AI能獨立寫App？深入理解Google與OpenAI的AI程式碼代理人，是助手還是災難？
從Google到OpenAI，AI程式碼代理人能自動開發軟體、除錯。本文深入解析其核心技術LLM的運作原理、潛在風險，以及開發者如何善用這項新工具。
AI已能自主編寫軟體。從 OpenAI、Anthropic 到 Google，新一代的AI程式碼代理人已能在人類監督下，連續工作數小時，完成從撰寫完整應用程式、執行測試到修復錯誤的複雜任務。然而，這些工具並非萬能丹，若不慎使用，不僅無法簡化專案，反而可能使其盤根錯節，更加複雜。
深入理解其底層運作原理，是幫助開發者判斷何時（以及是否）該使用它們，並避開常見陷阱的關鍵。
揭開黑盒子：AI代理人的核心引擎
所有AI程式碼代理人的核心，都是一種稱為大型語言模型（LLM）的技術。這是一種在包含大量程式碼的龐大文本數據上訓練出來的神經網路。它的本質是一部「模式匹配機器」，利用提示（prompt）來「提取」其在訓練期間學習到的壓縮統計表徵，並以最合理的模式延續作為輸出。
在這個提取過程中，LLM能夠在不同領域和概念之間進行內插，表現良好時能產生有用的邏輯推論，但表現不佳時則會產生看似真實的「杜撰錯誤」（confabulation errors）。
從蠻力到精準：模型的後天調校
這些基礎模型會透過微調（fine-tuning）和人類回饋強化學習（RLHF）等技術進一步完善。透過精選範例的訓練與人類的回饋，模型被塑造得更善於遵循指令、使用工具，並產出更有價值的結果。
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