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The gains illustrate how fundamental design choices compound: batching amortizes async overhead, pull semantics eliminate intermediate buffering, and the freedom for implementations to use synchronous fast paths when data is available immediately all contribute.
Phil Spencer began working at Microsoft as an intern in 1988 and became chief executive of Microsoft Gaming in 2022
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.