Autocoding platforms have emerged as powerful tools for developers, employing large language models to generate code from natural language prompts. While these platforms offer great promise, concerns regarding their use of data have also arisen. For example, Microsoft has faced lawsuits for using GitHub repositories to train its Copilot algorithm without crediting the original developers. Amid these challenges, some autocoding platforms, such as Tabnine, prioritize responsibly-sourced datasets and user privacy, setting them apart from competitors like GitHub Copilot.
In an interview with Analytics India Magazine, Brandon Jung, VP Ecosystem and Business Development at Tabnine, highlights the benefits and challenges associated with responsibly-sourced datasets. According to Jung, relying
The Ethical Advantages of Responsibly-Sourced Autocoding Platforms
- By 理想
- Published on
Autocoding platforms have emerged as powerful tools for developers, employing large language models to generate code from natural language prompts. While these platforms offer great promise, concerns regarding their use of data have also arisen. For example, Microsoft has faced lawsuits for using GitHub repositories to train its Copilot algorithm without crediting the original developers. […]
