本文从原理到实践系统地分享了如何高效使用AI编程工具。涵盖其底层机制（如Token计算、工具调用、Codebase索引与Merkle Tree）、提升对话质量的方法（如规则设置、渐进式开发）、实际应用场景（如代码检索、绘图生成、问题排查），并推荐了结合AI的编码最佳实践，包括文档、注释、命名规范和安全合规，旨在帮助不同经验水平的开发者真正把AI工具用好。

Abstract: Transformer models, such as BERT, GPT, and ViT, have been applied to a wide range of areas in recent years, due to their efficacy. In order to improve the training efficiency of Transformer ...

Working with numbers stored as strings is a common task in Python programming. Whether you’re parsing user input, reading data from a file, or working with APIs, you’ll often need to transform numeric ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. You are free to share(copy and redistribute) this ...

I’m not a programmer. But I’ve been creating my own software tools with help from artificial intelligence. Credit...Photo Illustration by Ben Denzer; Source Photographs by Sue Bernstein and Paul ...

This is my implementation of a branch and price algorithm to solve the humanitarian aid distribution problem. This problem is a VRP with a specific objective function ...

Abstract: Mixed Integer Linear Programming (MILP) optimization is a critical NP-hard problem applied across various sectors. Although machine-learning-based strategies have used historical data and ...