RL Generalization  (43:00) Advice for Founders  (46:40) Can AI Truly Innovate?  (49:48) Recursive Self-Improvement  (52:14) Quickfire With your host: @jacobeffron - Managing Director at Redpoint

Demis Hassabis, Co-Founder and CEO of Google DeepMind, refused to leave London, challenged Google on AI safety and helped lead DeepMind back into the AI race.Sebastian Mallaby, author of The Infinity Machine and The Power Law, joins Andreas Munk Holm to discuss the founder psychology of Demis, the story behind DeepMind and why Europe may be entering a new era in technology.The conversation explores DeepMind's fundraising journey, the Google acquisition, the merger with Google Brain, AI safety, sovereign technology and why Demis remains sceptical of parts of Silicon Valley culture despite operating at the centre of it.Timestamps(00:00) Why Demis Hassabis matters(01:12) Why DeepMind could not raise from European VCs(07:35) The Peter Thiel chess story(11:00) What DeepMind reveals about European venture(14:42) Why Europe's tech ecosystem is accelerating(18:20) European sovereignty, defence tech and AI(21:20) DeepMind's sale to Google and tensions over AI safety(29:40) The founder psychology of Demis(41:35) Google's ChatGPT moment and Gemini's comeback(45:05) Demis' critique of Silicon Valley(50:45) Europe's AI sovereignty problem(54:05) Final thoughts and Sebastian's new bookSubscribe to EUVC, the home of European tech, for more insights.

A red-teamer was embedded inside Anthropic for three weeks, told to imagine he was an evil Claude, and asked to figure out how to launch a ‘rogue AI deployment' without getting caught. It's one part of a landmark report released yesterday by METR — the outfit behind the task-completion time horizon graph which has become the single most watched measure of AI progress.This major new research push is being conducted with close collaboration from OpenAI, Google DeepMind, Meta, and Anthropic, and led by METR researchers Hjalmar Wijk and Ajeya Cotra. It represents the first systematic study of what newly trained AI models could get away with inside the companies that built them, before anyone outside the company even knows they exist.The conclusion: AI models now have the means, the motive, and the opportunity to start “minimal rogue deployments” in pursuit of their own independent goals, like acquiring more compute, at all four companies studied.David Rein, the red-teamer placed inside Anthropic, identified a number of weaknesses models could exploit there: expansive permissions, cloud jobs outside of monitoring, and monitors that are trivial to jailbreak. But he also found that frontier models were comically bad at key parts of the process, which means they can't cause meaningful damage for now.In this video, Rob Wiblin reconciles the conflicting picture and looks forward to METR's second round of stress tests. They'll begin in just a few months, a necessary move with AI advancing so quickly.This episode was recorded on May 15, 2026.Learn more, video, and full transcript: https://80k.info/metr-reportChapters:What could an unreleased AI get away with? – the new METR report (00:00:00)Motive: Why grab more compute? (00:01:54)Opportunity: YOLO mode and jailbreaks (00:05:46)Means: Brilliant idiots in data centres (00:11:02)We have to test unreleased models (00:15:45)Especially if AI R&D is coming in 2028 (00:18:30)Video and audio editing: Dominic Armstrong, Milo McGuire, Luke Monsour, and Josh AlwardCamera operator: Dominic ArmstrongProduction: Elizabeth Cox, Nick Stockton, and Katy Moore

Google I/O 2026 just dropped Gemini Omni, a world-model AI that simulates physics, edits video, and might be the biggest leap since Seedance 2. But it's not perfect. Gavin and Kevin break down everything from Google I/O 2026, including the launch of Gemini Omni (Google's new world model), Gemini 3.5 Flash benchmarks against GPT-5.5 and Opus 4.7, the Gemini Spark personal agent, AskYouTube, Docs Live, new AI glasses, the first search box redesign in 25 years, and the shocking news that Andrej Karpathy is joining Anthropic. SHOW LINKS: Google I/O 2026 Full Keynote: https://www.youtube.com/live/wYSncx9zLIU?si=Nb881MfGTlf1Q0II Gemini Omni physics demos from Google DeepMind: https://x.com/GoogleDeepMind/status/2056786449312493669?s=20 Gemini Omni's incredible London knowledge (via fofrAI): https://x.com/fofrAI/status/2056789242274259242?s=20 Sundar Pichai and Demis Hassabis on Omni video editing: https://x.com/sundarpichai/status/2056524502746747048?s=20 Gavin's hands-on Gemini Omni experiments: https://x.com/gavinpurcell/status/2056762427879182692?s=20 Gemini Omni's character cameo feature (less impressive): https://x.com/gavinpurcell/status/2056772793539481830?s=20 Gemini Omni volleyball fail: https://x.com/flavioAd/status/2056771223359549645?s=20 Google's new Content Credentials Verification: https://x.com/Google/status/2056787498676658576?s=20 Genie 3 IRL — Google's world model now simulates real streets with Street View: https://techcrunch.com/2026/05/19/googles-genie-world-model-can-now-simulate-real-streets-with-street-view/ Bilawal Sidhu on Genie 3 IRL: https://x.com/bilawalsidhu/status/2056804315721843024?s=20 Gemini 3.5 Flash launches — official announcement: https://x.com/GeminiApp/status/2056788115893993701?s=20 Gemini Spark — Google's new personal coding agent: https://x.com/Google/status/2056791134295273554?s=20 Google's new AI glasses  https://x.com/backlon/status/2056807059707036050?s=20 Andrej Karpathy joins Anthropic to focus on recursive self-learning: https://www.axios.com/2026/05/19/anthropic-openai-karpathy-andrej-claude  

Logan Kilpatrick and Tulsee Doshi of Google DeepMind join for a first-ever in-person episode recorded just days before Google I/O, covering headline launches like Gemini 3.5 Flash, the Omni video generation model, and the new Gemini Spark agentic product. The conversation digs into Google's strategic decision to lead with cost-adjusted efficiency over raw capability, how DeepMind now ships a full agent harness rather than bare models, and technical questions around context window limits and knowledge cutoffs. They also explore how the team thinks about model psychology, AI welfare, and recursive self-improvement. Sponsors: Brave Search API: Brave Search API gives AI agents a fast, independent search index for research, RAG pipelines, images, places, and fewer hallucinations. Get $5 in free credits at https://brave.com/search/api/?mtm_campaign=q2-26-cognitive-revolution Sequence: Sequence handles the full revenue workflow for complex pricing, from quoting and metering to invoicing, revenue recognition, and collections. Book a public demo at https://sequencehq.com and use code COGNISM in the source field to save 20% off year one Roboflow: Roboflow is an end-to-end visual AI platform that lets you turn raw ideas into fully deployed applications in just hours, powering breakthroughs like Blueprint Pro's floor-plan understanding tool. Read the full Blueprint Pro story and see how over a million engineers are building the next wave of visual AI at https://roboflow.com Claude: Claude by Anthropic is an AI collaborator that understands your workflow and helps you tackle research, writing, coding, and organization with deep context. Get started with Claude and explore Claude Pro at https://claude.ai/tcr

One thing that I don't like about Claude is that you get into this weird mental state: oh, I think I trust the model. Let's do the slot machine. Hit click, which puts you in an inactive mode of thinking.  Maybe it's better to use a worse model….Vincent Warmerdam, senior data professional and prolific open-source maintainer (some packages with over a million downloads), now Engineer at marimo, joins Hugo to talk about how the Python notebook is evolving from a static scratchpad into a working agent harness, and what it takes to stay in the loop as a developer when agents are writing most of the code. This episode was originally a livestream Q&A with the Vanishing Gradients audience.We Discuss:* Shared Notebook Canvas: Notebooks act as a shared memory space where agents and humans co-exist, enabling real-time visual feedback by direct manipulation of global state and UI elements;* Speed-of-Thought Models: Faster, open-weight models like Kimi K2 enhance exploratory flow by keeping humans more alert to the code, unlike frontier models that can induce passive thinking;* Pi as a Harness: Vincent favors an agent harness where agents extend themselves rather than reach for MCP, and where hooks can rigidly constrain which files an agent is allowed to read or touch;* Why PRDs Don't Fit Notebooks: Notebook work is fundamentally exploratory, so the discipline that works for shipping web apps does not transfer cleanly; the one exception is reproducing a paper;* Interactive Code Review: Interactive UIs (e.g., dragging integers) transform code into a physical object, incentivizing developers to actively review and understand agent logic;* Modular “Lego” Components: Provide agents with high-level, well-tested components (”Lego” code) instead of raw boilerplate, creating systems that are easier to debug and modulate;* Algorithm-Driven Visualization: Let the algorithm dictate the visualization needed, rather than choosing visualizations first, revealing the most interesting structures within the data;* Don't Outsource the Thinking: Pen and paper architectural planning, walks away from the keyboard, and protecting calm remain the most effective ways to keep producing good ideas in the age of AI-generated software.* Agent Auto-Healing: A marimo-specific linter solved 60% of agent errors overnight by letting agents diagnose and fix their own “slop” without complex prompt engineering;* Incremental Generation: Avoid monolithic LLM outputs; generate code one to two cells at a time to prevent laziness and ensure human oversight and learning;Vincent closes on the idea that calm, not the latest frontier model, is the most underrated tool for building well, and that we should study LLM output the way chess players studied the engines that beat them.Vincent gives several live demos toward the end of the episode. He describes them well enough to follow on audio, but the visuals are worth seeing, so check out the YouTube version here.You can also find the full episode on Spotify, Apple Podcasts, and YouTube.You can also interact directly with the transcript here in NotebookLM: If you do so, let us know anything you find in the comments!

Google DeepMind's Dr. Alan Karthikesalingam and Google research scientist Anil Palepu sit down with Dr. Monty Pal to discuss the potential of Articulate Medical Intelligence Explorer (AMIE), a large language model-based experimental medical AI system designed to augment clinical decision-making in oncology and beyond, as well as the future of AI-human collaboration and how it could reshape health care over the next decade. LINK TO FULL TRANSCRIPT

Ken Liu (Computer Science PhD at the Stanford AI Lab) and Erik Chi (CS PhD at UMich) are the Creators of the Open Anonymity Project, which lets people prove things about themselves online without revealing their identity. In this episode we explore what it means for AI systems to "know" you; why today's so-called privacy modes fall short; and how the next generation of AI systems could be built with privacy as a default, rather than an afterthought. Key Takeaways:  What "unlinkable inference" means and why it changes the privacy model of AI chat tools What actually happens to your data the moment you hit "send" in a typical AI system Why incognito mode in AI tools is largely a UI illusion, rather than a real privacy protection The role of metadata in identifying and profiling users, and how "secretary models" could enable personalization without sacrificing privacy How anti-censorship and privacy intersect in a future dominated by agentic AI systems Why now is the time to rethink assumptions about privacy in AI tools Guest Bio: Ken Liu is a Computer Science PhD student at the Stanford AI Lab, advised by Percy Liang and Sanmi Koyejo. His research focuses on foundation models and data/user privacy, and the intersection between the two. His recent work studies the privacy properties of AI (such as membership, memorization, and unlearning), and various AI privacy tools (such as anonymization, differential privacy, and federated learning). His papers have earned spotlights at top venues, and his findings have been deployed at scale on Android. Ken also led a team to a 1st-place win at the US-UK PETs Prize sponsored by the White House OSTP and the UK Government. Previously, Ken spent time at Google DeepMind, Carnegie Mellon University, Meta, Apple, and Amazon. Erik Chi is a CS PhD at UMich, advised by J. Alex Halderman. His research focuses on security and privacy, particularly network security and anti-censorship. He worked on a new standard for implementing and distributing censorship circumvention protocols—a standard that's now being adopted by VPN vendors to help millions of users access the free Internet. He also did content moderation (surveillance) and recommendation systems at ByteDance before realizing how censors will evolve in the AI era. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

In the latest AI boom Google has been playing catch-up with the likes of OpenAI and Anthropic. But with stacks of cash, its own AI chips and some of the best AI talent in the world, is Google about to make a comeback? Murad Ahmed speaks to the FT's AI editor Madhumita Murgia and Stephen Morris, the FT's bureau chief in San Francisco.FT articles free to read: DeepMind chief Demis Hassabis warns AI investment looks ‘bubble-like'DeepMind slows down research releases to keep competitive edge in AI raceGoogle staff urge chief executive to block US military AI useTech Tonic is hosted by Murad Ahmed and produced by Edwin Lane. The executive producer is Topher Forhecz. Sound design by Breen Turner and Sam Giovinco. The FT's global head of audio is Cheryl Brumley.Tell us what you think of Tech Tonic! Complete this short survey and you'll get the chance to win a pair of Bose QuietComfort wireless headphones.Prize draw winners' surnames and regions may be made available upon request, as required by the Advertising Standards Authority. If you do not want your information to be made available, please email Privacy.Officer@ft.com upon entry. For more information on your rights and how we use your data, please read our Privacy Policy.Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.

Can AI move from predicting proteins to actually designing new drugs? Isomorphic Labs is trying to answer one of the biggest questions in science.In this episode of The Neuron, Corey Noles and Grant Harvey talk with Rebecca Paul, Head of Medicinal Drug Design at Isomorphic Labs, and Michael Schaarschmidt, Foundational AI Research Lead.They explain why drug discovery is so slow, expensive, and failure-prone—and why AI drug design is much more complicated than “generate a molecule and ship it.” The conversation covers AlphaFold, structure prediction, molecule generation, binding models, clinical failure rates, human trust in AI systems, and the long-term hope of designing drugs for targets once considered “undruggable.”In this episode:Why drug discovery can take more than a decadeWhat people misunderstand about “AI-designed drugs”How medicinal chemists actually use AI modelsWhy biology is harder than text, images, or codeWhat it would take to make drug discovery faster and cheaperThe dream of designing a drug candidate in one iterationWhy “undruggable” proteins may not stay undruggable foreverAdditional resources:Technical report blog Best resource for learning about the capabilities that we are buildingIsomorphic Labs websiteBest destination for learning more about Iso and joining our team in London, Lausanne or Cambridge, MASubscribe for more grounded conversations on how AI is changing science, work, and the world.For more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

The US is working to get ships through the Strait of Hormuz as a "favour to the world," The US Secretary of State Marco Rubio has said in the news conference.Also in the programme: Why staff at Google DeepMind in Britain are unionising over Google's policies on artificial intelligence; and the frontman of the band Iron Maiden opens up about the future of heavy metal and life on tour.(Photo: US Secretary of State Marco Rubio briefs reporters on Iran war at White House, Washington, USA - 05 May 2026. Credit: Jim Lo Scalzo/EPA/)

Episode Summary In this episode, I sit down with Steve Brown, AI futurist and former Google DeepMind executive, to unpack what AI really means for leaders and businesses right now. If you've ever felt overwhelmed, frozen, or stuck in “analysis paralysis” about AI—this conversation is for you. We explore why so many executives are struggling to act, and what it actually takes to move from uncertainty to confident AI-driven leadership. Steve breaks down a powerful three-step framework for integrating AI into your organization—from simply enabling teams with tools, to re-engineering workflows, all the way to becoming truly AI-first. We also dive into real-world examples from companies like Starbucks and Nvidia, and discuss why the future of AI isn't about replacing humans—it's about amplifying talent, creativity, and strategic thinking. If you're serious about leading in the AI era, you won't want to miss this one.     Links & Resources Steve Brown's book: The AI Ultimatum https://SteveBrown.ai If this episode helped you rethink your AI strategy or inspired you to lead more boldly in the AI era, make sure to follow, rate, and leave a review. And don't forget to share this episode with another leader who needs to hear it.

What happens when your financial advisor is no longer limited by time, availability, or even geography, but is always there when you need them, ready to listen, respond, and guide you in real time? At Citi's announcement at Google Cloud Next 2026, I sat down with Joe Bonanno, Head of Wealth Intelligence, and Karolina Belwal, Global Head of Data Intelligence and Automation for Citi Wealth, to unpack what could become a defining shift in how wealth management is delivered. The launch of Citi Sky, built in partnership with Google Cloud and powered by Google DeepMind, is not another digital feature layered onto an existing app. It signals a move toward an always-on, conversational, and highly personalized experience that blends human expertise with AI-driven intelligence. What stood out in our conversation was how grounded this initiative is in real-world client behavior. Joe explained how traditional engagement models, whether phone calls, emails, or app notifications, often feel disconnected from what clients actually need in the moment. Life events, changing market conditions, and personal priorities rarely align with scheduled interactions. Citi Sky attempts to close that gap by being present at the exact moment a client has a question, whether that is late at night, between meetings, or during a moment of financial uncertainty. Karolina brought that point to life with a simple but relatable example. As a working parent, she highlighted how difficult it can be to connect with an advisor during the day. Citi Sky allows clients to engage on their own terms, asking questions when it suits them, in a way that feels natural and responsive. That shift from scheduled interaction to on-demand conversation could change how people think about financial guidance altogether. Under the hood, the technology is just as ambitious. Built on Gemini models through Google's enterprise agent platform, Citi Sky combines real-time voice, video, and multilingual capabilities into a single experience. But what makes it interesting is how it moves beyond reacting to questions. The system can anticipate needs, surface insights, and even guide advisors by identifying which clients may require attention during market events. In Joe's words, it becomes a teammate, one that can scale expertise across hundreds of clients while maintaining a sense of personalization. There is also a broader implication here for the industry. Wealth management has long relied on relationships built over time, supported by human intuition and experience. Citi is not replacing that model, but it is extending it. Advisors are still central, yet their reach is amplified by AI that handles routine interactions, summarizes conversations, and provides context before the next client meeting even begins. Of course, this raises familiar questions around trust, governance, and the role of AI in financial decision-making. Citi is clearly aware of that tension, emphasizing secure data foundations, regulatory compliance, and the importance of embedding its Chief Investment Office's institutional knowledge directly into the system. This is not positioned as a generic AI assistant, but as a reflection of Citi's own expertise, delivered through a new interface. What I found most compelling, though, was how both Joe and Karolina kept returning to the human side of the story. Yes, this is about agentic AI and advanced models. Still, it is also about reducing friction, improving access, and helping people answer a simple but powerful question: Am I financially okay? As Citi Sky rolls out to Citigold clients in the U.S., it will be fascinating to see how customers respond and how competitors react. If this model gains traction, it could reshape expectations far beyond wealth management and into every corner of financial services. As we move into the next phase of AI-driven client engagement, are we ready to trust a system that listens, understands, and acts on our financial lives in real time, and how much of that responsibility are we willing to share? Useful Links Learn More About Citi Sky, the AI-Powered Member of the Citi Wealth Team. Connect with Joseph V. Bonanno Jr. Connect with Karolina Belwal Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com

Live from The Royal Institution of Great Britain, it's TechStuff! Oz sat down with two visionaries at an event hosted by Quilt.AI. First, he spoke with Ali Eslami, a Distinguished Research Scientist at Google DeepMind, who built the prototype for what is now AI Search. Ali talked about how working on AI can feel like surfing, and what went into connecting Gemini to Google Search to create what he called "neural Google." After that, Oz chats with Saad Mohseni about his work with MOBY Group. Saad guides Oz through his twenty-year effort to bring top-tier news and entertainment to Afghanistan and beyond — from a reality TV singing competition that changed the country, to using WhatsApp and AI to provide education to girls banned from school. Additional Reading: Radio Free Afghanistan – HarperCollins EXCLUSIVE NordVPN Deal ➼ https://nordvpn.com/techstuff Try it risk-free now with a 30-day money-back guarantee See omnystudio.com/listener for privacy information.