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預告

Crucible Moments Season 3: Coming October 23

Previously on Crucible Moments, we explored the inflection points that shaped some of the most significant names in technology. Now, we're returning for a brand new season. Join us as leaders from Stripe, Zipline, Palo Alto Networks, Klarna, Supercell and more share what it's actually like to navigate the make-or-break decisions, early stumbles and leaps that turn scrappy startups into market defining forces. Hosted by: Roelof Botha, Sequoia Capital

預告

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3 分鐘
06/11/2025

OpenAI Sora 2 Team: How Generative Video Will Unlock Creativity and World Models

The OpenAI Sora 2 team (Bill Peebles, Thomas Dimson, Rohan Sahai) discuss how they compressed filmmaking from months to days, enabling anyone to create compelling video. Bill, who invented the diffusion transformer that powers Sora and most video generation models, explains how space-time tokens enable object permanence and physics understanding in AI-generated video, and why Sora 2 represents a leap for video. Thomas and Rohan share how they're intentionally designing the Sora product against mindless scrolling, optimizing for creative inspiration, and building the infrastructure for IP holders to participate in a new creator economy. The conversation goes beyond video generation into the team’s vision for world simulators that could one day run scientific experiments, their perspective on co-evolving society alongside technology, and how digital simulations in alternate realities may become the future of knowledge work. Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital

06/11/2025

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1 小時
3月17日

Greetings, Earthlings: Philip Johnston of Starcloud on Data Centers in Space

Philip Johnston, founder and CEO of Starcloud, explains why space will become the primary location for AI compute infrastructure within the next decade. After witnessing SpaceX's massive manufacturing scale at Starbase, Philip realized that declining launch costs would make space-based data centers cheaper than terrestrial ones. He breaks down the physics of heat dissipation in vacuum, the economics of solar power without atmosphere, and why the marginal cost of space infrastructure decreases while Earth-based costs increase. Philip previews a future where close to a trillion dollars per year in CapEx flows to space compute. And, yes, we get his take on aliens. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital.

3月17日

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44 分鐘
1月15日

Harvey CEO Winston Weinberg: Why You Should Reinvent Yourself Every 4 Months

This might be my favorite episode yet. Harvey’s Winston Weinberg is the canonical 2026 hypergrowth CEO. He takes us inside what it's really like to scale from zero to $190M run rate in just a few years. What stands out? His obsessive intensity and willingness to do uncomfortable things on a weekly basis. Winston shares how he cold-messaged thousands of lawyers to land his first customers, why he deliberately chose the hardest enterprise law firms as his first target customers, and how he thinks about hiring and org structure when everything breaks every four months. We also explore his unconventional background - he wasn't a developer, was new to the legal industry, and figured out sales from scratch. It's raw, honest, and incredibly practical for any founder navigating (or hoping to navigate) the chaos of hypergrowth.

1月15日

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57 分鐘
09/07/2024

Microsoft CTO Kevin Scott on How Far Scaling Laws Will Extend

The current LLM era is the result of scaling the size of models in successive waves (and the compute to train them). It is also the result of better-than-Moore’s-Law price vs performance ratios in each new generation of Nvidia GPUs. The largest platform companies are continuing to invest in scaling as the prime driver of AI innovation. Are they right, or will marginal returns level off soon, leaving hyperscalers with too much hardware and too few customer use cases? To find out, we talk to Microsoft CTO Kevin Scott who has led their AI strategy for the past seven years. Scott describes himself as a “short-term pessimist, long-term optimist” and he sees the scaling trend as durable for the industry and critical for the establishment of Microsoft’s AI platform. Scott believes there will be a shift across the compute ecosystem from training to inference as the frontier models continue to improve, serving wider and more reliable use cases. He also discusses the coming business models for training data, and even what ad units might look like for autonomous agents. Hosted by: Pat Grady and Bill Coughran, Sequoia Capital Mentioned: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, the 2018 Google paper that convinced Kevin that Microsoft wasn’t moving fast enough on AI. Dennard scaling: The scaling law that describes the proportional relationship between transistor size and power use; has not held since 2012 and is often confused with Moore’s Law. Textbooks Are All You Need: Microsoft paper that introduces a new large language model for code, phi-1, that achieves smaller size by using higher quality “textbook” data. GPQA and MMLU: Benchmarks for reasoning Copilot: Microsoft product line of GPT consumer assistants from general productivity to design, vacation planning, cooking and fitness. Devin: Autonomous AI code agent from Cognition Labs that Microsoft recently announced a partnership with. Ray Solomonoff: Participant in the 1956 Dartmouth Summer Research Project on Artificial Intelligence that named the field; Kevin admires his prescience about the importance of probabilistic methods decades before anyone else. 00:00 - Introduction 01:20 - Kevin’s backstory 06:56 - The role of PhDs in AI engineering 09:56 - Microsoft’s AI strategy 12:40 - Highlights and lowlights 16:28 - Accelerating investments 18:38 - The OpenAI partnership 22:46 - Soon inference will dwarf training 27:56 - Will the demand/supply balance change? 30:51 - Business models for data 36:54 - The value function 39:58 - Copilots 44:47 - The 98/2 rule 49:34 - Solving zero-sum games 57:13 - Lightning round

09/07/2024

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1 小時
14/05/2025 · 附贈內容

LIVE: Sam Altman of OpenAI on Building the ‘Core AI Subscription’ for Your Life

Recorded live at Sequoia’s AI Ascent 2025: Sam reflects on OpenAI’s evolution from a 14-person research lab to a dominant AI platform. He envisions transforming ChatGPT into a deeply personal AI service that remembers your entire life's context—from conversations to emails—while working seamlessly across all services. Sam describes the generation gap in how users engage with ChatGPT, and makes surprisingly specific predictions for the next 2-3 years of AI evolution.

14/05/2025 · 附贈內容

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32 分鐘
05/06/2024

Introducing "Training Data"

Join us as we train our neural nets on the theme of the century: AI. Sequoia Capital partners Sonya Huang and Pat Grady host conversations with leading AI builders and researchers to ask critical questions and develop a deeper understanding of the evolving technologies and their implications for technology, business and society. The content of this podcast does not constitute investment advice, an offer to provide investment advisory services, or an offer to sell or solicitation of an offer to buy an interest in any investment fund.

05/06/2024

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1 分鐘
25/02/2025

OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents

OpenAI’s Isa Fulford and Josh Tobin discuss how the company’s newest agent, Deep Research, represents a breakthrough in AI research capabilities by training models end-to-end rather than using hand-coded operational graphs. The product leads explain how high-quality training data and the o3 model’s reasoning abilities enable adaptable research strategies, and why OpenAI thinks Deep Research will capture a meaningful percentage of knowledge work. Key product decisions that build transparency and trust include citations and clarification flows. By compressing hours of work into minutes, Deep Research transforms what’s possible for many business and consumer use cases. Hosted by: Sonya Huang and Lauren Reeder, Sequoia Capital Mentioned in this episode: Yann Lecun’s Cake: An analogy Meta AI’s leader shared in his 2016 NIPS keynote

25/02/2025

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33 分鐘
30/07/2024

Meta’s Joe Spisak on Llama 3.1 405B and the Democratization of Frontier Models

As head of Product Management for Generative AI at Meta, Joe Spisak leads the team behind Llama, which just released the new 3.1 405B model. We spoke with Joe just two days after the model’s release to ask what’s new, what it enables, and how Meta sees the role of open source in the AI ecosystem. Joe shares that where Llama 3.1 405B really focused is on pushing scale (it was trained on 15 trillion tokens using 16,000 GPUs) and he’s excited about the zero-shot tool use it will enable, as well as its role in distillation and generating synthetic data to teach smaller models. He tells us why he thinks even frontier models will ultimately commoditize—and why that’s a good thing for the startup ecosystem. Hosted by: Stephanie Zhan and Sonya Huang, Sequoia Capital Mentioned in this episode: Llama 3.1 405B paper Open Source AI Is the Way Forward: Mark Zuckerberg essay released with Llama 3.1. Mistral Large 2 The Bitter Lesson by Rich Sutton 00:00 Introduction 01:28 The Llama 3.1 405B launch 05:02 The open source license 07:01 What's in it for Meta? 10:19 Why not open source? 11:16 Will frontier models commoditize? 12:41 What about startups? 16:29 The Mistral team 19:36 Are all frontier strategies comparable? 22:38 Is model development becoming more like software development? 26:34 Agentic reasoning 29:09 What future levers will unlock reasoning? 31:20 Will coding and math lead to unlocks? 33:09 Small models 34:08 7X more data 37:36 Are we going to hit a wall? 39:49 Lightning round

30/07/2024

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42 分鐘
04/12/2025

Palo Alto Networks ft Nir Zuk & Nikesh Arora - The Grudge That Transformed Cybersecurity

In the early 2000s, the cybersecurity industry was dominated by incumbents focused on high margins, not innovation. Nir Zuk tells the story of how, frustrated by this stagnant culture, he set out on his own with a radical idea: the Next-Generation Firewall. His vision was to unify dozens of security functions into a single, intelligent platform delivered via cloud—an approach everyone thought was crazy. Palo Alto Networks started as a disruptive startup with Nir sporting a "Check Point Killer" vanity license plate, and grew to dominate cybersecurity. We explore the crucible moments that defined its path: the controversial decision to insist on being a new kind of "firewall" vs. a “firewall helper,” the challenge of scaling a hyper-growth company, and the critical pivot from building everything in-house to current CEO Nikesh Arora’s aggressive acquisition strategy that remade the company for the cloud era. Nir, Nikesh, and the core leadership team offer a masterclass in product conviction, strategic transformation, and the courage to disrupt yourself before the market does it for you. Featuring: Nir Zuk, Nikesh Arora, Lee Klarich, Rajiv Batra, Mark McLaughlin, Jim Goetz, Asheem Chandra Hosted by: Roelof Botha, Sequoia Capital

04/12/2025

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47 分鐘

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