The Most Interesting Thing in AI

Jaksot

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  The Future of Economic Power - Circle’s Jeremy Allaire with Nicholas Thompson 16.09.2026 1t 9min

  Technological waves often arrive with a promise. The internet was going to democratize information. Blockchain was going to decentralize power. Now, AI's boosters say it will bring unprecedented prosperity. Few people are better positioned to speak to that possibility than Jeremy Allaire. As the CEO of the fintech company Circle—issuer of the USDC stablecoin—and a longtime internet entrepreneur, Allaire has been at the center of the first two technological waves. With AI, he says we’re going through a change that’s “bigger than the Industrial Revolution.” He sees a future of financially-empowered agents—and believes this technology could be the one that finally fulfills the promise of shared wealth.  In a conversation with Nicholas Thompson, CEO of The Atlantic, Allaire describes how the agentic economy might work, why regulation will be critical to its success, and what’s missing from the conversation around AI’s effect on society. Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC. (00:00) Introduction (03:33) Jeremy’s early fascination with open networks (07:14) Creating the first online archive of Noam Chomsky's work  (10:54) The promise of the early web (17:00) How the internet centralized power through social media giants (22:53) Founding Circle with the vision of creating "HTTP for money" (31:18) Navigating crypto's reputation challenges (38:18) Why Jeremy wrote The Agentic Economy Treatise (43:30) How AI agents could change the fundamental structure of companies (53:34) The risks of extreme capital concentration with AI (59:40) The choice we face with AI regulation (1:05:03) What Jeremy would do if he had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  The Race to Superintelligence - Richard Socher with Nicholas Thompson 09.09.2026 1t 8min

  As AI’s capabilities improve, reports of “rogue” agents and misaligned systems are becoming more frequent. In response, some activists, academics, and politicians have called for a pause in development, warning of the dangers that superintelligent AI could pose. But Richard Socher, the CEO of AI startup Recursive as well as the AI search engine You.com, sees another path. In his new book, The Eureka Machine, Socher lays out his vision for how self-improving AI could lead to breakthroughs in science, medicine, economics, and more. In conversation with Nicholas Thompson, CEO of The Atlantic, he details some of the ways we can mitigate its risks, explains why the limits of our own minds could hold AI back, and considers whether we’re projecting too many fears about human behavior onto an insensate technology. Produced independently of The Atlantic’s editorial staff. (00:00) Introduction (02:25) Richard's childhood in East Germany and Ethiopia (10:23) What Richard got wrong about AI hype and the DeepMind acquisition (12:14) The idea behind The Eureka Machine (17:18) How AIs can compete to make each other safer (20:30) Are fears about synthetic data overblown? (22:32) When hallucinations are actually helpful (28:16) How human intelligence could hold AI back (34:52) The metacognition tension (39:13) The OpenAI-Hugging Face hack (46:15) Would narrower AI goals have put us in a better spot? (50:30) Richard’s debate with Yoshua Bengio: are we building a dominant species? (54:29) What breakthrough will finally win over AI skeptics? (59:26) The case for widely available superintelligence (1:04:20) What Richard would do if he had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  How to Get Hired in the AI Era - Clara Shih with Nicholas Thompson 02.09.2026 50min

  For years, tech CEOs have promised that AI will take on the menial, repetitive tasks that have long been a part of office life. Typically, those tasks are assigned to younger, less experienced workers—and poll after poll shows Gen Z is increasingly concerned about what AI will mean for their job prospects. Clara Shih says those fears are, at least partly, justified. As the former head of Meta's Business AI Group, and the CEO of Salesforce AI before that, Shih knows firsthand how companies are deploying AI and where it's affecting hiring. Now, as the founder of the New Work Foundation, Shih is building tools to help young workers navigate this complex hiring maze. In conversation with Nicholas Thompson, CEO of The Atlantic, Shih details the skills students should focus on to prepare for the AI era, how employees can leverage the technology, and why more people—of all ages—might soon find themselves working for an algorithm. Produced independently of The Atlantic’s editorial staff. (0:00) Introduction (02:35) What New Work Foundation is doing for Gen Z job seekers (04:00) Is your major cooked? Testing the "Field Report" tool (06:50) What AI exposure scores don’t capture (10:20) How colleges should prepare students for the AI era (17:30) Why beginners shouldn't use AI to learn something new (22:00) Is college still worth it? (23:42) Why applying for a job is harder than it used to be (29:52) AI will make big companies more efficient—and less fun  (33:12) How the bitter lesson could apply to entire organizations (36:12) The three buckets all white-collar work might soon fall into (42:51) Are companies actually laying people off because of AI? (47:54) What Clara would do if she had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  Kara Swisher on What Silicon Valley Is Getting Right—and Wrong—in AI 26.08.2026 49min

  Kara Swisher has done a bit of everything. She’s covered the rise of Silicon Valley’s tech giants, founded and sold her own startup publication, and dabbled in Hollywood, with appearances in films such as The Devil Wears Prada 2 and Tron: Ares.  She’s now the host of multiple podcasts about tech and politics, as well as Kara Swisher Wants To Live Forever, a CNN series about the longevity industry. After decades of chronicling the Valley’s foibles, Swisher has many thoughts on AI—where the technology currently is and where it’s going. In conversation with Nicholas Thompson, CEO of The Atlantic, Swisher goes deep on whether the Big Tech companies are capable of managing AI responsibly; if the technology will deliver on the hype they’ve generated; and how media companies and creators can best leverage it.  Recorded in Bar Harbor, Maine. Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC. (00:00) Introduction (02:25) What Kara’s most excited about with AI (08:50) What the political backlash against data centers shows (11:15) Are we repeating the dot-com bubble with massive AI spending? (13:45) OpenAI's self-inflicted wounds (16:40) What the US should do about open-source AI (19:15) Will AI-driven social algorithms push politics toward the center? (21:25) Why young people are turning on Big Tech (25:10) How AI is reshaping the relationship between creators and media institutions (28:35) Will AI make trusted media brands more valuable? (37:30) How media business models should adapt in the age of AI (45:35) What Kara would do if she had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  How AI Could Upend Global Politics - Ian Bremmer with Nicholas Thompson 19.08.2026 1t 4min

  AI may have leveled the playing field in coding and app development, but it’s also put potentially dangerous tools in reach of nefarious actors. Now, empowered by AI, state-backed intelligence agencies and non-state actors alike can access tools that enable everything from mass surveillance to cyberattacks to bioweapon development. This dynamic could lead to a catastrophe, warns Eurasia Group’s Ian Bremmer. In conversation with Nicholas Thompson, CEO of The Atlantic, Bremmer describes the risks of open-source AI, the opportunities for international collaboration (including an “AI stability board”), and how to increase investment in safety and alignment. Will AI cause socially-destabilizing inequality? What are the chances it helps democracy rather than hurt it? And how concerned should we be about AI companions?  Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC. (00:00) Introduction (02:04) Why cyberattacks aren’t the primary threat of AI (05:58) What we should (and shouldn't) take away from the Mythos incident (08:53) How AI could enable the creation of bioweapons within a year (13:32) The surveillance trilemma: balancing existential risk mitigation, privacy rights, and open-source freedom  (16:11) Could a FINRA-style global AI stability board enforce safety standards? (19:54) Why market dynamics alone cannot ensure AI safety (23:14) Could a US-China bilateral agreement be enough to address governance?  (29:51) Does AI solve social media’s polarization issue? (34:13) Will AI-driven inequality threaten democratic foundations? (40:31) The vertical vs. horizontal race: can civil society and nonprofits build ethical guardrails fast enough to catch up?  (45:21) China’s AI strategy: prioritizing industrial robotics and defense (49:19) What role will Europe play in the AI era? (52:10) The emerging anti-AI backlash: a new wave of economic populism driven by displaced white-collar professionals  (56:42) Career advice for the AI era (58:17) How AI impacts consultancies like the Eurasia Group (01:00:00) What Ian would do if he had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  Writing in the Age of AI - Gemini Notebook’s Steven Johnson with Nicholas Thompson 12.08.2026 1t 2min

  Steven Johnson spent decades figuring out the best ways to turn his research into words on the page. Now, he’s adapting those methods for Gemini Notebook, Google’s AI-powered interactive bibliography. (Until recently, it was called NotebookLM.) But in building a tool designed to synthesize ideas, is there a risk of taking humans too far out of the writing process? In conversation with The Atlantic’s Nicholas Thompson, Johnson discusses the best practices, ethics, and limitations of using AI as a collaborator. The Atlantic has a licensing agreement with Gemini Notebook, and Google also advertises with The Atlantic. This episode was not a part of those deals. Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC. (00:00) Introduction (05:10) The evolution of Steven's writing process  (08:22) Managing the "iceberg" of research (11:45) The ethics of AI-assisted writing (19:02) What happens when AI becomes as good at writing as humans (24:17) Why some genres could change drastically with AI (29:10) How AI might undo polarization  (34:45) Designing educational guardrails for AI (44:26) What will AI do to writing styles? (49:10) Licensing author personas and protecting creators (56:52) A rule of thumb for how to use AI  (58:00) What Steven would do if he had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  Meta's Plan to Win in AI - Andrew Bosworth with Nicholas Thompson 08.07.2026 50min

  However you feel about Meta, Andrew Bosworth has likely played a part in it. The long-serving right hand to Mark Zuckerberg and current Chief Technology Officer, “Boz” has helped shape almost every stage of the company’s growth. He’s credited with introducing the Facebook News Feed in 2006, and, more recently, with overseeing the company’s efforts in the metaverse. Now, Boz is a key figure behind Meta's artificial intelligence strategy. In late June, he joined Nicholas Thompson, CEO of The Atlantic, for a conversation covering the state of Meta AI: from the privacy concerns around its glasses to its controversial (and now halted) program training models on its employees’ keystrokes and mouse movements to its pivot from open-source AI to a proprietary model. (00:00) Introduction (02:34) Can AI glasses get past the developer ecosystem Catch-22? (05:45) What’s true and false about NameTag, facial recognition, and Meta’s glasses  (09:22) Why Meta tracked employee keystrokes to teach AI how to use computers—and why it stopped (12:20) The legal complications of tracking employee data  (15:58) Why unique professional workflows are more valuable than generic internet text  (18:15) Boz’s vision for AI: a tool to maximize individual human potential, not replace workers  (21:15) How AI produces faster coding but slower thinking, leading to "well-executed bad products"  (24:10) If AI doubles a worker's productivity, do companies hire fewer people or double the team size?  (28:38) Why Boz is optimistic about life "under the algorithm" (32:08) Meta’s pivot from open source (Llama) to closed models (Muse Spark) (37:25) How long will scaling laws hold? (40:26) Where Meta already excels in AI (46:27) Why energy production is the upstream constraint for the future of AI Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  AI’s Threat to Privacy — Signal’s Meredith Whittaker with Nicholas Thompson 01.07.2026 51min

  AI agents can scour the internet for us, reply to our messages, and add events to our calendars. But in order to do so, they need sweeping access to our data. Handing that over presents an unprecedented threat to privacy, says Signal Foundation president Meredith Whittaker, who directs the Signal messaging app. In conversation with The Atlantic CEO Nicholas Thompson, Whittaker discusses the risks of agentic AI, Signal’s approach to AI coding, and why it’s uncompromising in its commitment to protecting user data.  This episode was recorded prior to Keir Starmer’s resignation announcement. (00:00) Introduction (02:52) AI’s threat to privacy (03:28) The end of the operating system as a safe boundary (04:15) The dangers of off-device compute and the limits of Apple’s privacy promises (05:30) Prompt injection vulnerabilities, and the risks of giving agents access to calendars, contacts, messages (06:50) How Signal mitigates the risk of AI software like Microsoft Recall (09:15) The accessibility trade-off: Why protecting privacy (at this moment) comes at the cost of screen readers for blind/low-vision users (12:20) Are AI agents the new root users? (15:28) The problem of proprietary OS providers (17:40) Why don’t consumers care about privacy? (19:35) Can a focus on enterprise customers fix AI’s privacy problems? (23:30) How government surveillance can undermine private industry privacy efforts (28:13) How Signal worked with Apple to fix the iOS notification exploit (30:50) Meredith Whittaker’s critiques of the UK government’s content-scanning proposal (36:20) The risks of compromising on privacy (42:30) Would Signal take a different approach to privacy if it were the world's largest messenger app? (45:36) What would you do with unlimited funding? Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  Will AI Agents Kill Social Media–Or Save It? Eli Pariser with Nicholas Thompson 24.06.2026 44min

  Take a scroll through Facebook or TikTok today, and you’ll likely find some AI-generated content: an influencer with impossibly-radiant skin, a stunt that bends the laws of physics, Shrimp Jesus. And while there might not be much social benefit to AI slop, that doesn’t mean that we should shun AI from our feeds entirely, says Eli Pariser. As the author of “The Filter Bubble,” Pariser has been a longtime critic of social media. But he’s also the cofounder of Upworthy, the bubbly bright news site that perfected the clickbait headline. Today, Pariser is building Roundabout, a kind of socially-conscious answer to Nextdoor, and he’s hopeful that AI agents can mend the thumb-shaped hole in our social fabric. But is more tech really the answer to our tech woes? Nicholas Thompson, CEO of The Atlantic, sits down with Eli to find out. (00:00) Introduction (02:00) How we can avoid social media's worst mistakes (03:36) Would subscription models have fixed social media? (05:03) How the agentic interface will change news consumption (07:19) If AI replaces social media, where is the new digital town square? (09:29) Nextdoor, engagement, and online utility (11:42) Agents replace utilitarian uses; humans stay in trusted spaces (13:37) The future of group chats: custom micro-platforms with add-on features (21:30) Can a social network built around community stewards and offline events thrive? The case for Roundabout (27:26) Upworthy grew fast but VC pressure drove it to clickbait (33:45) AI agents = filter bubbles on steroids with deep personalization (39:45) Fund external AI governance structures rather than internal alignment Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  How AI Agents Are Changing Business - PwC’s Dan Priest with Nicholas Thompson 17.06.2026 31min

  You've probably heard it already: AI is going to radically change the way we work. But the details change depending on who's making the prediction: AI will wipe out the C-suite, or entry-level jobs, or make us all into prompt engineers. Those scenarios are far-fetched, says Dan Priest. In his role as the Chief AI Officer at PwC, Priest sees firsthand how companies across the industrial landscape are utilizing AI– often in ways that clash with those  fatalistic prognostications. In a vital conversation with Nicholas Thompson, CEO of The Atlantic, Priest unpacks what he's learned about AI implementation, agents, and how businesses can adapt in the age of AI. (00:00) Introduction (02:30) The two extremes of AI adoption (04:46) Will we see a billion-dollar one-person company? (06:24) Why technology advances faster than implementation  (07:32) Where is AI actually being deployed? From IT/code generation to CFO/CHRO functions (10:17) Specialist vs. generalist roles in an AI world  (12:17) Should every employee have their own agent?  (14:39) Agent performance limits: Task length, concentration windows, and why multi-model checks and balances matter (18:11) Who gains most from AI: top performers or early career workers? (21:37) Agentic applications  (26:12) The hourglass organization: Replacing pyramid and diamond models with expanded entry points plus leadership, compressing middle management Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  How AI Is Changing Code - Paul Ford with Nicholas Thompson 10.06.2026 50min

  In the last year, AI has arguably made more progress in coding than in any other domain. Its technical capabilities – harnessed through apps like Codex and Claude Code – have changed the way engineers work. Boris Cherny, Anthropic’s head of Claude Code, claims that 100% of his output is now generated by AI. But what does the rapid advance in coding tools mean for engineers and businesses? To answer that, Nicholas Thompson, CEO of The Atlantic, sits down with engineer, author, and entrepreneur Paul Ford. The two discuss how AI has changed his work, its implications for a range of industries, and their missed opportunity to start a billion-dollar business (maybe). (00:00) Introduction (01:53) Writing vs. Engineering: Which profession has been transformed more by AI? (03:23) The pitfalls of AI writing and the limits of AI agents (04:09) How AI has changed the code development business model (09:01) "Vibe coding": Paul Ford's personal experience building products through AI prompts (10:47) "Death is coming" - The feeling of watching entire industries dissolve (12:54) Where consensus programming thrives under AI assistance, and where it struggles (15:18) Why making good software remains difficult despite faster code generation (17:05) The restaurant review problem: The experiential engineering tasks that AI can't replicate (21:33) Can you ship AI code without a human reviewing it? (23:01) Will AI become self-recursive? How code runs, finds bugs, and self-corrects through iteration (26:58) Engineers can produce 50x more code than before. What does that mean for PMs and design teams? (29:46) Velocity vs. quality: Can AI genuinely upskill mid-level talent or just increase output speed? (35:32) Should you teach your kids to code? (38:36) What we learned from not building Grammarly (42:04) Beyond agents: Incremental improvements and classic software-in-the-loop hybrid approaches Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  How Science Can Fix Dishonest AI - Yoshua Bengio with Nicholas Thompson 03.06.2026 50min

  In the years following the launch of ChatGPT, as concerns spread over the social and political impacts of LLMs, one person’s warnings seemed particularly dire: Yoshua Bengio’s, a scientist  and one of the “godfathers” of AI. The potential negative impacts of his life’s work weighed so heavily on Bengio that he signed his name to an open letter advocating for a pause in AI research. (The pause didn’t happen.) But recently, Bengio has found renewed optimism as he pursues a project dubbed “Scientist AI.” The pitch: What if AI didn’t care about pleasing us, and instead, like a scientist, prioritized accuracy, honesty, and probable outcomes? In a conversation with Nicholas Thompson, CEO of The Atlantic, Bengio outlines why he thinks this approach will produce better outcomes, the challenges to implementing a model that polices other (often better-funded) models, and why the age of AI– so far marked by an international arms race– will need greater international cooperation. (00:00) Introduction (05:00) Can we understand what's happening inside neural network vectors and attention systems? (07:00) How ChatGPT changed Bengio’s risk assessment  (09:37) The case for optimism (at least when it comes to technical solutions)  (12:30) The alignment problem: AI self-preservation drives and hidden agendas emerging (14:26) Can we train AIS to understand the world without changing it? Introducing Scientist AI (15:52) Using Scientist AI as a guardrail to evaluate risks of actions from other AIs (19:37) Sycophancy problem: current AIs pleasing users leads to harmful psychological effects (22:20) The difference between Scientist AI and current value-aligned systems (Anthropic, OpenAI) (24:06) Will AI capabilities slow down or continue accelerating beyond human intelligence? (29:58) US-China AI race: mutual risk requiring coordination like nuclear deterrence (31:57) UN AI advisory group with Maria Ressa: synthesizing science independently of politics (33:18) Sovereign AI for middle powers: partnering to avoid domination by US/China (37:54) Bengio's regret about not speaking up on AI risks earlier in his career (40:12) How liability insurance and regulatory incentives could make safety commercially viable (42:42) Why Europe lags in AI: capital markets and risk culture, not just regulation (46:43) Energy consumption from AI growth and impact on fossil fuel demand Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  The AI Jobs Disruption - Erik Brynjolfsson with Nicholas Thompson 27.05.2026 1t 2min

  Of all the potential risks and promises of AI, perhaps none are as immediately dire as this: How will it impact jobs? Will employers still need workers? What will it mean if the answer is “no?” Depending on who you’re talking to, the prospect of a future with fewer jobs is either liberating or terrifying. But for a more measured reaction, it helps to look at the data. Stanford economist Erik Bynjolfsson has done just that, drilling down into AI’s effects on employment, upskilling, output, and more. In a conversation with The Atlantic’s CEO Nichlas Thompson, Brynjolfsson goes through his studies of call centers and other AI-exposed fields, and the surprising findings that could bring some much-needed reality to our fears. (00:00) Introduction to Erik Brynjolfsson and his work on AI economics  (02:51) How much is free AI actually worth?  (05:25) Why isn’t powerful AI showing up in GDP?  (06:48) Introducing GDP-B: A new metric to capture value from free digital goods  (07:23) Why initial AI adoption often lowers output  (09:05) Evidence of the J-curve turning: Call centers, software, and aggregate stats  (14:48) Will AI create more jobs or destroy them? Understanding elastic vs. inelastic demand (19:36) Advice for students and workers: Focus on creating new value, not just efficiency  (21:34) Why AI helps different skill levels differently in call centers vs. coding  (25:47) The "Turing Trap": Why mimicking humans leads to substitution rather than augmentation (30:50) Four policy recommendations: Better metrics, dynamic labor markets, and human-AI complementarity  (37:52) "Canaries in the Coal Mine": Data showing early job displacement in AI-exposed fields  (47:08) How higher labor costs drive automation adoption (52:53) Fair compensation for creators: Designing incentives for the AI-content ecosystem  (59:03) The urgent need to study the transition, not just the technology Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  The Limits of Predictive AI - Carissa Véliz with Nicholas Thompson 20.05.2026 48min

  Can AI predict a person’s future? It’s a promise often made by sales teams, but the technology’s record is far from spotless. Even if it did achieve perfect foresight, a practically-clairvoyant AI might be incompatible with democracy, says Oxford philosopher Carissa Véliz. In a spirited conversation with Nicholas Thompson, CEO of The Atlantic, Véliz traces the history of predictions from ancient oracles to the modern algorithms shaping everything from criminal sentencing to insurance premiums. What are the ethics of outsourcing such consequential decisions to machines? The risks of getting it wrong are obvious. Véliz warns of the dangers of getting it right. (00:00) Introduction to Carissa Véliz and her work on privacy and AI  (01:29) Why "less crime" is an illusion of safety  (02:30) How surveillance machinery enables prediction and social control  (03:06) Defense of autonomy: why resisting surveillance protects freedom  (04:02) Can mass surveillance ever be beneficial? (05:36) Ring cameras and the erosion of democratic anonymity  (07:01) Prediction versus prophecy: how forecasts shape reality  (08:52) Job displacement predictions and self-fulfilling prophecies  (13:15) The Gettier problem: why probabilistic AI lacks justification  (16:06) When probabilistic AI works and when it fails  (18:52) Do individualized health predictions defeat the purpose of insurance? (25:24) Areas where probabilistic reasoning is inadequate: insurance, justice  (27:48) The problems of effective altruism and utilitarian calculation  (32:37) AI company ethics: copyright, rights, and virtue ethics  (37:47) Can more data solve "the turkey problem?"  (39:15) Practical privacy advice: Signal, Proton, VPN, and mindful choices Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  AI Utopia or Catastrophe? Nick Bostrom with Nicholas Thompson 13.05.2026 48min

  Will AI destroy the world, or transform it into one of abundance? Across two books and several papers, philosopher Nick Bostrom has envisioned a range of AI futures. He joins Nicholas Thompson to discuss the ethics of how we treat AI, whether AI has sentience, and why he believes we should keep building, even at the risk of annihilation.  Produced in collaboration with PwC. (00:00) Introduction to Nick Bostrom and Superintelligence  (01:56) How AI development matched Bostrom's predictions  (04:48) Recursive self-improvement: Are we there yet?  (07:40) Physical limits of intelligence and computational ceilings  (09:40) Timeline predictions: Next year vs. next five years  (11:46) Embodied intelligence: Can AI replicate motor skills?  (14:32) Centralization vs. democratization of AI power  (16:52) The race dynamics: One leader vs  many competitors (19:57) AI alignment: Making systems behave as intended  (21:37) The gap between model power and our understanding  (23:25) "Optimal Timing for Superintelligence" paper explained  (28:14) Swift to harbor, slow to berth: When to pause AI development  (35:20) Moral status of digital minds and sentience  (41:23) Building trust with potentially misaligned AI  (44:11) Where to invest unlimited AI research funding  (47:07) Closing: Should we say please and thank you to AI? Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  The Case for Open-Source AI - with Nicholas Thompson and Raffi Krikorian 06.05.2026 54min

  Why does AI answer the way it does? Even as models cite their sources, the question of “why” remains one of the most confounding in the industry, with huge implications for users and builders alike. Mozilla CTO Raffi Krikorian says much of the answer lies in open-source AI— letting users look under the hood to see what’s happening. It’s a compelling idea, one that could also impact safety and alignment. But can it thrive? And what are the risks of ceding control? In a deep conversation with Atlantic CEO Nicholas Thompson, Raffi describes a world where technology is liberated from a handful of corporations, shares his hopes and fears for AI, and reflects on his recent car crash involving a self-driving Tesla. (00:00) Introduction: The mystery of AI decision-making and the need for transparency  (02:25) Twitter, Uber, and the DNC: Raffi’s career history (05:01) How centralization changed Twitter into X (08:30) Why seven companies shouldn't control AGI  (11:38) Mozilla's mission: Building an open AI ecosystem like Firefox did for the web  (14:21) Is it strange that Google funds Firefox? (16:40) The four layers of AI openness: Compute, data, models, and developer tooling (22:20) Data ethics and provenance: Creating markets for ethically-sourced training data  (26:44) What counts as “true” open-source AI? (32:04) The risks of open source AI: Balancing accessibility with safety concerns  (35:56) Should powerful AI be restricted like nuclear weapons?  (39:17) Raffi's Tesla crash and the danger of automated complacency  (46:56) Preserving humanity in the age of AI: Avoiding the "WALL-E" future Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  Sam Altman on Where AI Models Go Next, with Nicholas Thompson 29.04.2026 53min

  OpenAI’s Sam Altman sits for an interview with Nicholas Thompson, CEO of The Atlantic, to discuss AI’s trustworthiness, its dangers, and its impact on young people. Altman also discusses his company’s pledge to “stop competing and start assisting” rival projects that approach AGI, and why he thinks we’re not there yet. In a thorough and wide-ranging conversation, Altman opens up about where he thinks AI will go next and the mysteries that he still can’t solve. Recorded at OpenAI’s offices in San Francisco. (00:00) Introduction (02:33) Is our understanding of AI keeping pace with its growth in power? (05:10) Is chain-of-thought the key to trusting a model? (11:07) Open source AI, cybersecurity, and "infected" agents (16:26) Have we hit recursive self-improvement? (19:18) What does AI do on Sam Altman's computer? (21:15) Why hasn't AI made an impact in business yet? (24:04) Will AI make the wealth gap worse? (27:01) Why do young people hate AI?  (30:23) The challenges of AI sycophancy  (33:36) Do you regret making AI so human-like?  (36:53) Synthetic data and "mad cow disease"  (39:22) The future of publishing and media  (41:54) Do we need neurosymbolic AI?  (43:40) Will you cooperate with Anthropic if they get to AGI first?  (47:42) What is your advice to parents who are anxious for their kids' future?  (49:46) If you had infinite resources, what would you pursue?? Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  Data Centers in Space - with Nicholas Thompson and Ariel Ekblaw 22.04.2026 39min

  AI needs data centers, and those data centers need energy and cooling. Recently, one proposal has captured the popular imagination: put data centers in space, where there’s ample solar energy and naturally cool surroundings. But things aren’t quite that simple, says space architect Ariel Ekblaw of the Aurelia Institute. On this episode of The Most Interesting Thing in AI, Ekblaw talks with The Atlantic CEO Nicholas Thompson about the possibilities for building structures in space, the innovative designs coming out of the Aurelia Institute, and why data centers in space are a good idea… for certain billionaires.  Produced in collaboration with PwC. (00:00) Introduction (02:22) What is a space architect?  (04:45) How does someone become a space architect? (07:39) How do "space Magna-Tiles" work? (11:00) Why build in space? (12:45) Will we have chatbots in space? (15:00) How space will change robotics (16:56) Why would anyone want to live in space?  (19:55) Will we actually go to space soon?  (20:49) Artificial gravity Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  Season 4 Trailer 15.04.2026

  Where does AI go next? And what happens to us? Join The Atlantic’s CEO Nicholas Thompson as he speaks with leaders, developers, philosophers, and more about AI’s impacts, present and future. New episodes every Wednesday, starting April 22.  Produced in collaboration with PwC. Learn more about your ad choices. Visit podcastchoices.com/adchoices
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  The Copyright Wars - with Nicholas Thompson and Bill Gross 26.11.2025 36min

  In this episode, The Atlantic’s CEO Nicholas Thompson speaks with serial entrepreneur and Idealab founder Bill Gross about his latest venture, ProRata, a bold attempt to create a fair exchange of value between AI companies and the creators whose work helped train their models. From inventing search advertising to tackling one of AI’s most urgent ethical challenges, Gross explains how innovation and fair market dynamics can align—and how humans are still underestimating the transformative power of AI. (00:00) Introduction (06:32) How Bill invented paid search in the 1990s (13:29) NYT v. OpenAI as the “lightning strike moment” that inspired ProRata (16:16) Solving the “impossible problem” of AI attribution (21:36) ProRata’s plan for revenue sharing between creators and AI companies (24:13) How YouTube shows revenue sharing could make AI companies even stronger (28:20) When there will be a one-person company with a billion-dollar valuation (29:23) AI could be net positive for the climate in as little as five years (33:01) The most interesting way Bill has used AI recently Learn more about your ad choices. Visit podcastchoices.com/adchoices