one day = one second of runebench public server bot activity

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Controlling staleness in an async RL stack has not been well understood, so we derived a closed-form formula that predicts staleness in advance. Our predictions match measured staleness from production RL runs within a fraction of a step. Building these simulations has led to key insights on how we maintain high GPU utilization during our RL runs without sacrificing ML performance.

Preserving entropy is critical for continued training; in modern post-training recipes, entropy is often a fixed resource that gets exhausted over the course of a training run, making it difficult for the model to improve and learn on new tasks. Adaptive entropy control methods expose entropy as a controllable hyperparameter instead of a side effect. We find that in a continued training setting, GRPO leads to entropy collapse which stalls training performance on subsequent training phases. REPO-R (Petrenko et al., 2026) can hold entropy near a specific target, preventing this collapse, and pushing performance higher in follow-on tasks when the target entropy value is properly tuned.

every time i see a new "create a song from a single prompt" kind of product being rolled out i think about these comments from @David_Rudnick

oakwood studio is evolving

I work on a tool for working with the information in videos called reduct.video We just released "Videoboard," a 2d canvas for storyboarding + clustering. It lets you edit video on an infinite canvas—a “really non-linear” editor. Some background...

new paper up on arxiv!

What does a leading 𝗻𝗲𝘂𝗿𝗼𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 think about *causation*? Summary of some positions by Buzsaki in The Brain From Inside Out (ch 2). Plenty of discussions about causation but here we have someone at the very “center of the action” in neuroscience. 🧶