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Artwork for Training Data

Training Data

Sequoia Capital
Artificial Intelligence
Openai
Reinforcement Learning
Large Language Models
Generative AI
Automation
Deepmind
Customer Experience
Machine Learning
Sequoia Capital
Software Development
Contact Center
Langchain
Chatgpt
AI Agents
Microsoft
Voice Technology
Elevenlabs
AI Audio
Artificial General Intelligence

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 adv... more

PublishesTwice weeklyEpisodes100Founded2 years ago
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Artwork for Training Data

Latest Episodes

Dylan Patel, founder of SemiAnalysis, argues the biggest gains in AI don't come from faster chips, they come from software-hardware co-design. Optimizing the model, the kernels, and the silicon together turns a 2x here and a 2x there into 100x. He ex... more

Dan Biderman and Jessy Lin, co-founders of Engram, are building a neolab around memory and continual learning, which they call two sides of the same coin. Their contrarian premise: instead of stuffing ever-larger prompts into the context window or bo... more

YouTube

The race to build superintelligence is producing models that keep getting better at objective problems, but not at behaving like actual people. Joon Sung Park, founder and CEO of Simile and creator of Stanford's "Smallville" generative agents study, ... more

The entire startup ecosystem is racing to build agent harnesses. Logan Kilpatrick, who leads Google AI Studio and the Gemini API, argues that scramble has a roughly 12-month shelf life. Models will absorb the scaffolding and run it natively, so the e... more

YouTube

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Recent Guests

Logan Kilpatrick
Head of Google AI Studio and the Gemini API
Google
Episode: Google DeepMind's Logan Kilpatrick: Why the Model Eats the Harness
Jensen Huang
CEO and founder of Nvidia
Nvidia
Episode: LIVE: Jensen Huang on Building the Dynamo of the Intelligence Age
Alfred Wahlforss
Founder and CEO of Listen Labs
Listen Labs
Episode: Knowing What Your Customers Want, All the Time: Listen Labs' Alfred Wahlforss
Jake Stauch
Founder and CEO of Serval
Serval
Episode: Rebuilding IT From the Ground Up for the AI Age: Serval's Jake Stauch
Mikey Shulman
Founder and CEO of Suno, building a music company and creative entertainment platform
Suno
Episode: Suno's Mikey Shulman: Everyone Can Make Music Now
Mati Staniszewski
Co-founder of ElevenLabs
ElevenLabs
Episode: ElevenLabs' Mati Staniszewski: How Voice Becomes the Interface for Everything
Boris Cherny
Engineer and creator of Claude Code
Anthropic
Episode: Anthropic's Boris Cherny: Coding's Printing Press Moment
Dmitri Dolgov
Engineer and lead figure at Waymo's autonomous vehicle program
Waymo
Episode: Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy
Greg Brockman
Co-founder and President of OpenAI
OpenAI
Episode: OpenAI's Greg Brockman: Why Human Attention Is the New Bottleneck

Host

Sonya Huang
Host of Training Data; introducing topics and guiding the interview

Reviews

4.7 out of 5 stars from 138 ratings
  • Pretty cool

    Nice speakers

    Apple Podcasts
    5
    seth_vikas
    Germanya year ago
  • Open evidence

    domain ignorance.Physicians overriding concern in private setting is repetitiveness of practice and in enterprise setting is how to address RVU’s not edge cases. It is like putting cart in front of horse

    Apple Podcasts
    1
    lalisyal
    United Statesa year ago
  • Super insightful

    Great hosts and really great in the weeds convos here

    Apple Podcasts
    5
    joel fowler
    United States2 years ago
  • Accessible with depth

    The first episode is essentially just Harrison Chase laying out “why agents” for an hour, in the best way possible. If his episode is any indication of what’s to come, this is going to be one of the best sources for a foundational understanding of what’s going on in the space.

    Apple Podcasts
    5
    Thomas J Myers
    United States2 years ago
  • Incredible!

    Pat Grady and Sonya Huang are incredibly insightful and some of the sharpest investors of our generation!

    Apple Podcasts
    5
    JXu8
    United States2 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Hosts bring clarity and sharp strategic questions to complex topics
Strong emphasis on practical lessons for implementing AI in real-world settings
Listeners appreciate the blend of engineering detail and business context
Thoughtful guests and deep technical dives that illuminate AI infrastructure

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Spotify
#44
United States/Technology
Apple Podcasts
#82
United States/Technology
Apple Podcasts
#52
United Kingdom/Technology
Apple Podcasts
#88
Canada/Technology
Apple Podcasts
#25
Italy/Technology
Apple Podcasts
#132
France/Technology

Talking Points

Recent interactions between the hosts and their guests.

LIVE: Jensen Huang on Building the Dynamo of the Intelligence Age
Q: What do you mean by the five-layer cake of AI and how should investors think about them?
Think of AI deployment as five layers: energy at the base providing power, chips and networking building the compute fabric, infrastructure for data centers and operations, the model layer where the leading AI families operate (OpenAI, Anthropic, etc.), and the top layer of applications that actually solve real-world problems. Investment flows are strongest into the top two layers, but all layers are essential for a healthy ecosystem.
LIVE: Jensen Huang on Building the Dynamo of the Intelligence Age
Q: Can you tell us what an AI factory is, and why is it the best investment for any enterprise in the next decade?
An AI factory is a scalable production system that turns inputs into intelligent outputs, using specialized hardware and software to generate language, images, and actions in real time. The ROI is enormous because these factories can produce meaningful, revenue-generating intelligence at scale, with multi-hundred-billion-dollar to trillion-dollar potential across energy, silicon, infrastructure, models, and applications.
Rebuilding IT From the Ground Up for the AI Age: Serval's Jake Stauch
Q: What happens when you encounter a new model that changes how things work—do you upgrade or downgrade based on reliability and guardrails?
They perform slow, measured releases, often preferring older, more reliable models for stability while experimenting with newer ones, and sometimes downgrading if the new model underperforms in critical enterprise contexts.
Rebuilding IT From the Ground Up for the AI Age: Serval's Jake Stauch
Q: How quickly can you incorporate new models into Serval's production version, and how automated is that process?
Model updates are not fully automated; evaluation is automated, but testing and integration require hands-on effort, with ongoing prompt tuning and infrastructure adjustments to handle new models and quirks.
Rebuilding IT From the Ground Up for the AI Age: Serval's Jake Stauch
Q: Do you have a North Star metric that tells you the product is getting better, or is it more a synthesis of customer anecdotes?
The founder emphasizes deep customer immersion, using direct channels like customer Slack workstreams to gauge product impact, with a focus on qualitative feedback shaping the roadmap rather than a single numeric North Star.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

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Frequently Asked Questions About Training Data

What is Training Data about and what kind of topics does it cover?

A technologically oriented show that probes how AI is built, deployed, and governed, with a strong focus on engineering, infrastructure, and product strategy. Recent conversations_CENTER on end-to-end training pipelines for advanced agents, production-grade deployment across distributed systems, AI-native enterprises, and the evolving role of AI assistants in software, music, and biotech. Notable threads include scaling GPUs for real-time feedback, multi-agent workflows, and the tension between model size, data, and compute, all anchored by pragmatic lessons from industry practitioners and researchers. The show often pairs founders, researchers, and senior operators to extract practical takeaways for listeners evaluating AI projects, vendor... more

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1. No Priors: Artificial Intelligence | Technology | Startups
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3. Y Combinator Startup Podcast
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5. Unsupervised Learning with Jacob Effron

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Training Data launched 2 years ago and published 100 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Training Data?

Recent guests on Training Data include:

1. Logan Kilpatrick
2. Jensen Huang
3. Alfred Wahlforss
4. Jake Stauch
5. Mikey Shulman
6. Mati Staniszewski
7. Boris Cherny
8. Dmitri Dolgov

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