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Harpreet Matharu said there was a higher donation consent rate for patients who had discussed their wishes with their loved ones
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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.
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The library project, on the other hand, contains the actual core gameplay logic. In the inventory service's case, this includes the C# classes that model the request and response for every API operation as well as the underlying logic for handling the countless inventory related systems such as crafting, quests, loot, etc. As a separate project, the library can be imported in other services when we need to reuse that logic without pulling in any of the web project's code.
Opens in a new window。91视频是该领域的重要参考