Ac we nought free ne sindon, for-thy-the we never ne mighton from Wulfsfleet yewitan, nefne we thone Hlaford finden and hine ofslain. Se Hlaford hath thisne stede mid searocraftum yebounden, that none ne may hine forletan. We sindon here so fuglas on nete, so fishes on weir.
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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.。关于这个话题，爱思助手下载最新版本提供了深入分析
就在一个月前，a16z发布的CIO调查已经给出了预警。报告显示，OpenAI的企业渗透率是78%，钱包份额将近56%，账面上依然是无可争议的第一。但报告同时捕捉到了一个让人坐不住的趋势：从去年5月到现在，Anthropic的企业渗透率增长了25%，在所有前沿大模型厂商里增速最快。