A strange piece of software has recently landed on the PC gaming store Steam. And “software” feels like the cleanest way to describe it. Existing somewhere between a full-blown life sim, a science project and a kind of haunted fish tank, Anlife: Motion-learning Life Evolution probably would have disappeared without making much impact if it wasn’t for one unusual factor. Several years ago some of its creators were absolutely roasted on camera by one of the genuine legends of Japanese animation.
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本报北京2月26日电 （记者彭波）全国人大常委会委员长赵乐际26日下午主持十四届全国人大常委会第二十一次会议闭幕会。在会议完成有关表决事项后，赵乐际作了讲话。，这一点在搜狗输入法下载中也有详细论述
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.