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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.
Sign up for new podcasts every week. Email feedback to [email protected]
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Bernhardsson
Show Notes:
0:00 Introduction
0:22 Erik's early interest in ML infra
1:22 Founding Modal Labs
4:17 State of GPU use today and what’s to come
7:14 Modal's end-to-end vision
9:00 Differentiating amongst competition
10:20 Cloud vs on-premise
12:35 Popular AI models
13:20 Gaps in AI infrastructure
14:55 Insights on vector databases
16:48 Training models vs off-the-shelf models
17:47 AI’s impact on coding and physics
22:14 AI's impact on music
By Conviction4.3
124124 ratings
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.
Sign up for new podcasts every week. Email feedback to [email protected]
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Bernhardsson
Show Notes:
0:00 Introduction
0:22 Erik's early interest in ML infra
1:22 Founding Modal Labs
4:17 State of GPU use today and what’s to come
7:14 Modal's end-to-end vision
9:00 Differentiating amongst competition
10:20 Cloud vs on-premise
12:35 Popular AI models
13:20 Gaps in AI infrastructure
14:55 Insights on vector databases
16:48 Training models vs off-the-shelf models
17:47 AI’s impact on coding and physics
22:14 AI's impact on music

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