AI 的形狀：崎嶇邊界、瓶頸與技術突進（以及為什麼 Nano Banana Pro 至關重要）
Original: The Shape of AI: Jaggedness, Bottlenecks and Salients
In this article, Wharton School professor Ethan Mollick takes a deep dive into the enormous gap between current AI technological…
沃頓商學院教授 Ethan Mollick 探討了 AI 發展的非線性特徵。他結合了著名的「崎嶇邊界（Jagged Frontier）」理論，並引入科技史學家 Thomas Hughes 的「反向突進（Reverse Salients）」概念，解釋為何強大的 AI 技術在實際應用中會遭遇瓶頸。Mollick 幽默地以虛構的「Nano Banana Pro」為例，說明解決特定工作流瓶頸的小型、專門化 AI 工具，其影響力往往大於一味追求強大卻泛用的通用大模型。
In this article, Wharton School professor Ethan Mollick takes a deep dive into the enormous gap between current AI technological development and actual real-world deployment. He argues that we cannot view AI through the lens of traditional linear technological progress — we must understand "the shape of AI."
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