GAEA Talks

GAEA Talks

GAEA TALKS explores the transformative power of artificial intelligence. Featuring leading AI experts, industry leaders, professors, data scientists, policymakers, technologists, futurists, ethicists, and pioneers, the podcast dives into the latest AI trends, opportunities, and risks, examining AI’s evolving role in business and society. As AI continues to reshape industries and redefine possibilities, GAEA TALKS delivers deep insights into the challenges and breakthroughs shaping the future. Each episode features candid discussions with thought leaders at the forefront of AI innovation, cove

  1. 1 day ago

    #090 - Human In The Lead, Not Human In The Loop with Cabinet Office's Dr Ravinder Singh

    Forrester technology and innovation forums (Austin, London, New York). Promo code "GAEATECH" for 10% off. Visit https://forrester.com/events/#tech to book your place. This week on GAEA Talks, Graeme Scott sits down with Dr Ravinder Singh, Head of Digital and Systems within the UK Cabinet Office Government Commercial Function, and one of the most authoritative voices in Britain on how governments and enterprises should actually build, adopt and govern AI.Ravinder leads the digital, systems and emerging technology work for one of the most consequential functions in Whitehall, and oversees the Government Commercial College - at over one hundred and six thousand users, the largest learning platform in the country after the Open University. Before his current role he was a Consulting Technical Architect at the Government Digital Service. His path into the civil service came after a private sector career at J.P. Morgan, HSBC, Credit Suisse, Accenture, 3i Infotech and Shell Oil. He holds a PhD from King's College London, arrived in the UK on the Highly Skilled Migrant Programme in 2004, and had already spent years as a civil servant in India, where he built the first Indian-languages word processor across seventeen official languages.Filmed in our new London studio, this is one of the most useful, calm and internationally-informed conversations on AI adoption that GAEA Talks has recorded. Ravinder cuts through the noise with a clarity that only comes from having built systems inside global banks, inside the private sector, inside Whitehall and across two countries. The line at the centre of the episode reframes one of the most misused phrases in the industry. Not human in the loop, but human in the lead. Machine learning has to be taught, guided and trained. Trust is earned iteration by iteration. Intelligence comes later. Everything downstream of that principle changes when you accept it.About Dr Ravinder Singh:Dr Ravinder Singh is Head of Digital and Systems within the UK Cabinet Office Government Commercial Function, where he leads the emerging technology, AI, machine learning, blockchain, IoT and quantum computing programmes and oversees the Government Commercial College with over 106,000 users. He was previously a Consulting Technical Architect at the Government Digital Service. Before joining the civil service he spent his career in global financial services and industry, including senior roles at J.P. Morgan, HSBC, Credit Suisse, Accenture, 3i Infotech and Shell Oil, delivering large-scale digital transformation and complex technology programmes. He holds a PhD from King's College London, arrived in the UK in 2004 on the Highly Skilled Migrant Programme, and previously worked as a civil servant in India, where he built the first Indian-languages word processor across seventeen official languages, holds two software copyrights and received a national award for the Punjabi spellchecking algorithm.The views expressed in this conversation are Dr Singh's own and do not represent the official position of the UK Cabinet Office or His Majesty's Government.

  2. 3 days ago

    #089 - Changing How LLMs Scale - The AI Token Breakthrough with Subquadratic CTO Alex Whedon

    Graeme Scott sits down with Alex Whedon, Co-Founder and CTO of Subquadratic and former Head of Generative AI at Tribe AI, for one of the most first-principles conversations GAEA Talks has recorded. The entire AI industry, Alex argues, is downstream from a single algorithm - the transformer - and its two fundamental flaws are quietly capping what AI can do. He breaks down quadratic compute scaling in plain terms (10x the input, 100x the compute), the memory wall where context can cost more than the model itself, and how Subquadratic's linear-scaling architecture claims to cut compute by up to 1,000x at extreme context lengths without sacrificing quality. Along the way he makes a bracing case that electricity, water, minerals and capital - not clever engineering - are the real limits on AI's growth, that the industry is being far too stingy with tokens, and that efficiency isn't a nice-to-have but an inevitability. In this episode: Why the whole AI space is downstream from one algorithmQuadratic scaling explained simply - 10x the input, 100x the computeThe memory wall, where context can need more memory than the modelWhat "subquadratic" means, and why linear scaling is the unlockA claimed ~1,000x compute reduction at 12 million tokensWhy transformers are the worst fit for data-heavy enterprise workThe real constraints on AI: electricity, water, minerals and capitalWhy we're "too stingy with the tokens"The DeepSeek lesson the incumbents ignoredWhy first to market is rarely best About Alex Whedon: Co-Founder and CTO of Subquadratic, which emerged from stealth in May 2026 with $29M in seed funding and SubQ - described as the first frontier model built on a fully subquadratic Sparse Attention architecture, with a research context window of up to 12 million tokens. Previously Head of Generative AI at Tribe AI, leading 40+ enterprise implementations for companies including Anthropic, New Relic and Mars, and earlier an engineer at Meta and Instagram. GAEA Talks is the enterprise AI podcast for leaders navigating the age of artificial intelligence. New conversations every week.

  3. 6 days ago

    #088 - From Models to Money with JP Morgan Director of AI Davood Shamsi

    This week on GAEA Talks, Graeme Scott sits down with Davood Shamsi, Director of AI at J.P. Morgan Chase, Stanford-trained mathematician, former Apple language model lead, and co-author of the forthcoming O'Reilly book From Models to Money. Filmed in our new London studio, Davood lays out the framework at the heart of his book. He explains why the vast majority of Gen AI pilots fail to produce real ROI, why so many enterprises are quietly hosting "zombie pilots" that nobody wants to kill, and why measuring an efficiency pilot the same way as a strategic bet is one of the biggest mistakes leaders are making right now. He then takes us inside the elegant simplicity of the transformer architecture, explains why data centres are quietly making electricity cheaper for consumers, and walks through the tribal-knowledge shift that will change the value of long-tenured employees inside every large organisation. Topics covered: The three questions every AI pilot must answerThe zombie pilot problem inside large enterprisesEfficiency vs compounding vs strategic bet pilots - and why measurement has to changeThe Amazon Just Walk Out and IBM Watson lessonsPrivacy-first AI - what Apple's approach still teaches every industryThe IPA thesis - why transformers are elegantly simpleWhy data centres are quietly making electricity cheaperThe tribal knowledge shift and the future value of long tenureThe price of anarchy and how AI could close the gap in every organisation

  4. 17 Jul

    #087 - The Silicon Path To Quantum Computing with Quantum Motion CEO James Palles-Dimmock

    This week on GAEA Talks, Graeme Scott sits down with James Palles-Dimmock, CEO of Quantum Motion, Cambridge-trained physicist, and one of the sharpest voices in the world on how quantum computing will actually reach useful scale. Filmed in the new London studio, this is one of the most technically substantive and hype-free conversations on quantum computing GAEA Talks has recorded. James's argument is simple and radical. Quantum computing will not scale by adding qubits one at a time in a university lab. It will scale by riding the only industrial process that can hit millions or billions of units, which is CMOS. That is the bet Quantum Motion is making, backed by over one hundred and sixty million dollars of funding, a deployed machine at the National Quantum Computing Centre and a leading position in DARPA's Quantum Benchmarking Initiative. Topics covered: What a quantum computer actually is (and what it is not)Why silicon spin qubits are the only credible route to million-qubit scaleThe AI and quantum crossover - why quantum is a data generator for AI, not a competitorWhy AI's real limitation is data and world models, not architectureThe Landauer limit and reversible computingSteve Jobs's "bicycle of the mind" and specific vs general AIThe scientific method in one line - "try to make mistakes as quickly as possible"Sovereign AI as resilience, not autarkyThe Quantum Motion roadmap to a utility-scale quantum computer by 2032 to 2033Why the real breakthroughs will come from a fourteen year old in her bedroom, not a warehouse

  5. 15 Jul

    #086 - Why AI Is An Ecosystem Not A Technology with Michael G. Jacobides

    This week on GAEA Talks, Graeme Scott sits down with Professor Michael Jacobides - Sir Donald Gordon Professor of Entrepreneurship and Innovation at London Business School, academic advisor at the BCG Henderson Institute, and one of the most respected minds anywhere on how AI is reshaping the structure of the modern enterprise. Filmed live in our new London studio, this is a masterclass in cutting through the current AI hype. Michael explains why the current wave of Gen AI is built on capital markets expectations rather than business outcomes, why the only people making real money from AI today are the picks and shovels, and why "AI first" is one of the silliest strategic frames in the market. He walks through his white rabbit and EBITDA elephant framework, the difference between productivity gains and value proposition disruption, the Chinese pragmatism versus US "race to become God" divide, and why the historical link between US academia and industry that produced everything from the Ethernet to the transformer paper is now being deliberately torn apart. Topics covered: Why AI needs to be analysed as an ecosystem, not a technologyThe capital markets problem in Gen AI valuationsThe picks and shovels reality - who is actually making money todayGen AI as a mass persuasion technology, not a truth technologyThe white rabbit and EBITDA elephant frameworkWhy value proposition disruption matters more than productivityThe Chinese pragmatism versus US "race to become God" divideWhy the DARPA-to-transformer academic pipeline is under threatTeddy Roosevelt's rule - feet on the ground and eyes on the stars

  6. 12 Jul

    #085 - The Temple of Wisdom and the Fight Against Mediocre AI with Lesley Li

    This week on GAEA Talks, Graeme Scott sits down with Lesley Li - TEDx speaker, three-time Innovate Finance Women in FinTech Powerlist honouree, and CEO of the wealthtech company U Impact. Filmed live in the new London studio, this is one of the most human conversations we have recorded on the show. Lesley grew up in the Drung ethnic minority of southern China, arrived in the UK with almost no English, took her first job as a cleaning girl and went on to earn two Master's degrees from the University of Cambridge and spend more than a decade at J.P. Morgan, Barclays and Mizuho. A sudden collapsed lung in 2024 became the turning point that led her to leave banking and dedicate her work to reigniting the human spark inside a rapidly automating world. In this episode she lays out her Temple of Wisdom framework, explains why productivity will inevitably plateau while innovation is the true differentiator, and argues that friction is a feature not a bug in the age of AI. Topics covered: The Temple of Wisdom - experience, deep thinking, consciousness and the sparkWhy most professionals are still on rubble rather than bricksThe Feel, Think, Act loop for humans in the AI ageSlow reading for faster thinking - Lesley's Intelligent Investor experimentThe neuroplasticity cost of outsourcing thought to LLMsThe smart contrarian framework and the mediocrity trapThe UK's engineering brain drain into financial servicesReciprocal AI - "make AI your bitch, not be the bitch of AI"

  7. 24 Jun

    #084 - The Real Meaning of Sovereign AI - Graeme Scott with Georgie Barrat

    This week on GAEA Talks, the format flips. Graeme Scott, the man who normally asks the questions, is in the hot seat. Guest host Georgie Barrat - one of the UK's leading technology journalists - interviews him on the topic he is most associated with: the real meaning of sovereign AI. Recorded live in the new London studio, this is a long-form, single-topic deep dive. Sovereign AI is one of the most-used and least-understood phrases in modern AI, and Graeme has been making the case for over a year that almost everyone in the public conversation is talking past each other. In this episode he sets out what he believes sovereign AI really means, why the token economy is a trap, why local and private AI is already shipping inside Apple and Google's stack, and why the UK is uniquely positioned to lead the next AI wave. Topics covered: What sovereign AI means to a person, a company, a multinational and a countryThe recent US restriction on a major foundation model and what it taught the industryWhy the token economy is costing the UK more than people realiseThe Apple, Google and AMD hardware play that nobody is talking aboutThe three stakeholders shaping the AI narrative and what each one is incentivised to obscureThe cognitive decline research starting to emerge from heavy LLM useThe three questions every leader should be able to answer about their AI architectureThe worst case and best case scenarios for the average person in the next three yearsWhy the UK's innovation DNA from Stephenson's Rocket to Alan Turing makes this the country's moment

  8. 16 Jun

    #083 - Why Drug Discovery Has To Go To Space with Mass Balance Founder Dr Toby Call

    Why does drug discovery need to go to space? In this week's episode of GAEA Talks, the second of season five and the second filmed in our new London studio, Graeme Scott sits down with Dr Toby Call, founder of Mass Balance, former co-founder of Chronomics, and alumnus of the International Space University. Toby explains why over forty percent of the proteins in the human body have no fixed structure, why this "dark proteome" includes some of the most important targets in cancer and Alzheimer's, and why AlphaFold and the rest of the current AI drug discovery stack cannot model them. He then makes the case for microgravity in orbit as the next great forcing function in biology, places that argument inside the wider story of the second space race, and brings it back down to earth with a clear-eyed view of sovereign AI, edge compute, and where the UK has to position itself over the next twelve to twenty four months. Essential listening for anyone building, funding or regulating the future of AI, life sciences or space. Topics covered: The dark proteome and why current AI hits a brick wall in drug discoveryMicrogravity as the next great forcing function in biologySpace data centres, cosmic ray bit flips and the radiative cooling debateSovereign AI through the lens of a country, a company and an individualThe UK's innovation track record from Stephenson's Rocket to DeepMindThe AGI fear moment and the AI autonomous kill chains already coming out of UkraineDr Toby Call on LinkedIn: https://www.linkedin.com/in/tobycallMass Balance: https://www.massbalance.bioGAEA AI: https://gaealgm.ai

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About

GAEA TALKS explores the transformative power of artificial intelligence. Featuring leading AI experts, industry leaders, professors, data scientists, policymakers, technologists, futurists, ethicists, and pioneers, the podcast dives into the latest AI trends, opportunities, and risks, examining AI’s evolving role in business and society. As AI continues to reshape industries and redefine possibilities, GAEA TALKS delivers deep insights into the challenges and breakthroughs shaping the future. Each episode features candid discussions with thought leaders at the forefront of AI innovation, cove

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  • Creator
    GAEA Talks
  • Years Active
    2025 - 2026
  • Episodes
    90
  • Rating
    Explicit
  • Copyright
    © GAEA Talks
  • Show Website
    GAEA Talks