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SF Compute: Commoditizing Compute

Overview

Shownote

Highlights

Transcript

Chapters

Pins

SF Compute: Commoditizing Compute

Latent Space: The AI Engineer Podcast

2025/04/11
Latent Space: The AI Engineer Podcast

Latent Space: The AI Engineer Podcast

2025/04/11
OverviewShownoteHighlightsTranscriptChaptersPins

Shownote

Evan Conrad, co-founder of SF Compute, joined us to talk about how they started as an AI lab that avoided bankruptcy by selling GPU clusters, why CoreWeave financials look like a real estate business, and how GPUs are turning into a commodities market. Chapters: 00:00:05 - Introductions 00:00:12 - Introduction of guest Evan Conrad from SF Compute 00:00:12 - CoreWeave Business Model Discussion 00:05:37 - CoreWeave as a Real Estate Business 00:08:59 - Interest Rate Risk and GPU Market Strategy Framework 00:16:33 - Why Together and DigitalOcean will lose money on their clusters 00:20:37 - SF Compute's AI Lab Origins 00:25:49 - Utilization Rates and Benefits of SF Compute Market Model 00:30:00 - H100 GPU Glut, Supply Chain Issues, and Future Demand Forecast 00:34:00 - P2P GPU networks 00:36:50 - Customer stories 00:38:23 - VC-Provided GPU Clusters and Credit Risk Arbitrage 00:41:58 - Market Pricing Dynamics and Preemptible GPU Pricing Model 00:48:00 - Future Plans for Financialization? 00:52:59 - Cluster auditing and quality control 00:58:00 - Futures Contracts for GPUs 01:01:20 - Branding and Aesthetic Choices Behind SF Compute 01:06:30 - Lessons from Previous Startups 01:09:07 - Hiring at SF Compute

Highlights

This podcast delves into the intricacies of the GPU market, focusing on CoreWeave's unique business model and its resemblance to a real estate venture. Evan Conrad from SF Compute discusses how his company transitioned from an AI lab to a cloud provider by selling GPU clusters. The conversation also examines the challenges and opportunities within the GPU industry, including pricing dynamics, customer needs, and future demand forecasts.
05:19
CoreWeave doesn't resemble a cloud provider or software company financially.
08:02
Chart explains GPU market profits through interest rates and cost depreciation.
11:38
CoreWeave's business model is more viable compared to selling high-priced short-term contracts.
16:34
Treating GPU clouds as real estate businesses can be profitable.
25:24
Short-term GPU burst capacity allows flexibility for users with varying needs.
28:17
Price drops in H100 GPUs reflect complex market dynamics.
30:00
Evan predicts a GPU shortage by winter due to future chip roll-out.
34:01
Peer-to-peer GPU markets are less efficient than interconnected clusters due to physical constraints.
36:50
Offering big burst capacity is particularly rewarding for difficult customers
38:23
VCs provided GPU clusters to startups due to credit risk challenges.
46:35
The financialization of GPUs could lead to their listing on exchanges.
50:17
Automated refunds switch customers to other resources during hardware issues.
57:53
Derivatives on mortgages are 12 times larger than the mortgages themselves.
58:00
Creating futures contracts for compute reduces risk.
1:06:23
Every year, someone tries to crack email but gives up.
1:08:43
Intercom is better positioned to use AI for email in support use-cases.
1:09:07
SF Compute seeks Linux-savvy engineers, not just Rust experts.
1:09:53
The role aims to prevent money loss and improve pricing for vendors and buyers
1:10:57
Tiger Beetle ensures systems do not lose money

Chapters

Introductions
00:00
CoreWeave as a Real Estate Business
05:37
Interest Rate Risk and GPU Market Strategy Framework
08:59
Why Together and DigitalOcean will lose money on their clusters
16:33
SF Compute's AI Lab Origins
20:37
Utilization Rates and Benefits of SF Compute Market Model
25:49
H100 GPU Glut, Supply Chain Issues, and Future Demand Forecast
30:00
P2P GPU networks
34:00
Customer stories
36:50
VC-Provided GPU Clusters and Credit Risk Arbitrage
38:23
Market Pricing Dynamics and Preemptible GPU Pricing Model
41:58
Future Plans for Financialization?
48:00
Cluster auditing and quality control
52:59
Futures Contracts for GPUs
58:00
Branding and Aesthetic Choices Behind SF Compute
1:01:20
Lessons from Previous Startups
1:06:30
Hiring at SF Compute
1:09:07
Hiring for Systems Engineering
1:09:53
Financial Systems Engineering Role
1:10:50

Transcript

Evan Conrad: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel, and I'm joined by Michael Swix, founder of SmallAI. Alessio: Hey, and today we're so excited to be finally in the studio with Evan Conrad from SF ...