Podcast artwork thumbnail for Training Data

Training Data

Sonya Huang, Pat Grady, Andrew Reed, Alfred Lin, Sonali Singh

Booking Overview

An interview-led AI and technology show hosted by Sequoia Capital partners, featuring prominent founders, CEOs, and leading researchers discussing frontier AI, enterprise applications, infrastructure, and societal implications. Credible pitches include high-profile AI company founders, enterprise technology executives, distinguished researchers, and computational biology or drug-discovery leaders; booking is very difficult because guests typically have substantial technical or commercial prominence.

Metrics

Episodes: 111

Frequency: Weekly

Rating: 4.3/5.0

Estimated listeners: 1,000 - 10,000

Listener location: USA

Contact Information

Publicly listed emails

podcast@sequoiacap.com

Looking for the right person? Join Podseeker to find direct host and producer contacts and manage your podcast outreach.

Host

Sonya Huang - Sequoia Capital partner focused on technology and artificial intelligence investments.

Pat Grady - Sequoia Capital partner focused on technology companies and venture investing.

Andrew Reed - Sequoia Capital partner and technology investor.

Alfred Lin - Sequoia Capital partner and technology investor with experience building and operating technology companies.

Sonali Singh - Sequoia Capital partner focused on technology and artificial intelligence.

Booking Intelligence

Booking Requirements

very_high
Typical Credentials:  
Founders or CEOs of notable AI, enterprise software, infrastructure, public safety technology, or computational biology companies; leading AI researchers; and executives or technical leaders with demonstrated expertise deploying advanced AI systems at meaningful scale.
Required Achievements:  
Founded or led a notable technology company, Made widely recognized contributions to artificial intelligence research or engineering, Built and deployed AI products or infrastructure at significant scale, Developed commercially meaningful applications of AI in enterprise, public safety, or drug discovery

Recent Guest Discussions

Aaron Levie - Enterprise AI Adoption, Application-layer Software, AI Agents, Model Economics, And The Diffusion Of AI Into Knowledge Work.

Ben Rudolph - Privacy-first Public Safety Technology, Data Ownership, City Infrastructure, AI Agents, And Data Governance.

Nick Noone - Privacy-first Public Safety Technology, Data Ownership, City Infrastructure, AI Agents, And Data Governance.

Parag Agrawal - Search Infrastructure For AI Agents, Agentic Web Economics, Content Attribution, And The Future Of Online Information Access.

Khurram Javed - Continual Learning, New AI Paradigms, Synthetic Data, Agent Architectures, And The Development Of Continuously Learning Systems.

Recent Topics

Technology, Artificial Intelligence, Machine Learning, Enterprise Software, Drug Discovery

Episodes

Here's the recent few episodes on
Training Data
:

David Silver and Lasse Espeholt of Ineffable Intelligence: A Superlearner for the Age of Experience

October 13, 2026

David Silver spent two years building AlphaGo on human data. When he removed human data altogether building AlphaGo Zero, the AI surpassed AlphaGo in under two days. He left DeepMind to run that same bet in pursuit of superintelligence. David and Lasse Espeholt, co-founders of Ineffable Intelligence, explain their plan to build a “superlearner”—an agent that starts knowing nothing and discovers science, mathematics, and language for itself by direct experience instead of through a pre-trainin...

Google's AI Infrastructure Chief, Amin Vahdat, on the Physics & Economics of Frontier AI

October 06, 2026

At 100,000-accelerator scale, something fails multiple times an hour, which is why Google's Chief Technologist for AI Infrastructure Amin Vahdat thinks FLOPS is a vanity metric. The metric that matters is what he calls goodput: the useful work a workload actually delivers through real failures. Amin walks through the calculus that split the TPU line into 8i and 8t for the first time, why the TPU's core primitives haven't changed since v1, and how Google and DeepMind co-design in the same room...

Box's Aaron Levie: On Reinventing Yourself in the AI Age and Enterprise Diffusion

September 15, 2026

Starting a company is hard. Reinventing your company for AI as a public company with quarterly earnings results is even harder. Aaron Levie has pulled off the transition with Box and offers hard-won advice for founders. The cofounder and CEO of Box argues the value isn't only in the model; it's in the bridge from a model's raw capability to the actual workflow inside a bank, a law firm, or a pharma company. That's the case for the application layer, and Box is building it: an agent harness tu...

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Training Data
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Frequently asked questions

Here's some frequently asked questions for
Training Data
:

How do I get in touch with Training Data?

Training Data is hosted by Sonya Huang and Pat Grady. Its publicly listed email is podcast@sequoiacap.com. For guest bookings, the host or producer is usually the best person to reach. Podseeker helps you find direct host and producer contacts and pitch from your own inbox.

What is the email for Training Data?

The publicly listed email for Training Data: podcast@sequoiacap.com.

How many listeners does Training Data have?

Podseeker estimates Training Data reaches 1,000 to 10,000 listeners per episode. Only the publisher has exact numbers.

Who is an ideal guest for Training Data?

Training Data typically books industry leaders. Typical guest background: Founders or CEOs of notable AI, enterprise software, infrastructure, public safety technology, or computational biology companies; leading AI researchers; and executives or technical leaders with demonstrated expertise deploying advanced AI systems at meaningful scale. Common among recent guests: Founded or led a notable technology company; Made widely recognized contributions to artificial intelligence research or engineering; Built and deployed AI products or infrastructure at significant scale. Recent guests include Aaron Levie, Ben Rudolph, and Nick Noone.

How hard is it to get booked on Training Data?

Very high. It mostly books well-known names.

What topics does Training Data cover?

Recent episodes cover Technology, Artificial Intelligence, Machine Learning, Enterprise Software, and Drug Discovery. Pitch an idea tied to one of these topics and mention a recent episode.

Publicly listed emails

podcast@sequoiacap.com

Looking for the right person? Join Podseeker to find direct host and producer contacts and manage your podcast outreach.

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