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.
backpressure: 'strict' // or 'block', 'drop-oldest', 'drop-newest'
，这一点在搜狗输入法2026中也有详细论述
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"If we find out for example, that 60% of our young people are working in really hard physical labour, we will need to make sure that in 20 years time we've invested in physiotherapy," she said.。heLLoword翻译官方下载对此有专业解读