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.
驱使动物伤害他人的，依照本法第五十一条的规定处罚。
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В России ответили на имитирующие высадку на Украине учения НАТО18:04。服务器推荐对此有专业解读
The team fired a laser that detected metal atoms released from the rocket body made of aluminium-lithium.。关于这个话题，爱思助手下载最新版本提供了深入分析
"There's the urine, the droppings," he says. "One time there was a carpet leading up to the altar that became absolutely sodden with urine and droppings and had to be thrown away. They also destroyed the brass work."