Training Data

Sequoia Capital
  • 4,2 (37)
  • ТЕХНОЛОГИИ
  • ЕЖЕНЕДЕЛЬНО

Join us as we train our neural nets on the theme of the century: AI. Sonya Huang, Pat Grady and more Sequoia Capital partners 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.

  1. Why IDEs Won't Die in the Age of AI Coding: Zed Founder Nathan Sobo

    -6 ДН.

    Why IDEs Won't Die in the Age of AI Coding: Zed Founder Nathan Sobo

    Nathan Sobo has spent nearly two decades pursuing one goal: building an IDE that combines the power of full-featured tools like JetBrains with the responsiveness of lightweight editors like Vim. After hitting the performance ceiling with web-based Atom, he founded Zed and rebuilt from scratch in Rust with GPU-accelerated rendering. Now with 170,000 active developers, Zed is positioned at the intersection of human and AI collaboration. Nathan discusses the Agent Client Protocol that makes Zed "Switzerland" for different AI coding agents, and his vision for fine-grained edit tracking that enables permanent, contextual conversations anchored directly to code—a collaborative layer that asynchronous git-based workflows can't provide. Nathan argues that despite terminal-based AI coding tools visual interfaces for code aren't going anywhere, and that source code is a language designed for humans to read, not just machines to execute. Hosted by Sonya Huang and Pat Grady, Sequoia Capital

    40 мин.
  2. How End-to-End Learning Created Autonomous Driving 2.0: Wayve CEO Alex Kendall

    18 НОЯБ.

    How End-to-End Learning Created Autonomous Driving 2.0: Wayve CEO Alex Kendall

    Alex Kendall founded Wayve in 2017 with a contrarian vision: replace the hand-engineered autonomous vehicle stack with end-to-end deep learning. While AV 1.0 companies relied on HD maps, LiDAR retrofits, and city-by-city deployments, Wayve built a generalization-first approach that can adapt to new vehicles and cities in weeks. Alex explains how world models enable reasoning in complex scenarios, why partnering with automotive OEMs creates a path to scale beyond robo-taxis, and how language integration opens up new product possibilities. From driving in 500 cities to deploying with manufacturers like Nissan, Wayve demonstrates how the same AI breakthroughs powering LLMs are transforming the physical economy. Hosted by: Pat Grady and Sonya Huang

    42 мин.
  3. How Google’s Nano Banana Achieved Breakthrough Character Consistency

    11 НОЯБ.

    How Google’s Nano Banana Achieved Breakthrough Character Consistency

    When Google launched Nano Banana, it instantly became a global phenomenon, introducing an image model that finally made it possible for people to see themselves in AI-generated worlds. In this episode, Nicole Brichtova and Hansa Srinivasan, the product and engineering leads behind Nano Banana, share the story behind the model’s creation and what it means for the future of visual AI. Nicole and Hansa discuss how they achieved breakthrough character consistency, why human evaluation remains critical for models that aim to feel right, and how “fun” became a gateway to utility. They explain the craft behind Gemini’s multimodal design, the obsession with data quality that powered Nano Banana’s realism, and how user creativity continues to push the technology in unexpected directions—from personal storytelling to education and professional design. The conversation explores what comes next in visual AI, why accessibility and imagination must evolve together, and how the tools we build can help people capture not just reality but possibility. Hosted by: Stephanie Zhan and Pat Grady, Sequoia Capital

    44 мин.
  4. OpenAI Sora 2 Team: How Generative Video Will Unlock Creativity and World Models

    6 НОЯБ.

    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

    1 ч.
  5. Nvidia CTO Michael Kagan: Scaling Beyond Moore's Law to Million-GPU Clusters

    28 ОКТ.

    Nvidia CTO Michael Kagan: Scaling Beyond Moore's Law to Million-GPU Clusters

    Recorded live at Sequoia’s Europe100 event: Michael Kagan, co-founder of Mellanox and CTO of Nvidia, explains how the $7 billion Mellanox acquisition helped transform Nvidia from a chip company into the architect of AI infrastructure. Kagan breaks down the technical challenges of scaling from single GPUs to 100K and eventually million-GPU data centers. He reveals why network performance—not just compute power—determines AI system efficiency. He discusses the shift from training to inference workloads, and his vision for AI as humanity's "spaceship of the mind," and why he thinks AI may help us discover laws of physics we haven’t yet imagined. Hosted by Sonya Huang and Pat Grady

    42 мин.

  6. 21 ОКТ.

    Securing the AI Frontier: Irregular Co-founder Dan Lahav

    Irregular co-founder Dan Lahav is redefining what cybersecurity means in the age of autonomous AI. Working closely with OpenAI, Anthropic, and Google DeepMind, Dan, co-founder Omer Nevo and team are pioneering “frontier AI security”—a proactive approach to safeguarding systems where AI models act as independent agents. Dan shares how emergent behaviors, from models socially engineering each other to outmaneuvering real-world defenses like Windows Defender, signal a coming paradigm shift. Dan explains why tomorrow’s threats will come from AI-on-AI interactions, why anomaly detection will soon break down, and how governments and enterprises alike must rethink defenses from first principles as AI becomes a national security layer. Hosted by: Sonya Huang and Dean Meyer, Sequoia Capital 00:00 Introduction 03:07 The Future of AI Security 03:55 Thought Experiment: Security in the Age of GPT-10 05:23 Economic Shifts and AI Interaction 07:13 Security in the Autonomous Age 08:50 AI Model Capabilities and Cybersecurity 11:08 Real-World AI Security Simulations 12:31 Working with AI Labs 32:34 Enterprise AI Security Strategies 40:03 Governmental AI Security Considerations 43:41 Final Thoughts

    44 мин.
  7. Why AI Will Transform Customer Experience: Cresta CEO Ping Wu and Sequoia’s Doug Leone

    14 ОКТ.

    Why AI Will Transform Customer Experience: Cresta CEO Ping Wu and Sequoia’s Doug Leone

    Ping Wu built Google's contact center business before becoming CEO of Cresta, where he's pioneering a unique approach to contact center transformation. Rather than full automation Ping advocates a dual approach, automating what's ready while using AI to assist humans with the rest. He makes the case for an abundance mindset—imagining new customer experiences like talking to airline apps or turning synchronous interactions asynchronous. Ping breaks down the technical challenges of deploying Contact Center AI at scale, from solving latency to orchestrating 20+ models in real-time. Sequoia’s Doug Leone shares his framework for building AI companies at speed and why he believes we're at the front end of an Industrial Revolution 2.0. Hosted by: Sonya Huang and Doug Leone, Sequoia Capital 00:00 Introduction 01:13 The Evolution of Contact Centers 02:05 Debating AI's Impact on Call Centers 04:07 Challenges and Opportunities in Contact Centers 08:14 Technological Waves in Contact Centers 11:10 AI vs Human Agents: The Future 13:35 Customer Experience and AI 16:33 The Role of Data in AI Automation 19:05 Competing in the AI Space 22:34 Building a Company in the AI Era 24:05 Instilling Speed in AI Companies 24:53 Management Experience and Growth Challenges 26:01 Identifying Leadership Potential 26:37 Cresta's Leadership Transition 28:34 Future Goals for Cresta 29:56 AI Market Cycles and Investment 35:38 Cresta's Technical Stack 45:11 AI's Impact on Business Communication

    45 мин.
  8. Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent

    30 СЕНТ.

    Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent

    As CTO of Block, Dhanji Prasanna has overseen a dramatic enterprise AI transformation, with engineers saving 8-10 hours a week through AI automation. Block’s open-source agent goose connects to existing enterprise tools through MCP, enabling everyone from engineers to sales teams to build custom applications without coding. Dhanji shares how Block reorganized from business unit silos to functional teams to accelerate AI adoption, why they chose to open-source their most valuable AI tool and why he believes swarms of smaller AI models will outperform monolithic LLMs. Hosted by: Sonya Huang and Roelof Botha, Sequoia Capital Mentioned in the episode: goose: Block’s open-source, general-purpose AI agent used across the company to orchestrate workflows via tools and APIs.  Model Context Protocol (MCP): Open protocol (spearheaded by Anthropic) for connecting AI agents to tools; goose was an early adopter and helped shape. bitchat: Decentralized chat app written by Jack Dorsey Swarm intelligence: Research direction Dhanji highlights for AI’s future where many agents (geese) collaborate to build complex software beyond a single-agent copilot. Travelling Salesman Problem: Classic optimization problem cited by Dhanji in the context of a non-technical user of goose solving a practical optimization task. Amara’s Law: The idea, originated by futurist Roy Amara in 1978, that we overestimate tech impact short term and underestimate long term. 00:00 Introduction 01:48 AI: Friend or Foe? 03:13 Block's Journey with AI and Technology 04:47 Block's Diverse Product Range 07:04 Driving AI at Block 14:28 The Evolution of Goose 27:45 Integrating Goose with Existing Systems 28:23 Goose's Learning and Recipe Feature 29:41 Tool Use and LLM Providers 31:40 Impact of AI on Developer Productivity 34:37 Block's Commitment to Open Source 39:09 Future of AI and Swarm Intelligence 43:05 Remote Work at Block 45:15 Vibe Coding and AI in Development 48:43 Making Goose More Accessible 51:28 Generative AI in Customer-Facing Products 54:09 Design and Engineering at Block 55:38 Predictions for the Future of AI

    1 ч.
См. все (73)

4,2
из 5
Оценок: 37

Об этом подкасте

Join us as we train our neural nets on the theme of the century: AI. Sonya Huang, Pat Grady and more Sequoia Capital partners 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.

Информация

  • Канал
    Sequoia Capital
  • Автор
    Sequoia Capital
  • Годы выхода
    2024 - 2025
  • Выпуски
    73
  • Ограничения
    С ненормативной лексикой
  • Сайт подкаста
    Training Data

Еще от провайдера «Sequoia Capital»

Вам может также понравиться