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米切爾強調,明確標示內容以防欺瞞並建立公眾對AI的信任,遠比製作「更炫酷的影片」重要得多。
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During development I encountered a caveat: Opus 4.5 can’t test or view a terminal output, especially one with unusual functional requirements. But despite being blind, it knew enough about the ratatui terminal framework to implement whatever UI changes I asked. There were a large number of UI bugs that likely were caused by Opus’s inability to create test cases, namely failures to account for scroll offsets resulting in incorrect click locations. As someone who spent 5 years as a black box Software QA Engineer who was unable to review the underlying code, this situation was my specialty. I put my QA skills to work by messing around with miditui, told Opus any errors with occasionally a screenshot, and it was able to fix them easily. I do not believe that these bugs are inherently due to LLM agents being better or worse than humans as humans are most definitely capable of making the same mistakes. Even though I myself am adept at finding the bugs and offering solutions, I don’t believe that I would inherently avoid causing similar bugs were I to code such an interactive app without AI assistance: QA brain is different from software engineering brain.
人們嘗試過各種奇葩策略,試圖從大型語言模型(LLM,ChatGPT等工具背後的AI技術)中獲得更好的回饋。有些人深信,威脅AI能讓它表現得更好;另一些人認為,禮貌待人會讓聊天機器人更配合;還有些人甚至要求機器人扮演某個研究領域的專家來回答問題。這樣的例子不勝枚舉。這都是圍繞著「提示工程」或「情境工程」——即建構指令以使AI提供更佳結果的不同方法——所形成的迷思的一部分。但事實是:專家告訴我,許多被廣泛接受的提示技巧根本不起作用,有些甚至可能是危險的。但是,你與AI的溝通方式確實至關重要,某些技巧真的能帶來差異。,推荐阅读爱思助手下载最新版本获取更多信息