#547: Parallel Python at Anyscale with Ray

#547: Parallel Python at Anyscale with Ray

When OpenAI trained GPT-3, they didn't roll their own orchestration layer. They used Ray, an open source Python framework born out of the same Berkeley research lab lineage that gave us Apache Spark. And here's the twist: Ray was originally built for reinforcement learning research, then quietly faded as RL hit a wall. Until ChatGPT showed up. Suddenly reinforcement learning was back, as the post-training step that turns a raw language model into something genuinely useful. Edward Oakes and Richard Liaw, two founding engineers behind Ray and Anyscale, join me on Talk Python to tell that story. We'll trace Ray from its RISE Lab origins at UC Berkeley to powering some of the largest training runs in the world. We'll talk about what Ray actually is, a distributed execution engine for AI workloads, and how a few lines of Python become work running across hundreds of GPUs. We'll cover Ray Data for multimodal pipelines, the dashboard, the VS Code remote debugger, KubRay for Kubernetes, and where Ray fits alongside Dask, multiprocessing, and asyncio. If you've ever stared at a single-machine Python script and thought, "there has to be a better way to scale this", this one's for you

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Episoder(555)

#556: Updates on Django's Async Story

#556: Updates on Django's Async Story

For years, "Django and async" came with an asterisk. The docs themselves warned you off it. Scary performance notes, a story that felt half-finished. Well, that story just got rewritten, literally, an...

26 Jul 0s

#555: Marimo Pair - A Canvas for Agent + Developers Collaboration

#555: Marimo Pair - A Canvas for Agent + Developers Collaboration

Coding agents have gotten really good at one kind of work. You scope a feature, edit some files, run the tests, ship it. It all happens on disk. But that is not how data work feels. You load something...

13 Jul 1h 4min

#554: Trustworthy AI in Healthcare and Longevity

#554: Trustworthy AI in Healthcare and Longevity

You ask an AI a question and it answers with total confidence. Most of the time, a confidently wrong answer is just an annoyance. But what if the question is medical, and there's a real patient on the...

10 Jul 1h

#553: All of our tools

#553: All of our tools

This episode is a fun crossover from our Python news and tips podcast, Python Bytes. We have had some big changes over there. Brian Okken has moved on and Calvin Hendryx-Parker has joined the show as ...

26 Jun 55min

#552: Astral joins OpenAI

#552: Astral joins OpenAI

OpenAI just acquired Astral, the company behind uv, Ruff, and ty. And if your first thought was "wait, is uv toast?", you are not alone. But here's the twist Charlie Marsh shared with me: he thinks th...

17 Jun 1h 5min

#551: Stroll Down Startup Lane - 2026

#551: Stroll Down Startup Lane - 2026

If you've ever been to PyCon, you know one of the best parts of the expo hall is Startup Row, a stretch of booths where early-stage companies built on Python show off what they're creating. But only a...

11 Jun 1h 48min

#550: AI Contributions and Maintainer Load in Open Source

#550: AI Contributions and Maintainer Load in Open Source

You wake up, brew the coffee, open GitHub, and there it is. Another pull request on your open source project. Thirteen thousand lines added. No issue filed first. No discussion. Just "here, please rev...

30 Mai 1h 2min

#549: Great Docs

#549: Great Docs

Your documentation has two audiences now - humans reading the rendered HTML, and AI agents trying to make sense of your library. Rich Iannone and Michael Chow from Posit are back on Talk Python with a...

25 Mai 1h 7min

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