Episode description

Sarah Catanzaro is a General Partner at Amplify Partners, and one of the leading investors in AI and ML. Her investments include RunwayML, OctoML, and Gantry.

Sarah and Lukas discuss lessons learned from the "AI renaissance" of the mid 2010s and compare the general perception of ML back then to now. Sarah also provides insights from her perspective as an investor, from selling into tech-forward companies vs. traditional enterprises, to the current state of MLOps/developer tools, to large language models and hype bubbles.

Show notes (transcript and links): http://wandb.me/gd-sarah-catanzaro

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⏳ Timestamps:

0:00 Intro

1:10 Lessons learned from previous AI hype cycles

11:46 Maintaining technical knowledge as an investor

19:05 Selling into tech-forward companies vs. traditional enterprises

25:09 Building point solutions vs. end-to-end platforms

36:27 LLMS, new tooling, and commoditization

44:39 Failing fast and how startups can compete with large cloud vendors

52:31 The gap between research and industry, and vice versa

1:00:01 Advice for ML practitioners during hype bubbles

1:03:17 Sarah's thoughts on Rust and bottlenecks in deployment

1:11:23 The importance of aligning technology with people

1:15:58 Outro

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📝 Links

📍 "Operationalizing Machine Learning: An Interview Study" (Shankar et al., 2022), an interview study on deploying and maintaining ML production pipelines: https://arxiv.org/abs/2209.09125

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Connect with Sarah:

📍 Sarah on Twitter: https://twitter.com/sarahcat21

📍 Sarah's Amplify Partners profile: https://www.amplifypartners.com/investment-team/sarah-catanzaro

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💬 Host: Lukas Biewald

📹 Producers: Riley Fields, Angelica Pan

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