研究团队表示，三款模型基于相同的基础训练数据集，高一致率的结果符合预期。真正具备研究价值的是模型间25%的分歧部分，这种差异大概率并非源于模型对工具质量的独立判断，而是由基于人类反馈的强化学习（RLHF）调优策略不同，以及生成环节的专属微调差异导致。

Attackers used “technical assessment” projects with repeatable naming conventions to blend in cloning and build workflows, retrieving loader scripts from remote infrastructure, and minimizing on-disk ...

While the Windows maker did not attribute the activity to a specific threat actor, the use of VS Code tasks and Vercel ...

The thick client is making a comeback. Here’s how next-generation local databases like PGlite and RxDB are bringing ...

International Business Machines Corporation stock plunges; downgrade IBM to Hold as Anthropic's Claude Code threatens ...

Anthropic research shows developers using AI assistance scored 17% lower on comprehension tests when learning new coding libraries, though productivity gains were not statistically significant. Those ...

A critical OpenClaw flaw allowed malicious websites to connect to locally running agents, brute-force passwords without ...

Just like algae blooms in the ocean and pollen in the spring, there’s been an explosion in the past year or two of new software, related tools and lingo from the IT and mainstream/consumer side. Some ...

GitHub games are open-source projects for testing gameplay ideas, sharing code, and collaborating publicly outside ...

Scientists have developed a new way to help understand what happens in the body when people consume a plant product and the ...

Sample files for Azul are kept in a Simple Storage Service (S3) compatible binary large object (blob) store, and processed ...

Container instances. Calling docker run on an OCI image results in the allocation of system resources to create a ...