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.
スー・チー氏後継と目されたリーダーがなぜ軍主導の選挙に?
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Suppose you're building a map application. You have millions of restaurants, gas stations, and landmarks, each with a latitude and longitude. A user taps the screen and asks: "What's near me?"
Scientists have captured a beautiful image in unprecedented detail of the vast Milky Way galaxy, of which our own solar system is a part.
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Earlier today I set you these three problems about the number 11. Here they are again with solutions.，这一点在同城约会中也有详细论述