AI并非编程抽象层的向上延伸，而是横向跃迁——用自然语言定义意图，训练模型“编译”数据，彻底颠覆“写程序”的传统认知。
Article URL: https://www.sixsideddice.com/Blog/Thoughts/SidewaysNotUpWhyAIIsNotANewAbstractionLayer.html Comments URL: https://news.ycombinator.com/it…
从根本论证AI不能靠提示词变聪明，揭示大模型的能力天花板与代码本质。
Article URL: https://www.theregister.com/ai-and-ml/2026/06/14/ai-is-code-and-cant-be-prompted-into-being-smarter/5254141 Comments URL: https://news.yc…
AI无法拥有欲望，这正是人类创造力的源泉——来自一个对AI本质的犀利洞察。
Article URL: https://www.troywolters.com/blog/ai-cannot-desire.html Comments URL: https://news.ycombinator.com/item?id=48498646 Points: 1 # Comments: …
探讨AI本质，指出特定机器学习模型无法实现通用计算的深刻洞见
Article URL: https://www.gabrielpickard.com/posts/ai-is-computation/ Comments URL: https://news.ycombinator.com/item?id=48388219 Points: 2 # Comments:…
AI的本质一直是概率问题？这篇讨论从序列模型到通用AI的模拟路径，引发对统计学习深层的反思。
AI was always a probability problem.. If we look at the emergence of sequence models (or statistical learning in broader sense), they predict the next…