Latest Interviews
Showing 871–885 of 9,624 transcripts.
Clear all filters- The Diary Of A CEO1h 58m
Scott Galloway: The Rich Are Quietly Preparing For The AI Collapse
Professor Scott Galloway argues that the United States and the artificial intelligence sector face a simultaneous crisis of reputation driven by perceived government corruption and a narrative shift where AI benefits only the wealthy. He contends that tech leaders employ exaggerated job destruction fears as fundraising tactics while ignoring societal costs, a strategy that risks severe economic disruption if employment falls too sharply too quickly. Ultimately, Galloway predicts an inevitable market correction and advises investors and workers to prioritize resilience, storytelling skills, and disciplined long-term saving rather than chasing speculative valuations.
Inside Clay's Sales Playbook | Becca Lindquist
Clay, Becca Lindquist, Harry Stebbings
Clay Head of Sales Becca Lindquist outlines a high-growth strategy that prioritizes hiring adaptable, data-driven "high-slope" candidates while enforcing a strict compensation model targeting a 7.5x quota-to-OTE ratio. Her approach combines a zero-tolerance policy for stagnation and ego with aggressive AI integration to scale SDR productivity and build a collaborative, winning culture. These methods have enabled the company to achieve $100 million in annual recurring revenue by focusing on deep domain expertise, rigorous forecasting, and performance-based incentives over rigid playbooks.
- The Economist8 min
Are AI models running out of power? | The Economist
Facing severe hardware shortages and monopoly choke points where Nvidia and TSMC dominate supply, major AI developers like OpenAI and Anthropic are throttling services and redirecting resources to manage capacity. In response to these constraints, five cloud providers plan a $700 billion infrastructure build-out while companies grapple with three-to-five-year lead times for essential components and aging chip inventories. This fundamental mismatch between rapid software cycles and slow physical production is projected to reverse declining inference costs, potentially raising prices and slowing overall industry adoption.
- All-In Podcast1h 21m
OpenAI Misses Targets, Codex vs Claude, Elon vs Sam Trial, Big Hyperscaler Beats, Peptide Craze
Elon, Sam, Friedberg, Jason Calacanis, David Sacks, Chamath Palihapitiya
OpenAI faces mounting structural tensions as it misses 2025 revenue and user targets while CEO Sam Altman pushes for an IPO against CFO Sarah Fryer's caution amidst $600 billion in future compute commitments. The company currently maintains a compute advantage over rivals like Anthropic through excess data center capacity, even as the broader AI sector grapples with power grid bottlenecks and a record $725 billion in hyperscaler capital expenditures for 2026. Concurrently, Elon Musk pursues a $150 billion lawsuit alleging a breach of charitable trust following internal documents revealing plans to remove him before the entity's conversion to for-profit status.
- The Economist6 min
How high could the oil price go? | The Economist
Zanny Minton Beddoes, Edward Carr, Mathieu, Henry
Global oil markets face a structural crisis where a 14 million barrel-per-day supply deficit has eroded the "sanguine" expectation of a quick peace deal, creating a price disconnect that literature estimates would require $167 to $460 per barrel to correct. With production gains from non-conflicted regions proving negligible, the market is currently absorbing this shortfall through record-fast inventory drawdowns of 8 to 10 million barrels daily, driven by pre-war shipments and sanctions-induced cargo displacement. As critical buffers for jet fuel and diesel approach minimum levels and logistical constraints lengthen trade routes, the only remaining adjustment mechanisms involve further depletion of commercial stocks or active demand destruction in major consuming regions like Asia.
- Sequoia Capital27 min
Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy
Dmitri Dolgov, Konstantine Buhler
Dmitry Dolgov, Waymo's co-founder, outlines a 21-year evolution from DARPA challenges to a sixth-generation autonomous fleet that has achieved 200 million fully autonomous miles and delivered over 20 million rides with a safety profile 13 times superior to human drivers. The company's architecture utilizes a multimodal "Foundation Model" integrating physics reasoning and spatial understanding to power a structured, end-to-end system across 11 cities, now accelerating toward global expansion in London and Tokyo through the newly launched Waymo Origin vehicle. This mission-driven approach bypasses incremental improvements to rapidly scale commercial deployment, treating full autonomy as an existential imperative to eliminate the 13 million annual road fatalities while transitioning the core technology into a primary family transportation tool.
- Goldman Sachs15 min
Riding the AI Wave
The April 30 FOMC meeting revealed a divided Federal Reserve committee that shifted from expectations of a near-term rate cut to a non-committal stance, a position reinforced by the incoming appointment of hawkish member Kevin Warsh. While private sector leverage has decreased since the Great Financial Crisis, concerns regarding public sector debt sustainability and elevated term premiums persist alongside a robust equity rally driven by hyperscalers and artificial intelligence. Investment strategists consequently maintain a bullish but cautious 7/10 allocation to technology, avoiding fixed income while rotating into energy and defense to hedge against potential consumer drawdowns expected in the mid-year "air pocket."
- Y Combinator38 min
Recursion Is The Next Scaling Law In AI
Ankit Gupta, Francois Chaubard
Two 2025 research initiatives, Hierarchical Reasoning Models (HRM) and Tiny Recursive Models (TRM), challenge standard scaling laws by utilizing inference-time recursion to achieve state-of-the-art reasoning with drastically fewer parameters. HRM reaches 27 million parameters using a three-level weighted hierarchy, while the simplified TRM distills the architecture to just 7 million parameters yet achieves 87% accuracy on ARC-Prize benchmarks by treating recurrence as a dynamic latent memory tape. These systems overcome historical RNN limitations through Deep Equilibrium Models and latent recursion, offering a pathway to efficient, deep reasoning that diverges from traditional Chain-of-Thought constraints.
Figure's First Full HQ Tour: From the Lab to the Factory Floor
Brett Adcock, Molly O'Shea, Moritz
Figure AI is a Bay Area-based pure-play manufacturer with a 500-person engineering workforce deploying its flagship Figure 3 humanoid robot, which operates autonomously using the locally running Helix AI policy. The company has achieved record production output at its "Baku" facility while reducing unit costs by 90% compared to previous models, enabling deployments in settings ranging from the White House to BMW automotive assembly lines. Looking ahead, Figure aims to commercialize a lease-based home model and advance toward its "iPhone moment" with the upcoming Figure 4, which targets radical improvements in cost and usability while pursuing physical interaction-based AGI.
- Stanford Online1h 6m
Stanford CS153 Frontier Systems | Anjney Midha from AMP PBC on Frontier Systems
Instructor Anj Pransanjane guides a cohort of roughly 500 in-person and thousands of remote students through a course framing the current AI era as a "great transition" driven by $1.2 trillion in projected compute investments. The curriculum details shifting industry bottlenecks, such as the rising costs of H100 GPUs and the strategic importance of verifiable context, while urging participants to build asymmetric advantages in non-scalable personal niches. Ultimately, the program challenges students to identify the necessary standards and institutions to transform compute from a monopolized resource into a standardized commodity.
- Sequoia Capital28 min
OpenAI's Greg Brockman: Why Human Attention Is the New Bottleneck
OpenAI executives estimate they are 80% toward achieving AGI, a milestone driven by aggressive compute acquisition strategies and architectural innovations that currently enable AI to autonomously engineer software kernels. The organization is pivoting toward an enterprise and consumer model where a single AGI entity handles complex goals, urging startups to leverage agentic coding tools for massive productivity gains while navigating a landscape where human attention has become the primary bottleneck. This shift is underpinned by anticipated scientific breakthroughs in physics and biology, alongside internal reforms designed to manage the risks of autonomous agents within a future where humans oversee teams of AI rather than writing code manually.
- Sequoia Capital32 min
This is AGI: Sequoia AI Ascent 2026 Keynote
Pat Grady, Sonya Huang, Konstantine Buhler
This analysis outlines a $10 trillion market opportunity driven by a paradigm shift from information distribution to autonomous computation, where AI agents are rapidly replacing cognitive labor with agentic systems capable of long-horizon execution. Founders are advised to leverage the "MAD" model—focusing on customer moats, immediate affordance, and bridging the adoption diffusion gap—to capitalize on a timeline that compresses years of work into days. The event further projects that by 2026, the convergence of these technologies will trigger a cognitive industrial revolution, fundamentally redefining human value from task execution to relationship building and strategic oversight.
- Sequoia Capital20 min
Robotics' End Game: Nvidia's Jim Fan
NVIDIA Robotics is transitioning from language-centric VLA models to World Action Models like Dream Zero, which prioritize learning physical laws through video prediction to enable zero-shot generalization. This architectural shift is supported by a new data collection strategy replacing low-efficiency teleoperation with scalable egocentric video and neural simulators, establishing a log-linear scaling law between training hours and dexterity. Looking toward 2040, Jim Phan projects the industry will achieve a "Physical Turing Test," an orchestration "Physical API" for automated fleets, and "Physical Auto-Research" where robots autonomously improve their own designs.
Anthropic Raises $45B but Falls Short on Compute & Thoma Bravo Hand Back Medallia Keys to Creditors
Jason Lemkin, Rory O'Driscoll, Harry Stebbings
The event analyzes a pivotal shift in the AI landscape where market competition is evolving from human-led selection to autonomous AI-agent vendor choices, creating a three-way oligopoly among OpenAI, Anthropic, and Google. Strategic dynamics are further complicated by regulatory friction, such as China blocking Meta's acquisition of Manus, and severe private equity distress driven by the obsolescence of legacy enterprise software. Investors are responding by consolidating venture capital portfolios around massive, infrastructure-focused bets like NVIDIA while liquidating human-centric tools like Figma and Duolingo that face existential risk from agent-driven workflows.
The $10 Trillion Bet on Humanoid Robots | Figure Founder Brett Adcock
Founded by Archer eVTOL creator Brett Adcock, Figure AI pursues the commercialization of general-purpose humanoid robots capable of operating autonomously for extended shifts across diverse industries. Having raised nearly $2 billion with a $39 billion valuation, the company recently terminated an OpenAI partnership to maintain control over its vertically integrated hardware and AI stack, aiming to triple production by May and deploy thousands of units within the year. Despite facing technical hurdles in scaling reliability, Figure projects a market opportunity worth trillions as it transitions from prototype testing to mass commercial deployment in homes and factories.