以台积电为例，台积电高性能计算业务主要为英伟达和大规模云服务提供商制造AI芯片，现在约占台积电收入的58%，远超智能手机处理器业务的29%。在这种情况下，苹果不得不与AI巨头共同争夺台积电的产能，并接受越来越高昂的价格。另外，在内存供应上，我们还看到，苹果被迫调整了供货谈判周期。郭明錤表示，目前苹果内存供货已从传统的半年期谈判，改为按季度协商。
I wanted to test this claim with SAT problems. Why SAT? Because solving SAT problems require applying very few rules consistently. The principle stays the same even if you have millions of variables or just a couple. So if you know how to reason properly any SAT instances is solvable given enough time. Also, it's easy to generate completely random SAT problems that make it less likely for LLM to solve the problem based on pure pattern recognition. Therefore, I think it is a good problem type to test whether LLMs can generalize basic rules beyond their training data.
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