Write "reminders" to change "smart future" - GPT4 prompt words into the code to optimize the driver's seat experience

 

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In the new wave of front-end technology, the gradual maturity and development of Artificial Intelligence (AI) leads us forward. Among them, OpenAI's GPT4 provides us with a new possibility to help us optimize the code and make programming easier. In this article, we will explore together how to optimize our code by relying on GPT's prompt words within 1-2 minutes, and show our difficulty in exploring the code without GPT and the jaw-dropping brilliance after getting help.

In each case, we will analyze in detail the specific differences between the code before and after optimization by attaching the full code. At the same time, the key role played by each prompt word provided by GPT4 in the process will be analyzed in a simple and in-depth manner.

This is a technological journey of "collision and fusion of wisdom", a spiritual challenge of exploration and practice. Loaded with GPT4 intelligent prompts, we are speeding around the corner of technology, squandering all the clanging of codes, and advancing into the future of optimization.

The seemingly subtle optimization has become a milestone in the intelligent revolution; the seemingly simple reminder has built a bridge for human-machine cooperation. Now, you and I can shake the "impossible" one by one under the guidance of GPT4.

Many programmers may feel that the GPT series (BERT, GPT-3&4, etc.), as the AI ​​monster of language processing, seems to be very different from our daily code optimization work. But in fact, what GPT can learn and master from big data is not only vocabulary and grammatical rules, but also various algorithms and the mysteries of their optimization. Using GPT as your code tuning tool, you will find that your work efficiency will be greatly improved. Below, specific examples are used to illustrate how to use GPT prompt words for code optimization.

Sorting algorithm optimization

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Origin blog.csdn.net/lifetragedy/article/details/131703492