63-летняя Деми Мур вышла в свет с неожиданной стрижкой17:54
Work toward Gateway, a small space station that would orbit the moon and serve as a staging point for future missions, is not going away, officials said. But they made clear the agency’s priority is getting Artemis flights off the ground more often before building out that lunar outpost.
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前苹果与 Meta 高管庞若鸣加盟 OpenAI
他强调，未来用户不再需要逐个打开应用，而是通过一句话、一个指令，让 Agent 在后台完成所有跨应用的任务流程。
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.