2026-03-06 00:00:00:03014367710http://paper.people.com.cn/rmrb/pc/content/202603/06/content_30143677.htmlhttp://paper.people.com.cn/rmrb/pad/content/202603/06/content_30143677.html11921 李强作的政府工作报告（摘登）
The obvious counterargument is “skill issue, a better engineer would have caught the full table scan.” And that’s true. That’s exactly the point! LLMs are dangerous to people least equipped to verify their output. If you have the skills to catch the is_ipk bug in your query planner, the LLM saves you time. If you don’t, you have no way to know the code is wrong. It compiles, it passes tests, and the LLM will happily tell you that it looks great.。新收录的资料对此有专业解读
。新收录的资料是该领域的重要参考
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ONNX 导出失败的根因是图里某处会把一个标量常量以没有 dtype（即 None） 的形式传给了 ONNX 导出器，导致 torch.onnx。_type_utils.JitScalarType.from_name 收到 None 并抛出 ValueError: Scalar type name cannot be None。这类情况常在用高级索引/原地赋值（tensor[index] = other、index_put、masked_scatter 等）时出现，导出器有时会把标量常量漏掉 dtype。。业内人士推荐新收录的资料作为进阶阅读