因此，崔元俊表示，公司正在评估该产品线的未来，后续机型并非板上钉钉之事。“人们在选择设备时有不同的品味、要求和标准，”他说，“我们尚未决定何时推出下一代产品，但仍在考虑中。”
FT Digital Edition: our digitised print edition。服务器推荐对此有专业解读
'The nation mourns' - Canada leaders react to school shooting。搜狗输入法2026对此有专业解读
Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.
We have tried in good faith to reach an agreement with the Department of War, making clear that we support all lawful uses of AI for national security aside from the two narrow exceptions above. To the best of our knowledge, these exceptions have not affected a single government mission to date.