Are you a developer looking for ways to improve your coding efficiency?
Artificial Intelligence (AI) is rapidly changing the way we work, and developers are no exception. With the help of AI-based tools, developers can increase their productivity, write better code, and stay up-to-date with the latest advancements in the field. In this article, we will take a look at 11 AI tools for developers that can help them code smarter and faster.
Tabnine
website: https://www.tabnine.com/
Tabnine is a powerful AI-based code completion tool that enhances the auto-completion feature of integrated development environments (IDEs). This tool supports over 20 languages and 15 editors, including popular IDEs such as VS Code, IntelliJ, Android Studio, and even Vim. Although it is not an end-to-end code generator, Tabnine provides developers with extended snippet proposals and targeted line code completions based on context and syntax, offering comprehensive line code completions and natural language to code. It is considered as the main competitor of Github Copilot, which is another AI-based code completion assistant. Tabnine offers a free version with limited features and a paid version at $12/month.
Polycoder
website: https://github.com/VHellendoorn/Code-LMs
Polycoder, developed by researchers at Carnegie Mellon University, is an open-source alternative to OpenAI's Codex. It is based on OpenAI's GPT-2 model and is trained on a 249 GB codebase in 12 programming languages. The authors of Polycoder claim that it can write C code with greater accuracy than any other model, including Codex. Unlike many code generators, Polycoder is open-source and allows users to customize the code generated according to their specific requirements. Additionally, Polycoder has the capability to generate code in multiple programming languages and can be integrated with other tools and platforms to assist developers in their coding tasks. The model also allows users to fine-tune the generated code, making it more human-like. This ability to fine-tune code is an important feature that sets it apart from other code generation models.
CodeT5
website: https://github.com/salesforce/CodeT5
CodeT5 is an open-source programming language model built by researchers at Salesforce. It is based on Google's T5 (Text-to-Text Transfer Transformer) framework, which is a powerful machine learning model that can generate human-like text. In order to train CodeT5, the team sourced over 8.35 million instances of code, including user comments, from publicly accessible GitHub repositories. A majority of these datasets were derived from the CodeSearchNet dataset, which includes popular programming languages such as Ruby, JavaScript, Go, Python, PHP, C, and C#, in addition to two C and C# datasets from BigQuery. CodeT5 can bring several capabilities to software programming, including:
- Text-to-code generation: CodeT5 can generate code based on natural language descriptions, making it easier for developers to express their ideas in code.
- Code autocompletion: CodeT5 can complete the whole function of code given the target function name, which can save developers a lot of time and effort.
- Code summarization: CodeT5 can generate a summary of a function in natural language description, which can be useful for developers who want to understand the functionality of a specific code snippet or for users who want to understand the functionality of a codebase quickly.
Additionally, it's worth mentioning that, CodeT5 is not only a powerful tool for developers but also for researchers and academics who can use this model to improve their research in natural language processing and machine learning.
Open AI Codex
website: https://openai.com/blog/openai-codex
The OpenAI Codex is a model that has been developed based on GPT-3 and is used to power GitHub Copilot, a tool from GitHub that allows developers to generate code within mainstream development environments such as VS Code, Neovim, JetBrains and even in the cloud with GitHub Codespaces. As per the claims, it is able to write code in at least a dozen languages including JavaScript, Go, Perl, PHP, Ruby, Swift and TypeScript, and even BASH. The Codex model is trained on a large number of lines of code that are available in the public domain, such as GitHub repositories. It is available for developers and platform companies through a private beta, for building tools and integration.
