Thus, despite much effort, no gelling agent has yet been discovered that possesses all the properties and benefits of agar. Agar continues to be the best all-arounder: versatile, cheap, and established. And, if Gelidium agar should ever run out, and another colloid is not at hand, microbiologists could revert to culinary agar, which, although not as pure and transparent, offers a low-cost alternative to lab-grade agar.
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В жарких странах станет еще жарчеСовместный отчет Copernicus Climate Change Service и Всемирной метеорологической организации фиксирует, что 2024 год стал самым теплым годом за всю историю наблюдений в Европе. При этом ледники в Скандинавии и на Шпицбергене показали рекордные темпы потери массы, а среди синоптиков все чаще стало звучать словосочетание «тропические ночи», когда температура не опускается ниже 20 градусов Цельсия.
Жители Санкт-Петербурга устроили «крысогон»17:52。heLLoword翻译官方下载是该领域的重要参考
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.