📄 中文摘要
当前的人工智能并不具备真正的“思考”能力，而是作为一种统计估计引擎运作。它将概念投射到复杂的向量空间中，每个单词都是一个坐标。模型通过从数十亿个参数中计算概率来学习序列的延续。尽管这种架构性能优越，但也暴露了大型语言模型（LLMs）的固有限制。所谓的“幻觉”并不是神秘的错误，而是模型校准困难的表现。当人工智能生成事实错误时，问题并不仅仅在于信息不足，而是源于信心偏差：模型在数学上可以“确定”，但实际上却可能是错误的。
谦逊是否会成为人工智能的下一个前沿？
出处: What if humility were AI's next frontier?
发布: 2026年2月28日
📄 English Summary
What if humility were AI's next frontier?
Today's AI operates as a statistical estimation engine rather than 'thinking' in a human-like manner. It projects concepts into a complex vector space, treating each word as a coordinate. The model learns to predict the continuation of a sequence by calculating probabilities from billions of parameters. While this architecture is highly effective, it reveals the inherent limitations of large language models (LLMs). The phenomenon known as 'hallucinations' is not a mysterious bug but a symptom of the challenges in model calibration. When AI generates factual errors, the issue arises not solely from a lack of information but from a confidence bias: a model can be mathematically 'certain' while still being incorrect.