Training Data

Latest Episodes:

Arc Institute's Patrick Hsu on Building an App Store for Biology with AI Apr 15, 2025

Show notes

Patrick Hsu, co-founder of Arc Institute, discusses the opportunities for AI in biology beyond just drug development, and how Evo 2, their new biology foundation model, is enabling a broad ecosystem of applications. Evo 2 was trained on a vast dataset of genomic data to learn evolutionary patterns that would have taken years to find; as a result, the model can be used for applications from identifying mutations that cause disease to designing new molecular and even genome scale biological systems.

Hosted by Josephine Chen and Pat Grady, Sequoia Capital

Mentioned in this episode:

Sequence modeling and design from molecular to genome scale with Evo: Public pre-print of original Evo paper
Genome modeling and design across all domains of life with Evo 2: Public pre-print of Evo 2 paper
ClinVar: NIH database of the genes that are known to cause disease, and mutations in those genes causally associated with disease state
Sequence Read Archive: Massive NIH database of gene sequencing data
Machines of Loving Grace: Daria Amodei essay that Patrick cites on how AI could transform the world for the better
Arc Virtual Cell Atlas: Arc’s first step toward assembling, curating and generating large-scale cellular data from AI-driven biological discovery (among many other tools)
Protein Data Bank (PDB): a global archive of 3D structural information of biomolecules used by DeepMind to train AlphaFold
OpenAI Deep Research: The one AI app Patrick uses daily

Replit CEO Amjad Masad on 1 Billion Developers: A Better End State than AGI? Apr 08, 2025

Show notes

Amjad Masad set out more than a decade ago to pursue the dream of unleashing 1B software creators around the world. With millions of Replit users pre-ChatGPT, that vision was already becoming a reality. Turbocharged by LLMs, the vision of enabling anyone to code—from 12-year-olds in India to knowledge workers in the U.S.—seems less and less radical. In this episode, Amjad explains how an explosion in the developer population could change the economy, society and more. He also discusses his early days programming in Jordan, his unique management approach and what AI will mean for the global economy.

Hosted by David Cahn and Sonya Huang, Sequoia Capital

Mentioned in this episode:

On the Naturalness of Software: 2012 paper on applying NLP to code

Attention Is All You Need: Seminal 2017 paper on transformers

I Am a Strange Loop: 2007 follow up to Douglas Hofstadter’s 1979 classic Gödel, Escher, Bach that explores how self-referential systems can describe minds

On Lisp: Paul Graham’s 1993 book on the original programming language of AI

Why CRM Needs an AI Revolution, with Day.ai Founder Christopher O’Donnell Apr 01, 2025

Show notes

Christopher O’Donnell believes the fundamental problems with CRM—incomplete data, complex workflows, siloed work products and the fear of leads falling through the cracks—can finally be solved through AI. Founder of Day.ai and former Chief Product Officer of HubSpot, Christopher explains how his team is building a system that automatically captures the full context of customer relationships while giving users transparency and control. He shares lessons from building HubSpot’s CRM and why he’s taking a deliberate approach to product development despite the pressure to scale quickly in the AI era.

Hosted by Pat Grady, Sequoia Capital

Mentioned in this episode:

The Innovator's Dilemma: Classic book by Clay Christensen (referenced regarding HubSpot's second S-curve strategy)
Hubspot CRM: The only product to successfully challenge Salesforce’s dominance in the CRM category
From Super Mario Brothers to Elden Ring: Analogy to what an AI-powered CRM experience can be through comparison of video games launched in 1985 vs 2022
Punk’d: Hidden camera–practical joke reality television series that premiered on MTV in 2003, created by Ashton Kutcher and Jason Goldberg
Slow is smooth and smooth is fast: SEALs-derived concept mentioned regarding product development)
Aga stove (highlighted as extraordinary product design example)

From Software Engineers to AI Word Artisans: Filip Kozera of Wordware Mar 25, 2025

Show notes

Filip Kozera sees parallels between Excel’s democratization of data analytics and Wordware’s mission to put AI development in the hands of knowledge workers. Drawing inspiration from Excel’s 750 million users (compared to 30 million software developers), Wordware is creating tools that balance the rigid structure of programming with the fuzziness of natural language. Filip explains why effective AI development requires working across multiple abstraction layers—from high-level concepts to detailed implementation—while preserving human creative control. He shares his vision for “word artisans” who will use AI to amplify their creative impact.

Hosted by Sonya Huang, Sequoia Capital

Mentioned in this episode:

Lovable: Generative AI app that builds UIs and web apps
Her: 2013 Spike Jonze film that Filip uses as an example of how voice will not be the best modality to express knowledge work.
Descript: AI video editing app that Filip uses a lot.
Granola: AI notetaking app Filip uses every day..
Gemini 2.0 Pro: Google’s newest long context model that can handle 6000 page pdfs.
Limitless pendant: Wearable device for collecting personal conversational context to drive AI experiences that Filip can’t wait for to ship.
DeepLearning.AI: Andrew Ng’s amazing resource for learning about AI

3Blue1Brown: Grant Sanderson’s incredible channel on YouTube that explains math and AI visually.

Josh Woodward: Google Labs is Rapidly Building AI Products from 0-to-1 Mar 18, 2025

Show notes

As VP of Google Labs, Josh Woodward leads teams exploring the frontiers of AI applications. He shares insights on their rapid development process, why today’s written prompts will become outdated and how AI is transforming everything from video generation to computer control. He reveals that 25% of Google’s code is now written by AI and explains why coding could see major leaps forward this year. He emphasizes the importance of taste, design and human values in building AI tools that will shape how future generations work and create.

Mentioned in this episode:

Notebook LM: Personal research product based on Gemini 2 (previously discussed on Training Data.)
Veo 2: Google DeepMind’s new video generation model.
Paul Graham on X replying to Aaron Levie’s post that “One approach to take in building in AI is to do something that's too expensive to be reasonably practical right now, and just bet that the costs will drop by 10X or 100X over time. The cost curve is on your side.”
Where Good Ideas Come From: Book on the history of innovation by Steven Johnson.
Project Mariner: Google DeepMind’s research prototype exploring human-agent interaction starting with browser use.
Replit Agent: Josh’s favorite new AI app
The Lego Story: Book on the history of Lego.

Hosted by: Ravi Gupta and Sonya Huang, Sequoia Capital

How AI Breakout Harvey is Transforming Legal Services, with CEO Winston Weinberg Mar 11, 2025

Show notes

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

The AI Product Going Viral With Doctors: OpenEvidence, with CEO Daniel Nadler Mar 04, 2025

Show notes

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

OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents Feb 25, 2025

Show notes

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

Palo Alto Networks’ Nikesh Arora: AI, Security and the New World Order Feb 18, 2025

Show notes

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

MongoDB’s Sahir Azam: Vector Databases and the Data Structure of AI Feb 13, 2025

Show notes

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

Our TOPPODCAST Picks

Follow Us

Stay Connected

Related Podcasts

Links

Stay Connected

Our TOPPODCAST Picks

Follow Us

Stay Connected

Training Data

Related Podcasts

1

2

3

4

5

6