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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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Сейчас в городе закрыты школы, разрушены многие больницы. Экстренные службы занимаются восстановлением города.
第八条 国家鼓励、扶持人工智能等网络犯罪防治技术的研究开发和推广应用，强化对人工智能等新技术新应用的安全管理。
客人还是当年那些，80、90后的小姐已经出道。客人和小姐之间也开始出现代沟。Dora就好几次抱怨中年客人唱歌太大声、太难听。