Anthropic's quotes in an interview with Time sound reasonable enough in a vacuum. "We felt that it wouldn't actually help anyone for us to stop training AI models," Jared Kaplan, Anthropic's chief science officer, told Time. "We didn't really feel, with the rapid advance of AI, that it made sense for us to make unilateral commitments… if competitors are blazing ahead."
第十二条 任何个人和组织办理互联网信息发布、即时通讯等服务，应当提供真实身份信息，不得实施下列行为扰乱网络实名制管理：，更多细节参见heLLoword翻译官方下载
India vs England，这一点在safew官方下载中也有详细论述
СюжетВступление Украины в ЕС:
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.