今天（3/14）在X.com上看到吴恩达大神 NG Wu 关于AI时代程序员如何应对的一些观点，非常有道理，复制到这里并随便做了人机翻译和大家共勉： 
“ 我最常被问到的一个问题是,应该做什么,谁担心人工智能会取代工作。 我的回答是:了解人工智能并控制它,因为未来最重要的技能之一将是能够准确地告诉计算机你想要什么,所以它可以为你做到这一点。 编码(或让AI为你编码)是做到这一点的好方法。” 
Some people today are discouraging others from learning programming on the grounds AI will automate it. This advice will be seen as some of the worst career advice ever given. I disagree with the Turing Award and Nobel prize winner who wrote, “It is far more likely that the programming occupation will become extinct […] than that it will become all-powerful. More and more, computers will program themselves.” Statements discouraging people from learning to code are harmful!
今天,有些人正在阻止其他人学习编程,理由是人工智能将实现自动化。 这个建议将被视为有史以来最糟糕的职业建议。 我不同意图灵奖和诺贝尔奖获得者,他写道:“编程职业灭绝的可能性要大得多,而不是它将变得全能。 越来越多的计算机会自己编程。”阻止人们学习代码的说法是有害的!
In the 1960s, when programming moved from punchcards (where a programmer had to laboriously make holes in physical cards to write code character by character) to keyboards with terminals, programming became easier. And that made it a better time than before to begin programming. Yet it was in this era that Nobel laureate Herb Simon wrote the words quoted in the first paragraph. Today’s arguments not to learn to code continue to echo his comment.
在20世纪60年代,当编程从打孔卡(程序员不得不费力地在物理卡上打孔,按字符编写代码字符)转移到带有终端的键盘时,编程变得更容易。 这比之前开始编程的时间更好。 然而,正是在这个时代,诺贝尔奖获得者赫伯·西蒙写了第一段引用的文字。 今天不学习代码的论点继续回应他的评论。
As coding becomes easier, more people should code, not fewer!
随着编码变得更容易**,更多的人应该编码,而不是更少**!
Over the past few decades, as programming has moved from assembly language to higher-level languages like C, from desktop to cloud, from raw text editors to IDEs to AI assisted coding where sometimes one barely even looks at the generated code (which some coders recently started to call vibe coding), it is getting easier with each step.
在过去的几十年里,随着编程从汇编语言转向高级语言,如C,从桌面到云,从原始文本编辑器到IDE,到AI辅助编码,有时人们甚至很少查看生成的代码(一些程序员最近开始称之为vibe编码),每一步都变得更容易。
I wrote previously that I see tech-savvy people coordinating AI tools to move toward being 10x professionals — individuals who have 10 times the impact of the average person in their field. I am increasingly convinced that the best way for many people to accomplish this is not to be just consumers of AI applications, but to learn enough coding to use AI-assisted coding tools effectively.
我之前写道,我看到精通技术的人协调人工智能工具,以迈向10倍的专业人士 - 个人的影响是普通人在其领域的影响的10倍。 我越来越相信,对于许多人来说,实现这一目标的最佳方式不仅仅是成为人工智能应用程序的消费者,而是学习足够的编码,以有效地使用人工智能辅助的编码工具。
One question I’m asked most often is what someone should do who is worried about job displacement by AI. My answer is: Learn about AI and take control of it, because one of the most important skills in the future will be the ability to tell a computer exactly what you want, so it can do that for you. Coding (or getting AI to code for you) is a great way to do that.
我最常被问到的一个问题是,应该做什么,谁担心人工智能会取代工作。 我的回答是**:了解人工智能并控制它,因为未来最重要的技能之一将是能够准确地告诉计算机你想要什么,所以它可以为你做到这一点。 编码(或让AI为你编码)是做到这一点的好方法。**
When I was working on the course Generative AI for Everyone and needed to generate AI artwork for the background images, I worked with a collaborator who had studied art history and knew the language of art. He prompted Midjourney with terminology based on the historical style, palette, artist inspiration and so on — using the language of art — to get the result he wanted. I didn’t know this language, and my paltry attempts at prompting could not deliver as effective a result.
当我在为每个人制作生成AI课程时,我需要为背景图像生成AI艺术品,我与一位研究过艺术史并了解艺术语言的合作者合作。 他促使Midjourney使用基于历史风格,调色板,艺术家灵感等的术语 - 使用艺术语言 - 以获得他想要的结果。 我不认识这种语言,我对提示的微不足道的尝试无法产生有效的结果。
Similarly, scientists, analysts, marketers, recruiters, and people of a wide range of professions who understand the language of software through their knowledge of coding can tell an LLM or an AI-enabled IDE what they want much more precisely, and get much better results. As these tools are continuing to make coding easier, this is the best time yet to learn to code, to learn the language of software, and learn to make computers do exactly what you want them to do.
同样,科学家,分析师,营销人员,招聘人员以及通过编码知识了解软件语言的广泛专业人士可以更准确地告诉支持AI的IDE,并更准确地告诉支持AI的IDE,并获得更好的结果。 由于这些工具继续使编码更容易,这是学习编程,学习软件语言以及学习使计算机完全按照您希望他们做的事情的最佳时机。
[Original text: https://deeplearning.ai/the-batch/issue-292/ ]
