知情人士透露，该协议为一项跨越数年的长期租赁合同，旨在满足开发 AI 模型所需的庞大算力需求。
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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Leaked draft of $1bn memorandum of understanding reveals mandatory targets, sharing of data, and reported access to mining concessions
"cachedGrowthBookFeatures": {
Rust is Just a Tool