![]() ![]() When I learned to code, I participated in an activity where I gave a robot instructions on how to make a sandwich. Here's another illustration of prompt engineering: A large language model or LLM will behave similarly. As a result, you give a response to the prompt based on what you've learned. You can receive a prompt to write an essay about a time you overcame a challenge or a prompt to write about a classic book, such as the Great Gatsby. You can liken this concept to receiving a prompt for an essay. A prompt is a sequence of text or a line of code that can trigger a response from an AI model. Prompt engineering is the practice of giving an AI model specific instructions to produce the results you want. ![]() OpenAI Codex, a machine-learning model that can translate natural language into code, powers GitHub Copilot Under the hood, GitHub Copilot draws context from comments and code, instantly suggesting individual lines and whole functions. How does GitHub Copilot work under the hood? ![]() In this case, GitHub Copilot leverages context from the code and comments you write to suggest code instantly! With GitHub Copilot, you can convert comments to code, autofill repetitive code, and show alternative suggestions.
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