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No Priors: Artificial Intelligence | Technology | Startups
Erik Bernhardsson on Creating Tools That Make AI Feel Effortless
No Priors: Artificial Intelligence | Technology | Startups

Erik Bernhardsson on Creating Tools That Make AI Feel Effortless

Conviction 23m 16 months ago
At this moment of inflection in technology, co-hosts Elad Gil and Sarah Guo talk to the world's leading AI engineers, researchers and founders about the biggest questions: How far away is AGI? What markets are at risk for disruption? How will commerce, culture, and society change? What’s happening in state-of-the-art in research? “No Priors” is your guide to the AI revolution. Email feedback to show@no-priors.com. Sarah Guo is a startup investor and the founder of Conviction, an investment firm purpose-built to serve intelligent software, or "Software 3.0" companies. She spent nearly a decade incubating and investing at venture firm Greylock Partners. Elad Gil is a serial entrepreneur and a startup investor. He was co-founder of Color Health, Mixer Labs (which was acquired by Twitter). He has invested in over 40 companies now worth $1B or more each, and is also author of the High Growth Handbook.

Show Notes

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Today on No Priors, Elad chats with Erik Bernhardsson, founder and CEO of Modal Labs, a platform simplifying ML workflows by providing a serverless infrastructure designed to streamline deployment, scaling, and development for AI engineers. Erik talks about his early work on Spotify’s ML algorithms, what Modal offers today, and his vision for building an end-to-end solution for AI engineers. They dive into GPU trends, cloud vs on-premise setups, and when to train custom models vs use off-the-shelf solutions. Erik also shares his thoughts on the evolving role of AI in fields like coding, physics, and music.
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Show Notes:
Introduction 
Erik's early interest in ML infra
Founding Modal Labs 
State of GPU use today and what’s to come
Modal's end-to-end vision 
Differentiating amongst competition
Cloud vs on-premise 
Popular AI models 
Gaps in AI infrastructure
Insights on vector databases 
Training models vs off-the-shelf models 
AI’s impact on coding and physics
AI's impact on music

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