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.
The practical challenge is balancing the benefit of updates against the time investment required. You can't refresh every piece of content constantly, so prioritize based on importance and competitive pressure. Content that generates significant traffic or ranks well in AI responses deserves regular attention to maintain those positions. Content about rapidly changing topics needs more frequent updates than evergreen material. Content facing new competition from recently published articles needs refreshing to remain competitive.
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"We watch a weather report and our whole world crumbles around us - it's taken a toll on our health if I'm perfectly honest with you - it's taken over our lives," he said.
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