Epoch AI 发布 4 份基准评测审查：1 份通过，3 份存在缺陷

The 6–7 month gap is a quantified benchmark of how quickly open-weight models absorb frontier-level cyber offensive capability, a metric security teams and policymakers can use to set review timelines. Chinese open-weight models closing in on US closed models is the notable trend here, relevant to anyone comparing model sourcing for security-sensitive workloads across ASEAN and beyond.

官方账号Epoch AI@EpochAIResearch11 sourcesSource

Progress on a single long-horizon game is a proxy for how quickly agentic planning and decision-making capabilities are moving, and SpireClimb gives teams a repeatable way to measure that gap across model releases. Practitioners benchmarking agents on sequential decision tasks can use the difficulty tiers to compare models beyond static Q&A tests. Tracking which labs' models clear the hardest difficulty will be a useful signal in coming releases.

官方账号Epoch AI@EpochAIResearchSource

AI adoption in mathematics is measured here through paper acknowledgments rather than surveys, giving a harder signal of how embedded these tools have become in research workflows. Mathematicians, journal editors and research funders should watch which subfields cross the majority threshold next. Differential geometry's jump from 8% to 57% in two months is among the fastest adoption shifts documented in academic publishing.

官方账号Epoch AI@EpochAIResearch2 sourcesSource