LLMs have transformed how we write code, but they’ve also created new frustrations. We’ve all been there: staring at a huge AI-generated diff with no clue if it’s actually right. AI fooling us with code that seemed to work but was subtly wrong. Tests that all passed but didn’t actually test anything meaningful. The whole point of LLMs is producing text that looks correct - and that’s exactly what makes validation so hard.
这一调整的效果，已在2026年“两高”工作报告中有所体现。
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三是脆弱的护城河： 今天用户觉得Kimi的长文本好用，明天智谱清言更新了功能，后天千万发出了十几亿红包......用户立马切换阵营，毫无忠诚度可言。
这一循环与更大的媒介内容生态是相辅相成的。当NPD概念因为综艺节目大火时，类似“教你快速判断一个人是不是NPD”“来细数一下我遇到过的NPD的特点”“NPD的血包特质以及怎么破”等标题的帖子，也在社交平台上获得极大的传播声量，有关NPD评估测试也会明显增多。