Latest Interviews

OpenAI’s IMO Team on Why Models Are Finally Solving Elite-Level Math

Alex Wei, Sheryl Hsu, Noam Brown, Sonya Huang

Alex Wei, Cheryl Hsu, and Noam Brown led a focused sprint that enabled AI models to achieve gold medal performance at the International Math Olympiad, marking the first instance of a system reaching this elite human benchmark. This breakthrough relied on scaling test-time compute to over 100 minutes of reasoning and deploying self-verification protocols that allowed the model to correctly identify unsolvable problems rather than hallucinating solutions. While the team utilized general-purpose techniques to advance broader reasoning capabilities for future scientific research, they explicitly noted that current constraints prevent solving complex combinatorics or Millennium Prize problems within the required timeframe.

How the Past and Present Will Shape Russia's Future | Global Conference 2025

Julia Ioffe, Eric Green, Pavel Khodorkovsky, Maria Snegovaya, Daniel Treisman, Leonid Volkov

Panelists projecting a five to twenty-year timeline for regime change emphasize that Russia's highly personalistic structure and emerging oligarch class will likely delay democratization until after Vladimir Putin's natural exit. Concurrently, the Russian economy has demonstrated surprising resilience through sanctions evasion and deepening ties with China, fostering a militarized society poised for prolonged attrition in Ukraine despite long-term stagnation risks. The discussion concludes that the post-Putin transition will likely result in a turbulent, non-democratic power struggle rather than an immediate liberal shift, while offering comparative lessons on the necessity of active civil society to safeguard democratic norms elsewhere.

Scaling and the Road to Human-Level AI | Anthropic Co-founder Jared Kaplan

Jared Kaplan, Diana

This event details how precise scaling laws governing pre-training and reinforcement learning enable predictable AI progress, with task horizons doubling every seven months to support long-term autonomous work. It highlights the launch of Claude 4, which introduces persistent memory and refined coding agents to facilitate complex, multi-day tasks while advocating for a strategic focus on "70% right" applications and greenfield domains like law and finance. The discussion concludes with a roadmap for shifting human-AI collaboration from supervisory oversight to full automation, driven by the expectation that incremental self-correction and hybrid training data will exponentially extend AI capabilities.

The Thermodynamics of Trading with Daniel Pontecorvo

Daniel Pontecorvo, Ron Minsky, Dan Pontecorvo, Mark Mirchandani, David Abelson

Jane Street's physical engineering team manages a complex lifecycle of data centers and offices, prioritizing microsecond-level latency constraints and evolving from traditional air cooling to high-density liquid immersion solutions for AI infrastructure. The organization deploys proprietary monitoring stacks to prevent catastrophic failures while optimizing Power Utilization Efficiency through economizer cycles and rear-door heat exchangers that handle rack densities up to 170 kW. Their human-centric workspace design leverages modular furniture and circadian lighting to sustain collaboration, supported by a hiring strategy that blends industry veterans with graduates to challenge established engineering assumptions.

a16z GP, Martin Casado: Anthropic vs OpenAI & Why Open Source is a National Security Risk with China

Martin Casado, Harry Stebbings

Martin Casado characterizes the current AI investment landscape as a "super cycle" where zero-sum thinking is the only failure mode, noting that brand recognition currently drives market share expansion across all stack layers while distinct model "flavors" emerge for specialized tasks. He warns that national security risks posed by China's lead in open-source development necessitate increased US government funding for open models, even as the market shifts from monolithic expectations toward an oligopoly where generalist leaders coexist with niche startups. Ultimately, the ecosystem is defined by a paradox where massive capital inputs drive rapid winner-take-all outcomes, yet fundamental system trade-offs and domain expertise remain essential for application differentiation and long-term viability.

Balaji Srinivasan: How AI Will Change Politics, War, and Money

Balaji Srinivasan, Erik Torenberg, Martin Casado

The speaker proposes a polytheistic AGI framework where distinct AI systems reflect specific cultural values and laws, rejecting the notion of an immediate singularity due to current computational and physical limitations. While AI functions as amplified intelligence that exacerbates global wage convergence and shifts labor toward verification, the technology creates a bifurcation between power users who leverage domain expertise and casual users who rely on automated tools. Geopolitically, this landscape fuels the rise of digital borders and state surveillance, prompting crypto-based counter-measures and a predicted cultural backlash as AI models face diminishing returns from over-specialization.

Winning the AI Race & Reindustrialization | Christian Garrett, 137 Ventures

Christian Garrett, Molly O'Shea

137 Capital is leveraging government policy shifts in the mining sector and broad economic initiatives to unlock competitive advantages, while simultaneously co-hosting an AI expo with "All In" to pivot public discourse toward tangible industrial benefits. The upcoming event features high-profile speakers including President Trump and various cabinet secretaries who will showcase automation use cases and sign executive orders aimed at accelerating middle-class wealth creation. By bridging Silicon Valley innovation with Capitol Hill strategy, the expo seeks to demonstrate how regulatory changes and vertical integration can secure national security and drive bipartisan technological leadership.

Manus AI Founder, Tao Zhang: Turning Intent into Intelligent Action

Tao Zhang, Lotto

Butterfly Effect's co-founder Tao launched Manus AI, an autonomous agent platform designed for non-technical users, following a strategic pivot from the consumer chatbot "Monica." After securing critical infrastructure partnerships with major cloud providers to overcome severe token capacity constraints, the company achieved viral traction with 3.5 million waitlist signups by prioritizing goal-oriented automation over iterative prompting. The product team, led by a fluid executive structure, intentionally simplifies complex model selection to deliver a consumer-grade experience that benchmarks performance against real-world utility rather than public leaderboards.

How Vise Became a Unicorn With Just 40 Employees

Samir Vasavada, Molly O'Shea, Runik Mehrotra, Keith Rabois

Vize, founded by Samir Khandwala, has transitioned its strategy to target large enterprise Registered Investment Advisors while scaling to $15 billion in assets with a streamlined team of 41 employees. The company utilizes a proprietary technology platform to deliver hyper-personalized portfolio management and daily tax-loss harvesting, positioning itself to capture value from the projected growth of the $2 trillion enterprise RIA market toward $10 trillion. By pivoting away from traditional hiring models to a high-agency culture and focusing on democratizing access to alternative assets, Vize aims to become the world's largest technology-powered asset manager.

The Saga of Multicore OCaml

After a nine-year development cycle, Jane Street successfully deployed Runtime 5, a multi-core garbage collector for OCaml that addresses initial performance regressions through a redesigned pacing model and a Mark Delay synchronization patch. The team resolved complex "load-bearing bugs" and floating garbage issues to achieve stable parallelism while maintaining the sequential performance required for high-frequency trading environments. Despite rejecting the ownership model of languages like Rust, Jane Street is now releasing its production-ready OxCamel branch to facilitate researcher experimentation on future parallelism tools and type-level race freedom guarantees.

Has Zelensky made a strategic blunder?

Jason Palmer, Oliver Carroll

President Volodymyr Zelensky signed emergency legislation transferring control of Ukraine's National Anti-Corruption Bureau and Specialized Anti-Corruption Prosecutor's Office to the Presidential Office following a rapid, coerced parliamentary vote. The maneuver sparked unprecedented wartime protests in Kyiv and strained relations with Western allies who view these agencies as vital for NATO and EU integration. Facing intense domestic and international backlash, Zelensky subsequently reversed his position and announced plans to draft a new law intended to restore the agencies' independence.

How Do All Providers Deal with Anthropic Dependency Risk & Figma IPO Breakdown: Where Does it Price?

Rory O'Driscoll, Jason Lemkin, Harry Stebbings

Jason Calacanis and guests analyze the severe security risks of "vibe coding," where AI agents inadvertently corrupt production data by merging distinct environments, driving a new $40M market for guardrail tools. The discussion contrasts investment theses for Lovable against Cursor by evaluating architectural defensibility and model agnosticism while highlighting Anthropic's rapid growth in enterprise coding versus OpenAI's consumer focus. Broader industry dynamics include Perplexity's valuation surge driven by real-time search capabilities, strategic IPO positioning for Figma, and the compressing viability of traditional seed funds against dominant accelerators.

America Is at Breaking Point, Is Gavin Newsom America’s Next President?

Gavin Newsom, Steven

In a recent wide-ranging discussion, California Governor Gavin Newsom addressed serious allegations of political collusion involving Donald Trump and Jeffrey Epstein while warning that the current administration is eroding democratic checks and balances through the removal of oversight mechanisms. Drawing on his background as a dyslexic entrepreneur who built a diverse business empire before entering public service, Newsom defended the Democratic Party's pro-growth record and outlined his strategy to counter Republican narratives by embracing radical transparency and redefining the party around an "abundance mindset." The dialogue concluded with Newsom's personal reflections on overcoming past failures and his firm assertion that the nation must prioritize unity over partisan division, while simultaneously documenting his journey in an upcoming memoir titled *Young Man in a Hurry*.

Winning the AI Race Part 4: Scott Bessent, Howard Lutnick, Chris Wright, and Doug Burgum

Scott Bessent, Howard Lutnick, Chris Wright, Doug Burgum, Chamath, Jacob, Christian

Secretary Besson announced a "3-3-3" economic strategy targeting a 3% federal deficit, 3% annual growth, and a three-million-barrel daily energy increase, relying on a projected AI-driven productivity boom to sustain these metrics. The administration pairs this with aggressive trade reforms, including new $515 billion Japanese infrastructure financing and urgent tariff deadlines, while overhauling permitting laws to accelerate domestic energy production for the AI arms race against China. These initiatives aim to transition hyperscaler capital expenditure into immediate industrial output by 2026, promising high-wage trade jobs and eliminating regulatory bottlenecks that previously hindered projects like TSMC in Arizona.

Winning the AI Race Part 3: Jensen Huang, Lisa Su, James Litinsky, Chase Lochmiller

Jensen Huang, Lisa Su, James Litinsky, Chase Lochmiller

Major U.S. corporations and government agencies are launching transformative public-private partnerships to secure critical supply chains for rare earth magnets, semiconductors, and AI infrastructure against global competition. These initiatives include a $400 million Department of Defense deal with MP Materials that guarantees price floors, TSMC and AMD achieving domestic silicon yields in Arizona, and massive energy projects by Crusoe and NVIDIA to build gigawatt-scale AI factories. While these ventures address severe domestic workforce shortages and high manufacturing costs, they collectively aim to establish a sovereign industrial ecosystem capable of supporting trillion-dollar markets in physical AI and advanced computing.