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今天10月15日周四1 条
10月14日周三
10月13日周二
  1. MIT Technology Review · AI38

    开放模型利大于弊吗?Anthropic 称 GLM-5.3 构成重大网络攻击风险引发争论

    Anthropic 发布报告称,中国公司 Z.ai 于 8 月发布的开放模型 GLM-5.3 可被任何人自由下载和修改,构成重大网络攻击风险。这场争论的核心是前沿模型应像 GLM-5.3 一样开放,还是留在前沿实验室内部;Nvidia CEO Jensen Huang 主张美国发展更多开放模型,Anthropic 的 Dario Amodei 则主张更谨慎。

10月12日周一
  1. clem 🤗18

    如果你是研究者,请考虑公开分享你的 RL 环境!你为某个实验搭建的东西,可能帮助整个领域向前推进。 我知道在美国前沿实验室分享正处在黑暗时期,但我相信这能对领域和世界产生巨大影响!

    引用Naveen@NaveenKumar__T

    This is how open source should work. A closed lab publishes research, and within days the community turns it into training environments anyone can use. Early and rough, as Clem says, but the direction is lovely. #OpenSource #AI

9月27日周日
  1. vitalik.eth36

    Lean 共识将会非常出色。

    引用Francesco@fradamt

    One step closer to 4-8x faster Ethereum finality! It took some time and lots of tokens, but we now have a formally verified proposal for a decoupled consensus protocol in I* (a future Ethereum upgrade)! Not yet a full spec (up next), but it includes all the key consensus-relevant details to become one. Since Ethereum aspires to be live without most of the stake online, the protocol involves many more components than a normal BFT protocol, and its correctness involves much more than standard safety and liveness. Those nuanced properties are now verified! What's more, I came away convinced that all protocol design will involve AI-assisted Formal Verification in the future, both for correctness and iteration speed. The work wasn't limited to just: Design the protocol -> Formally verify it Instead, the loop became more like: Design -> Formal Model -> Find exactly what breaks and why -> Redesign it. For a fairly complicated protocol like this one, I think having the Lean model be part of the design loop played a big role in accelerating the process. A future with agents paired with formal models is a superpower for Ethereum development, because they can then use those models to find exactly where an argument breaks down, formalize counterexamples, test proposed fixes, iterate on the protocol. Many details that would slip under the radar when asking agents (and indeed, humans) can now be specified exactly and checked by the Lean kernel. This then forces agents to be more precise and lets them make verifiable progress on their own. It's been incredible to see this play out, seeing agents find gaps and propose protocol changes to fix them. In other words, autoresearch can speed up protocol design, formal verification is here to stay, and Ethereum Finality will get faster.

9月25日周五
8月24日周一
  1. Andrew Ng62

    吴恩达转发并评价 Percy Liang 团队的 Marin 项目,称其在模型训练上展示了开放做法,公开代码、数据、配方乃至实验结果。被引内容显示,Marin 535B-A23B 本周启动训练,预训练占 80%、中期训练占 20%,共 18.75T tokens,使用 11 台 GB200 NVL72,约 3 个月完成,算力规模 2.7e24 FLOPs,后续还有后训练。启动前团队先跑了从 1.6B-A61M(48B tokens)到 27.7B-A1.2B(926B tokens)的四级扩展阶梯以排查问题并预测主训练结果。

    引用Percy Liang@percyliang

    🚢 Marin 535B-A23B started training this week! As usual, the whole process is open. Voyage plan: pretraining (80%) + midtraining (20%) on 18.75T tokens on 11 x GB200 NVL72 for ~3 months (2.7e24 FLOPs). Post-training will follow. Before kicking off the run, we trained a 4-rung scaling ladder from 1.6B-A61M (48B tokens) to 27.7B-A1.2B (926B tokens) to debug issues, and to make a forecast of our hero run. This is by far our biggest run, so definitely expecting the unexpected.