The presentation discusses the open-sourcing of a project called Net, which aims to help migrate legacy code and enhance developer cycles. The project includes high-quality data sets and tools for code generation, natural language processing, and code analysis. The goal is to create better solutions, improve existing code performance, and reduce errors and debugging. The project is being hosted on the Machine Learning Exchange, which provides data and AI asset catalogs and integrates execution engines for easy experimentation. The ultimate aim is to develop production AI systems that can automatically translate and modernize legacy code with minimal effort.
- The open-sourcing of the Net project aims to help migrate legacy code and enhance developer cycles
- The project includes high-quality data sets and tools for code generation, natural language processing, and code analysis
- The goal is to create better solutions, improve existing code performance, and reduce errors and debugging
- The project is being hosted on the Machine Learning Exchange, which provides data and AI asset catalogs and integrates execution engines for easy experimentation
- The ultimate aim is to develop production AI systems that can automatically translate and modernize legacy code with minimal effort