Machine learning at scale
Ludovico BessiMachine learning systems in the real world.
| Platform |  | Pricing | Freemium | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 134 | Subscribers | Read | machinelearningatscale.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Reinforcement Learning with Rubric Anchors: A Technical Deep Dive
TLDR: A new study introduces “Reinforcement Learning with Rubric Anchors” (Rubicon), a framework extending Reinforcement Learning from Verifiable Rewards (RLVR) to open-ended, subjective tasks.
Don't Abolish Tokenizers—Understand Them
TLDR: Hating on tokenizers is the cool thing to do right now, but the “tokenizer-free” alternatives being pushed (byte-level, dynamic patching) are just tokenization by another name—and they usually come with massive performance penalties.
From PPO to GRAPE: A Technical Review of the LLM Alignment Landscape
TL;DR A new paper by Meta AI’s provides a first-principles review of LLM alignment, tracing the evolution from complex, on-policy algorithms like PPO to simpler, offline methods like DPO.
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Authors
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ML engineer @Google
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