No PriorsNo Priors Ep. 77 | With Foundry CEO and Founder Jared Quincy Davis
Episode Details
EPISODE INFO
- Released
- August 22, 2024
- Duration
- 42m
- Channel
- No Priors
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
In this episode of No Priors, hosts Sarah and Elad are joined by Jared Quincy Davis, former DeepMind researcher and the Founder and CEO of Foundry, a new AI cloud computing service provider. They discuss the research problems that led him to starting Foundry, the current state of GPU cloud utilization, and Foundry's approach to improving cloud economics for AI workloads. Jared also touches on his predictions for the GPU market and the thinking behind his recent paper on designing compound AI systems. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jaredq_ Show Notes: 00:00 Introduction 02:42 Foundry background 03:57 GPU utilization for large models 07:29 Systems to run a large model 09:54 Historical value proposition of the cloud 14:45 Sharing cloud compute to increase efficiency 19:17 Foundry’s new releases 23:54 The current state of GPU capacity 29:50 GPU market dynamics 36:28 Compound systems design 40:27 Improving open-ended tasks
SPEAKERS
Sarah Guo
hostJared Quincy Davis
guestElad Gil
host
EPISODE SUMMARY
In this episode of No Priors, featuring Sarah Guo and Jared Quincy Davis, No Priors Ep. 77 | With Foundry CEO and Founder Jared Quincy Davis explores foundry’s Jared Davis Reimagines AI Cloud, GPU Economics, And Scaling Laws Jared Quincy Davis, CEO of Foundry, argues that modern AI breakthroughs like AlphaFold and ChatGPT are really stories of immense compute leverage, not just small heroic teams. He explains how Foundry is rebuilding the public cloud from first principles for AI workloads, claiming 12–20x better economics by improving utilization, reliability, and elasticity of GPU clusters. Davis critiques today’s AI cloud as effectively expensive, inflexible colocation, and outlines new products like SPOT and MARS that turn underused, reserved GPU capacity into elastic, preemptible compute. He also discusses a shift from monolithic giant models toward compound AI systems and verifiable, massively parallel “networks of networks” that can push frontier performance without requiring only the largest, most interconnected GPU superclusters.
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