AI by Hand ✍️

AI by Hand ✍️

PPO → DPO → GRPO → Rubrics (Mar 2, 2026)

AI by Hand ✍️ Seminars

Prof. Tom Yeh's avatar
Prof. Tom Yeh
Mar 02, 2026
∙ Paid

Library › Seminar Series 2026

  1. Manifold-Constrained Hyper Connections (mHC) from DeepSeek (Jan 9, 2026)

  2. How Small Models Learn Tool Use (Jan 11, 2026)

  3. Generative AI (Jan 11, 2026)

  4. Attention (Jan 15, 2026)

  5. Google Ironwood TPU: From Bits to HBM (Jan 19, 2026)

  6. 9 AI Eval Formulas You Must Know (Jan 24, 2026)

  7. Meta Superintelligence Labs vs Facebook AI Research (Jan 30, 2026)

  8. Transformer: Six Levels of Understanding (Feb 13, 2026)

  9. OpenClaw Seminar (Feb 23, 2026)

  10. PPO → DPO → GRPO → Rubrics (Mar 2, 2026)

  11. Gemma 4 (May 7, 2026)

  12. Qwen 3.6 (May 21, 2026)

In last week’s AI by Hand ✍️ seminar, I talked about reinforcement learning from first principles. I started all the way back from pre-training and inference, before climbing forward through the major evolution stages of the modern RL stack: PPO → DPO → GRPO. I finally arrived at Rubrics, widely considered one of today’s frontier topics in RL research.

I was joined by Cameron R. Wolfe, author of the Deep (Learning) Focus newsletter (60K subscribers) and a Senior Research Scientist at Netflix. He gave a special guest lecture based on his popular recent article Rubric-based Rewards for RL.

After eight seminars in 2026, I’ve settled into a format that has clearly resonated:

AI by Hand Lecture → Industry Guest Interview → Industry Guest Lecture.

I’m the professor in the first half—and the student in the second. 🙌

Feedback

Industry Expert: Cameron Wolfe

As a professor in academia, how can I possibly know what kind of research is really going on in the industry? I turn to people like Cameron. I've been reading his long-form articles long before I even started sharing my own content through this AI by Hand newsletter. Cameron was one of the early supporters who encouraged me to share more publicly.

I still remember two years ago when he told me he had just gotten married and was moving to Netflix to become a Senior Research Scientist working on reinforcement learning. He mentioned he might need to pause the Deep Focus newsletter for a while. Fortunately for all of us, the break was short. Cameron kept writing. I kept learning.

In the seminar, I finally got a chance to interview him so his story can be heard by all of you:

  • Q: Can you use Jiu-Jitsu as a metaphor to explain reinforcement learning?

  • Q: Reinforcement learning used to feel like robotics demos. Why has RL become so important for frontier language models?

  • Q: What are the main challenges of doing RL research at large scale?

  • Q: What motivated you to write the Deep Focus newsletter?

Watch the recording to hear Cameron explain it in his own words.

Recording & Workbook

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