Ion Stoica — Spark, Ray, and Enterprise Open Source

Ion Stoica — Spark, Ray, and Enterprise Open Source

Author: Lukas Biewald January 20, 2022 Duration: 53:42

Ion Stoica is co-creator of the distributed computing frameworks Spark and Ray, and co-founder and Executive Chairman of Databricks and Anyscale. He is also a Professor of computer science at UC Berkeley and Principal Investigator of RISELab, a five-year research lab that develops technology for low-latency, intelligent decisions.

Ion and Lukas chat about the challenges of making a simple (but good!) distributed framework, the similarities and differences between developing Spark and Ray, and how Spark and Ray led to the formation of Databricks and Anyscale. Ion also reflects on the early startup days, from deciding to commercialize to picking co-founders, and shares advice on building a successful company.

The complete show notes (transcript and links) can be found here: http://wandb.me/gd-ion-stoica

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Timestamps:

0:00 Intro

0:56 Ray, Anyscale, and making a distributed framework

11:39 How Spark informed the development of Ray

18:53 The story behind Spark and Databricks

33:00 Why TensorFlow and PyTorch haven't monetized

35:35 Picking co-founders and other startup advice

46:04 The early signs of sky computing

49:24 Breaking problems down and prioritizing

53:17 Outro

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Lukas Biewald hosts Gradient Dissent: Conversations on AI, a series that moves beyond theoretical discussions to examine how artificial intelligence is actually built and deployed. Each episode features a direct, unscripted talk with a leading practitioner-you’ll hear from engineers and researchers at places like NVIDIA, Meta, Google, Lyft, and OpenAI. The focus is on the tangible challenges and breakthroughs they encounter, from initial research to the complex reality of putting models into production. This isn't about abstract futures; it's a grounded look at the decisions shaping the field right now. Biewald, bringing his perspective from Weights & Biases, steers conversations toward the practical trade-offs and collaborative efforts that define modern AI work. For anyone in technology or business who wants to understand the mechanics behind the headlines, this podcast offers a rare, candid window into the process. You’ll come away with a clearer sense of how ideas become functional systems and what it really takes to operate at the cutting edge.
Author: Language: English Episodes: 100

Gradient Dissent: Conversations on AI
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