Hi all. I wanted to flag that the openai from today 09.07.2026 stopped returning thinking summaries on the codex endpoint. All is "normal" on the api endpoint.<p>I don't know if this is a/b or geographic testing.<p>Take this as you will.
Reading a paper means opening a PDF, then hunting separately for the code, the citations, whether it replicated, and what genes/drugs it touches. I spent a few months trying to fix that.Two parts:1. The map: I embedded 8.5M papers (arXiv, PubMed Central, bioRxiv, medRxiv), ran UMAP to lay them out in 2D, and render them with a WebGL scatterplot. Every dot is a paper — click it for an LLM TLDR, key findings, citations, peer reviews (where they exist), and similar work. Zoom in and the cluste
This is a reinforcement learning environment I made for post-training large language models that are already post-trained on coding and math. Optimization problems in general are good verifiable reward problems, with lots of intermediary rewards because even relatively simple algorithms can solve very easy instances while superhuman-level algorithms, similar to what OpenAI displayed with the Heuristic Programming Contest yesterday, are the end state after substantial post-training. AES inversion
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