Training Data

Sequoia Capital
  • ٤٫٣ (٣٠)
  • التكنولوجيا
  • يتم التحديث أسبوعيًا
Training Data

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. How AI Breakout Harvey is Transforming Legal Services, with CEO Winston Weinberg

    قبل يومين

    How AI Breakout Harvey is Transforming Legal Services, with CEO Winston Weinberg

    Harvey CEO Winston Weinberg explains why success in legal AI requires more than just model capabilities—it demands deep process expertise that doesn’t exist online. He shares how Harvey balances rapid product development with earning trust from law firms through hyper-personalized demos and deep industry expertise. The discussion covers Harvey’s approach to product development—expanding specialized capabilities then collapsing them into unified workflows—and why focusing on complex work like international mergers creates the most defensible position in legal AI. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital

    ٥٤ من الدقائق
  2. Is This Doctors’ New Favorite AI App? OpenEvidence, with CEO Daniel Nadler

    ٤ مارس

    Is This Doctors’ New Favorite AI App? OpenEvidence, with CEO Daniel Nadler

    OpenEvidence is transforming how doctors access medical knowledge at the point of care, from the biggest medical establishments to small practices serving rural communities. Founder Daniel Nadler explains his team’s insight that training smaller, specialized AI models on peer-reviewed literature outperforms large general models for medical applications. He discusses how making the platform freely available to all physicians led to widespread organic adoption and strategic partnerships with publishers like the New England Journal of Medicine. In an industry where organizations move glacially, 10-20% of all U.S. doctors began using OpenEvidence overnight to find information buried deep in the long tail of new medical studies, to validate edge cases and improve diagnoses. Nadler emphasizes the importance of accuracy and transparency in AI healthcare applications. Hosted by: Pat Grady, Sequoia Capital  Mentioned in this episode:  Do We Still Need Clinical Language Models?: Paper from OpenEvidence founders showing that small, specialized models outperformed large models for healthcare diagnostics Chinchilla paper: Seminal 2022 paper about scaling laws in large language models Understand: Ted Chiang sci-fi novella published in 1991

    ١ س ٥ د
  3. OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents

    ٢٥ فبراير

    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

    ٣٣ من الدقائق
  4. Palo Alto Networks’ Nikesh Arora: AI, Security and the New World Order

    ١٨ فبراير

    Palo Alto Networks’ Nikesh Arora: AI, Security and the New World Order

    Palo Alto Networks’s CEO Nikesh Arora dispels DeepSeek hype by detailing all of the guardrails enterprises need to have in place to give AI agents “arms and legs.” No matter the model, deploying applications for precision-use cases means superimposing better controls. Arora emphasizes that the real challenge isn’t just blocking threats but matching the accelerated pace of AI-powered attacks, requiring a fundamental shift from prevention-focused to real-time detection and response systems. CISOs are risk managers, but legacy companies competing with more risk-tolerant startups need to move quickly and embrace change.  Hosted by: Sonya Huang and Pat Grady, Sequoia Capital  Mentioned in this episode: Cortex XSIAM: Security operations and incident remediation platform from Palo Alto Networks

    ١ من الساعات
  5. MongoDB’s Sahir Azam: Vector Databases and the Data Structure of AI

    ١٣ فبراير

    MongoDB’s Sahir Azam: Vector Databases and the Data Structure of AI

    MongoDB product leader Sahir Azam explains how vector databases have evolved from semantic search to become the essential memory and state layer for AI applications. He describes his view of how AI is transforming software development generally, and how combining vectors, graphs and traditional data structures enables high-quality retrieval needed for mission-critical enterprise AI use cases. Drawing from MongoDB's successful cloud transformation, Azam shares his vision for democratizing AI development by making sophisticated capabilities accessible to mainstream developers through integrated tools and abstractions. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital  Mentioned in this episode: Introducing ambient agents: Blog post by Langchain on a new UX pattern where AI agents can listen to an event stream and act on it  Google Gemini Deep Research: Sahir enjoys its amazing product experience Perplexity: AI search app that Sahir admires for its product craft Snipd: AI powered podcast app Sahir likes

    ٤٤ من الدقائق
  6. Roblox Studio Head Stef Corazza: Using AI to Empower Creators

    ٤ فبراير

    Roblox Studio Head Stef Corazza: Using AI to Empower Creators

    Stef Corazza leads generative AI development at Roblox after previously building Adobe’s 3D and AR platforms. His technical expertise, combined with Roblox’s unique relationship with its users, has led to the infusion of AI into its creation tools. Roblox has assembled the world’s largest multimodal dataset. Stef previews the Roblox Assistant and the company’s new 3D foundation model, while emphasizing the importance of maintaining positive experiences and civility on the platform.  Mentioned in this episode: Driving Empire: A Roblox car racing game Stef particularly enjoys RDC: Roblox Developer Conference Ego.live: Roblox app to create and share synthetic worlds populated with human-like generative agents and simulated communities| PINNs: Physics Informed Neural Networks ControlNet: A model for controlling image diffusion by conditioning on an additional input image that Stef says can be used as a 2.5D approach to 3D generation. Neural rendering: A combination of deep learning with computer graphics principles developed by Nvidia in its RTX platform Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital

    ٥٥ من الدقائق

  7. ٢٨ يناير

    ReflectionAI Founder Ioannis Antonoglou: From AlphaGo to AGI

    Ioannis Antonoglou, founding engineer at DeepMind and co-founder of ReflectionAI, has seen the triumphs of reinforcement learning firsthand. From AlphaGo to AlphaZero and MuZero, Ioannis has built the most powerful agents in the world. Ioannis breaks down key moments in AlphaGo's game against Lee Sodol (Moves 37 and 78), the importance of self-play and the impact of scale, reliability, planning and in-context learning as core factors that will unlock the next level of progress in AI. Hosted by: Stephanie Zhan and Sonya Huang, Sequoia Capital Mentioned in this episode: PPO: Proximal Policy Optimization algorithm developed by DeepMind in game environments. Also used by OpenAI for RLHF in ChatGPT. MuJoCo: Open source physics engine used to develop PPO Monte Carlo Tree Search: Heuristic search algorithm used in AlphaGo as well as video compression for YouTube and the self-driving system at Tesla AlphaZero: The DeepMind model that taught itself from scratch how to master the games of chess, shogi and Go MuZero: The DeepMind follow up to AlphaZero that mastered games without knowing the rules and able to plan winning strategies in unknown environments AlphaChem: Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies DQN: Deep Q-Network, Introduced in 2013 paper, Playing Atari with Deep Reinforcement Learning AlphaFold: DeepMind model for predicting protein structures for which Demis Hassabis, John Jumper and David Baker won the 2024 Nobel Prize in Chemistry

    ٥٢ من الدقائق
  8. Kumo’s Hema Raghavan: Turning Graph AI into ROI

    ٢١ يناير

    Kumo’s Hema Raghavan: Turning Graph AI into ROI

    Hema Raghavan is co-founder of Kumo, a company that makes graph neural networks accessible to enterprises by connecting to their relational data stored in Snowflake and Databricks. Hema talks about how running GNNs on GPUs has led to breakthroughs in performance as well as the query language Kumo developed to help companies predict future data points. Although approachable for non-technical users, the product provides full control for data scientists who use Kumo to automate time-consuming feature engineering pipelines. Mentioned in this episode: Graph Neural Networks: Learning mechanism for data in graph format, the basis of the Kumo product Graph RAG: Popular extension of retrieval-augmented generation using GNNs LiGNN: Graph Neural Networks at LinkedIn paper  KDD: Knowledge Discovery and Data Mining Conference Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital

    ٥٢ من الدقائق
مشاهدة الكل (٣٥)

٤٫٣
من ٥
‫٣٠ من التقييمات‬

حول

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.

المعلومات

  • قناة
    Sequoia Capital
  • صناع العمل
    Sequoia Capital
  • سنوات النشاط
    ٢٠٢٤ - ٢٠٢٥
  • الحلقات
    ٣٥
  • التقييم
    ملائم
  • موقع البرنامج على الويب
    Training Data

المزيد من Sequoia Capital

قد يعجبك أيضًا

للاستماع إلى حلقات ذات محتوى فاضح، قم بتسجيل الدخول.

اطلع على آخر مستجدات هذا البرنامج

قم بتسجيل الدخول أو التسجيل لمتابعة البرامج وحفظ الحلقات والحصول على آخر التحديثات.
تحديد بلد أو منطقة

أفريقيا والشرق الأوسط، والهند

آسيا والمحيط الهادئ

أوروبا

أمريكا اللاتينية والكاريبي

الولايات المتحدة وكندا