SDSHNet: Dynamic feature fusion with transformer and star operation for efficient detection in aluminum alloys microscopic inclusion

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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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松下曾一度将电视业务列为考虑撤出或出售的「课题业务」,而此次与创维的全面合作,被内部视为摆脱这一困境的关键节点。(松下目前正在全球推进约 1.2 万人的裁员,但此次业务转移暂不涉及新的人员削减)