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title: "[译] [1000] 第十章 开发小游戏"
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* Designing and programming a code-breaking logic game
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* Designing and programming a press-your-luck dice game
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* 在我们的程序中加入随机性
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* 设计并编程一个破解代码的逻辑游戏
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* 设计并编程一个冒险掷骰子游戏
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There are many reasons why people learn to program. Some people want to automate tedious tasks as we did in the previous chapter. Some people want to work with artificial intelligence as we did in Chapter 7. Other people want to make interactive websites, Android or iOS apps, or Alexa skills. There’s an endless amount of stuff that programmers can make.
Another popular reason to learn programming is to create games. For that reason, we thought we’d end our Copilot programming journey with you by designing two small computer games. The first is a code-breaking game where you use clues to identify the computer’s secret number. The second is a two-player dice game where each player needs to balance risk and luck to reach the required number of points before the other player does. Instead of using graphics and animation, these games use text. We’ve made this decision to help us stay focused on the game logic, rather than the way that the game is represented or the way that the player interacts with the games. Along the way, we offer some next steps if you are interested in taking your game-making abilities further. And don’t worry, your current skills are a great start to that!
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title: "[译] [1100] 第十一章 展望未来"
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* Using prompt patterns to write and explain code
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* Current limitations and future directions of generative AI tools
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* 应用提示词模式编写与解释代码
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* 生成式 AI 工具的现状限制及未来发展趋势
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In this final chapter, we want to give you a glimpse of the creative ways people are currently using generative AI tools like GitHub Copilot and ChatGPT. For example, it’s possible to make Copilot Chat ask you the questions, rather than the other way around. And it’s possible to make Copilot take on a different persona to be even more helpful to your current programming task. We’re going to keep this brief, and it’s not clear how much of this will become standard practice, but we want to take this opportunity to demonstrate the power of being creative with these new tools. We’ll also talk about some of the current limitations of generative AI tools (you’ve seen some of them already in this book!) and offer our thoughts on what may be next.
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在本书的终章,我们期望展示人们当前如何创造性地使用生成式 AI 工具,例如 GitHub Copilot 和 ChatGPT。比如,可以实现让 Copilot Chat 主动提出问题,而非单向交流。更进一步,还能让 Copilot 采取不同的身份,以便更好地适应你的编程任务。我们将保持简洁,尽管现在还不确定这些方法会在何种程度上成为常规操作,但我们希望借此机会展现出利用这些新工具进行创造性思维的潜力。此外,我们还将讨论生成式 AI 工具目前的一些限制(本书中已有所涉及),并就可能的未来趋势提供我们的见解。
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* 11.1 Prompt patterns
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* Determining which modules we need to write a given tool
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* Automating cleaning up emails that have > > > symbols
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* Automating cleaning up emails that have `> > >` symbols
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* Automating manipulating PDF files
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* Organizing your and your partner’s phone pictures in the same place
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* 探讨程序员编写工具的动机
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* 确定编写特定工具需要哪些模块
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* 自动清除含有 `> > >` 符号的电子邮件
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* 对 PDF 文件进行自动化操作
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* 把你及你伙伴的手机照片统一整理至同一位置
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Suppose that you’re responsible for creating 100 reports, one for each of 100 people. Perhaps you’re a teacher and need to send a report to each of your students. Perhaps you work for HR and need to send an annual assessment report to each employee. Regardless of your role, you have the problem of having to create these reports, and you decided to prepare your reports as .pdf files. You need a customized cover page for each report, too, and those cover pages are designed by one of your colleagues (a graphic design artist).
You and your colleague work independently, and finally, the job is done. Or wait, not so fast. Because now you have to put each cover page at the beginning of each of your reports.
At this point, a non-programmer might grit their teeth and start on the job, manually merging the cover page with the first report, the second cover page with the second report, and so on. That could take hours. Not knowing that there may be another way, a non-programmer may just power ahead until the job is done.
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