improve coding efficiency by suggesting code snippets based on context
In recent years, LLMs have shown significant improvements in their overall performance. When they first became mainstream a couple of years before, they were already impressive with their seemingly human-like conversation abilities, but their reasoning always lacked. They were able to describe any sorting algorithm in the style of your favorite author; on the other hand, they weren't able to consistently perform addition. However, they improved significantly, and it's more and more difficult to find examples where they fail to reason. This created the belief that with enough scaling, LLMs will be able to learn general reasoning.
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虽然说匠人精神并不会马上消失，但“只做匠人”正在变得性价比极低。
Поводом для разбирательства стал кавер на трек, размещенный на нескольких сайтах, в котором были полностью изменены оригинальные слова. Проведенное по запросу надзорного ведомства лингвистическое исследование выявило в тексте признаки унижения человеческого достоинства, а также возбуждения ненависти и вражды по отношению к российским военнослужащим, участвующим в специальной военной операции.