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.
An animated sequence quantised using error-diffusion dithering. Note the jittering artifacts present in the background.
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Unions argue that "one day less" can be good for energy, productivity and society, and that normalising four‑day patterns can keep people in work who might otherwise drop out altogether.
春节期间，北京亦庄，目之所及皆是鼓足干劲、奋力拼搏的蓬勃景象。
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