GAEA Talks

This week on GAEA Talks Live from HumanX, Graeme Scott sits down with Alex Ratner - co-founder and CEO of Snorkel AI, affiliate assistant professor at the Paul G. Allen School of Computer Science at the University of Washington, and one of the most influential voices in the world on data-centric AI.Alex has been working in AI data for fifteen years. He earned his AB in Honors Physics at Harvard, completed his PhD in computer science at Stanford under Christopher Re, and led the open source Snorkel project that came out of his thesis. He co-founded Snorkel AI in 2019 to commercialise that research. Snorkel is now a frontier data lab supporting most of the major frontier AI labs and a growing number of vertical AI companies and enterprises with the data sets, environments and benchmarks that AI is actually trained, evaluated and improved on.In this episode, recorded live at HumanX 2026 in San Francisco, Alex argues that compute, talent and data are the three legs of the AI stool, and that data is the leg most people still underestimate. He explains why the more powerful and black-boxed models become, the more upstream data and context problems get hidden behind layers of abstraction. He walks Graeme through how pre-training, post-training and reinforcement learning are all really just stages of giving a model the right context. He shares why every enterprise will run their own data-centric loop in the next few years, why benchmarks are getting "benchmaxed" before they are useful, and why Snorkel has just committed three million dollars in Open Benchmarks Grants to fund the academic and open source community building the next generation of evaluation tools.What you'll take away from this conversation:• Why compute, talent and data are the three legs of AI - and why data is the most underestimated of the three• The "data is everyone else's problem" myth - and why it has held the field back for fifteen years• Why the more powerful and black-boxed AI becomes, the more dangerous the upstream data problems hidden underneath get• A working definition of context - from prompt context to pre-training mix to post-training and reinforcement learning• Why generalist and specialist models will coexist - and why your unique data is your specialisation edge• The Liverpool versus Jersey Shore thought experiment - and how subtle data biases shape model behaviour in ways we still cannot fully predict• Why benchmarks are critical, why they keep getting "benchmaxed", and why Snorkel is funding three million dollars of Open Benchmarks Grants for academia and open source• Moravec's paradox - and why we still confuse what is hard for humans with what is hard for AI• The jagged frontier of intelligence - and why understanding where AI fails is now a safety question, not just a capability question• Why coding agents look superhuman on contest problems but still fall down on long, messy, real-world software work• The Feynman plate-spinning anecdote - and why curiosity and "unimportant" problems are still where the breakthroughs come from• The data-centric loop - measure with data, find the gaps, build more data to fill them - and why every enterprise will be running it• Alex's single piece of advice for anyone serious about AI - do not forget the data, do not forget the context

This week on GAEA Talks, Graeme Scott sits down with Jonathan Brill - business futurist, ranked the world's number one futurist by Forbes, called "the world's leading transformation architect" by Harvard Business Review, and the bestselling author of AI and the Octopus Organisation: Building the Superintelligent Firm.Jonathan has spent two decades at the front edge of where technology, strategy and human organisations meet. He was Futurist-in-Residence at Amazon and Global Futurist at HP, where he ran long term strategy for the office of the CTO. He is Head of Invention at Deepinvent and Executive Chairman of the Center for Radical Change, where he has interviewed over a thousand business leaders and surveyed two point seven million managers to understand why some leaders thrive when the world changes and others do not. He is also the author of Rogue Waves: Future-Proof Your Business to Survive and Profit from Radical Change.In this episode, Jonathan argues that the way most enterprises are structured today is fundamentally inappropriate for the world they are now operating in. He explains why the quality of AI output per dollar will improve roughly thirty two times in the next five years, why solo founders are already building one point eight billion dollar businesses on AI vibe coded foundations, and why the US Navy has accidentally become one of the clearest case studies in the world of what real AI-era transformation looks like. He walks Graeme through the four ways of thinking every leader needs to develop, the kill chain to kill web shift driving modern military and business operations, and the central thesis of his new book - that organisations need to stop operating like nineteenth century locomotives and start operating like octopuses, with distributed intelligence pushed all the way out to the edges.What you'll take away from this conversation:• The thirty two times improvement in AI output per dollar coming over the next five years - and what that means for how you operate, hire and compete• The Medvi story - one founder, four hundred million dollars in first-year sales, one point eight billion dollar valuation, and what it proves about scale• How the US Navy went from seven "unleashed" engineers to five hundred, increasing ideation-to-fleet speed ten times in eighteen months• The octopus organisation thesis - why distributed minds beat centralised ones in a non-linear, probabilistic world• The four ways of thinking every leader needs - deductive, inductive, Bayesian and abductive reasoning, and why most organisations are dangerously over-indexed on one• Why most middle management was built for quality assurance, not quality innovation• The kill chain to kill web shift - and why context, not hierarchy, should drive decisions• Why we are building AI in the shape of Google Search when we should be building it in the shape of an inventor• The humanoid robot question - why the human form is probably the wrong shape for almost any specific task• What happens when human labour is twenty percent of your company and your software stack is eighty percent• Why the next billion dollar industries will come from solving problems we could never compute in human heads• The values question - what we actually value, what changes in the next decade, and why that should reshape how organisations are designed• The "agency over fear" message that runs through the whole conversation - and why Jonathan thinks there is more potential right now than at any point in human history

This week on GAEA Talks Live from HumanX, Graeme Scott sits down with Anton Osika - co-founder and CEO of Lovable, the AI app builder that has powered over forty million products in sixteen months, with more than two hundred thousand new products being built on the platform every single day.Anton grew up obsessed with understanding how things work, studied physics, became a CTO of a forty-person AI team, and in 2023 became convinced that large language models would fundamentally change how software was built. He biked over to his future co-founder's apartment, called him from the street, and the two of them started building what would become Lovable. Since launch, Lovable has grown at a rate very few products in software history have matched, and is now used by solo founders, freelancers, product managers inside Microsoft and Uber, and Fortune 500 companies looking to give every one of their employees the ability to go from idea to shipped software.In this episode, recorded live at HumanX 2026 in San Francisco, Anton explains why the build phase is only the beginning, why running software reliably, securely and at scale is the next frontier for AI platforms, and why reading Nick Bostrom ten years ago set him on a path to build tools that could empower the largest possible number of humans.What you'll take away from this conversation:- How Lovable went from idea to forty million products built in sixteen months- The "build phase is only the beginning" realisation - and why lifecycle management is the next great AI platform problem- Why Anton believes software creation is the single highest-leverage capability to democratise- The end-to-end penetration testing layer Lovable now runs before any AI-built app goes live on the internet- Why fortune five hundred adoption is happening faster than anyone expected - and what product managers at Microsoft are actually doing with Lovable- The Grammy-nominated freelancer story - and what it says about the future of small business in America- Why Anton believes this is the best time in history to start a company- The physics-trained instinct for breaking down systems - and how it shapes how Anton builds Lovable- Why empowering non-technical creators is the fastest path to solving more of the world's real problems- What the "messy operations" of shipping production-grade software actually look like- Why culture and team energy are Anton's single biggest focus inside a hyper-growth company- The Nick Bostrom influence that set Anton's ten-year trajectory into AIAbout Anton Osika:Anton Osika is the co-founder and CEO of Lovable, the AI app builder that has enabled more than forty million products to be created by users with no engineering background. Before Lovable, Anton was CTO of an AI company and has spent the last decade building AI products, teams and culture. He holds a background in physics, is one of the most recognised voices in Europe on AI-empowered software creation, and is a leading European tech founder.GAEA Talks is the enterprise AI podcast for leaders navigating the age of artificial intelligence. Subscribe for weekly conversations with the people shaping the future of business, technology and society.Anton Osika on LinkedIn: https://www.linkedin.com/in/antonosikaLovable: https://lovable.devHumanX: https://www.humanx.coGAEA AI: https://gaealgm.ai#AI #ArtificialIntelligence #GAEATalks #GAEATalksLive #HumanX #HumanX2026 #Lovable #AICoding #NoCode #VibeCoding #AIBuilder #AIApps #Founders #EuropeanTech #AIPodcast #GAEAAI

This week on GAEA Talks, Graeme Scott sits down with Mahdi Yahya - co-founder and president of Radiant, founder and former CEO of Ori, and one of the most original founder voices in the world on AI infrastructure, sovereign compute, and the backbone of the AI economy.Mahdi has spent twenty years building companies at the intersection of technology, infrastructure and the arts. He fled Lebanon during the 2006 war at nineteen, arrived in London with no degree, and built his first company in data centre networking. He then enrolled at the Drama Centre London for his BA, founded an experimental arts and technology gallery called Room One that produced theatre and virtual reality work with the National Theatre and Damon Albarn, and partnered with Ericsson on the breakthroughs that helped lay the foundations for edge computing. He spent eight years building Ori into a global AI cloud platform, which earlier this year merged with Brookfield's Radiant in a deal valuing the combined business at one point three billion dollars. Radiant is now the first vertically integrated sovereign AI infrastructure company in the world, backed by Brookfield's ten billion dollar AI Infrastructure Fund, with plans to build and acquire up to one hundred billion dollars of AI infrastructure worldwide.In this episode, Mahdi argues that intelligence is becoming infrastructure - the next civilisational utility after fire, steam, electricity and oil. He explains why every serious country is now treating sovereign AI as critical national infrastructure, why the world is currently spinning up something equivalent to a new supercomputer almost every week, and why the data your AI generates is more valuable, and more dangerous, than the data you feed it. He warns that shadow AI is already inside almost every enterprise, that the unified output of AI risks flattening human individuality, and that agency is the one trait that will distinguish the people who thrive in the AI era from those who do not.What you'll take away from this conversation:• The "intelligence is infrastructure" thesis - why AI joins fire, steam, electricity and oil as the next civilisational utility• Why we are now spinning up a new supercomputer almost every week globally• The Brookfield, Ori and Radiant story - how an eight year founder bet became a one point three billion dollar combined company• The case for sovereign AI - why countries cannot afford to give the keys to their intelligence infrastructure to other nations• Why the data AI generates inside your business is more valuable, and more dangerous, than the data you give it• Shadow AI inside enterprises - and what business leaders should prioritise in the next twelve to eighteen months• Why most existing private cloud and on-prem data centres physically cannot run modern AI workloads• Liquid cooling, power density and gigawatt data centres - the unglamorous reality that will decide which countries can host serious AI• Why the user interface of the digital world is about to shift from screens and apps to a sovereign AI layer in front of everything• The Lebanon to London story, and why drama school turned out to be the best founder training Mahdi could have chosen• The Shakespeare problem - how unified AI output threatens individuality, and why agency becomes the biggest differentiator between humans• Why "observational intelligence" is the next layer the AI stack will need• Why intelligence will become a metered utility, accessed by every person in the world, within our lifetime

This week on GAEA Talks Live from HumanX, Graeme Scott sits down with Dr Ali Agha - co-founder and CEO of Field AI, former NASA JPL principal investigator on two of the most ambitious DARPA robotics challenges in history, and one of the leading researchers in the world on risk-aware autonomy.Ali has spent almost two decades building AI for robots. He started with rescue robots and robotics competitions, met his co-founder at MIT, and went on to work at Qualcomm and then NASA JPL, where for seven to eight years he was a principal investigator on two DARPA grand challenges that the global robotics community treats as a holy grail. He and his co-founder realised that deployable robotics and foundation models had become two separate worlds, and that putting them together was the only path to a robot brain that could generalise across environments while staying safe. That insight became Field AI, now running in production on three continents across humanoid, legged, wheeled, drone and heavy-duty platforms.In this episode, recorded live at HumanX 2026 in San Francisco, Ali explains why data alone cannot produce safe physical AI, why architectural innovation and risk awareness are the non-negotiable second half of the equation, and why his team intentionally decoupled the dynamics of the robot body from the world model.What you'll take away from this conversation:- Why the commoditisation of robot hardware is the hidden unlock behind the physical AI boom- The real difference between conversational AI and physical AI - and why "ninety nine percent" is not good enough for a flying machine- Why Field AI separates world model from embodiment - and how that lets one brain run on tens of different platforms- The belief world model - what it is, why it is probabilistic, and why it is physics-aware- Why end-to-end neural network robotics is a debugging nightmare - and why Field AI refused to take that path- How adding a new robot to a fleet creates "ninety-nine new links" of shared learning, not just one extra unit- Why the risk-aware architecture is the reason Field AI can deploy on live construction sites changing minute to minute- Why edge compute, thermal cameras, lidar and event cameras all matter when the lights go out in an industrial setting- The labour shortage, aging population and climate-driven migration numbers reshaping robotics demand- The real construction job statistic - forty thousand injuries and a thousand deaths per year in the US alone- Why the future of robotics is less "Terminator" and more "capacity multiplier for humans"About Dr Ali Agha:Dr Ali Agha is the co-founder and CEO of Field AI, which builds the world's first field-deployable, general-purpose robot brain. He spent seven to eight years at NASA Jet Propulsion Laboratory (JPL), where he was a principal investigator on two of the most recent DARPA robotics challenges, and previously held research roles at Qualcomm after completing his PhD in electrical and computer engineering. Field AI is now live in production across three continents.GAEA Talks is the enterprise AI podcast for leaders navigating the age of artificial intelligence. Subscribe for weekly conversations with the people shaping the future of business, technology and society.Dr Ali Agha on LinkedIn: https://www.linkedin.com/in/aliaghaField AI: https://fieldai.comHumanX: https://www.humanx.coGAEA AI: https://gaealgm.ai#AI #ArtificialIntelligence #GAEATalks #GAEATalksLive #HumanX #HumanX2026 #PhysicalAI #Robotics #FieldAI #AIRobots #RobotBrain #Autonomy #EdgeAI #WorldModels #Humanoid #NASAJPL #DARPA #AIPodcast #GAEAAI