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THE DAILY INDEX

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TLDR AI — continued

RECENT OPENAI RESEARCH HAS DEMONSTRATED THE ABILITY OF LLMS TO SOLVE FRONTIER PROBLEMS IN MATHEMATICS

Researchers set out to find out how good frontier LLMs are at doing frontier theory research. They designed a prover-verifier workflow that used GPT-5.5 Pro as the solver and Claude Opus 4.7 as the verifier. This workflow was stress-tested on open problems from areas with very different levels of familiarity. The results were surprisingly strong and the system resolved a list of open questions.

MILES: A PYTORCH-NATIVE STACK FOR LARGE-SCALE LLM RL POST-TRAINING

Miles is a framework for large-scale LLM RL post-training. It makes frontier-scale LLM RL easier to build, reproduce, and operate. RL post-training has become a distributed systems problem as models have become larger and run across more distributed and specialized hardware. Miles makes large-scale LLM RL training more composable, reproducible, and easier to scale while keeping the core trainer small enough for researchers and infrastructure teams to customize.

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