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All-In Podcast

Cerebras CEO Andrew Feldman and Planet Labs CEO Will Marshall reveal the administrative realities of going public versus the operational status quo, while outlining transformative infrastructure shifts—moving data centers to space as launch costs plummet, and rebuilding silicon architectures for the AI era—that signal a record IPO wave ahead.

20VC with Harry Stebbings

Legora CTO Jacob Lorettson explains how AI tooling has fundamentally shifted engineering bottlenecks from code writing to systems architecture and review, while emphasizing that "taste" and edge-case handling remain critical differentiators as competitors can now replicate surface-level features instantly via "vibe coding."

The Pomp Podcast

Despite Bitcoin crashing 50% from all-time highs, Jordy Visser views this correction as a healthy decoupling from traditional markets and a generational buying opportunity, positioning Bitcoin as the essential infrastructure for an AI agent-dominated future while warning that artificial intelligence will disrupt the S&P 500's safety beyond 2030.

Excess Returns

SpaceX's IPO at a $1.75 trillion valuation with only 4% of shares floating creates unprecedented market structure chaos, as accelerated index inclusion rules force massive price-insensitive buying into a tiny float while extreme valuation multiples (80-100x sales) and Musk's historical tendency to defy fundamentals make price discovery impossible and volatility inevitable.

Cognitive Revolution

Frontier AI labs are converging on recursive self-improvement as their core strategy, with OpenAI targeting 2028 for autonomous AI researchers capable of matching human R&D performance, while privately acknowledging their safety monitoring plans remain inadequate and openly discussing the need for potential coordinated industry slowdowns.

Latent Space

Ahmad Awais reveals how CommandCode.ai fixed DeepSeek v4's 'tool confusion' through deterministic repair logic, enabling the open-source model to outperform Claude Opus 4.7 by eliminating repetitive schema errors that previously caused an average of 56 failed tool calls per session.

Adam Taggart | Thoughtful Money

Portfolio manager Lance Roberts confirms the market correction has technically begun after nine consecutive weeks of gains, but suggests it may manifest as sector rotation from overvalued tech and semiconductors into quality value stocks rather than a broad market collapse, even as strong earnings revisions and economic data continue supporting the bull case.

Stanford Online

The speaker challenges the game industry's outdated assumption that players primarily seek competition, presenting 2024 data showing only 18% of gamers are motivated by competition while 50% seek stress relief and 40% want community. They introduce a framework of nine motivators divided into classic (Fun, Mastery, Competition, Immersion, Meditation, Comfort) and modern (Self-expression, Companionship, Education), arguing that successful games must layer social and creative motivators onto traditional designs to serve contemporary player needs.

Stanford Online

Base 10 CEO Tuhin explains why AI inference is shifting from frontier models to custom post-trained models as companies scale, driven by 70-90% cost savings, latency requirements, and the strategic need to own proprietary data rather than feed it to potential competitors.

Stanford Online

Dan Fu explains how LLM inference serves as the engine converting electricity into intelligence, detailing the lifecycle of requests through modern serving systems and emphasizing that GPU kernel expertise enables full-stack ML innovation.

Andrei Jikh

Major exchanges have rewritten index rules to fast-track $4 trillion worth of mega-IPOs, forcing passive 401(k) funds to automatically buy shares and provide exit liquidity for insiders. This engineered demand supports artificially inflated valuations built on circular accounting tricks and unsustainable AI spending that shows negative returns even in best-case scenarios.

Forbes

Axiom Math CEO Karina Hong explains how their AI mathematician 'Axiom Prover' achieved a perfect score on the Putnam exam and produced eight peer-reviewed research papers in 100 days, while commercializing through high-stakes code verification using synthetic data and self-verification to create a self-improving loop of mathematical reasoning.