This is an proposal for how to label code that is AI-generated from code that is human authors.
These annotations are useful for human-driven code review, allowing code reviews to have more context on where the code is coming from. These annotations are also useful for AI and code applications. AIs can find places generated code can be optimized and future models can better distinguish generated code from human code.
| /** | |
| * This file contains AI generated code. Generated code exists | |
| * between the BEGIN AI SECTION and END AI SECTION designators. | |
| * | |
| * @ai-generated model=openai.gpt-4 | |
| */ | |
| import React from "react"; | |
| interface Person { | |
| name: string; |
| """ | |
| Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
| BSD License | |
| """ | |
| import numpy as np | |
| # data I/O | |
| data = open('input.txt', 'r').read() # should be simple plain text file | |
| chars = list(set(data)) | |
| data_size, vocab_size = len(data), len(chars) |
I hereby claim:
To claim this, I am signing this object:
I hereby claim:
To claim this, I am signing this object:
