Open weights are not enough: we need open training frameworks for research and better algorithms [P]

1. 1Build open training frameworks that provide visibility into the training process
2. 2Run experiments using open frameworks to test and refine algorithms
3. 3Configure frameworks to make them modifiable and adaptable to different research needs
4. 4Test and evaluate the performance of new algorithms developed using open frameworks
5. 5Apply open training frameworks to real-world problems to drive innovation and progress in ML and AI

Researchers, engineers, and practitioners on a team can benefit from open training frameworks as they enable collaboration, transparency, and innovation in ML and AI development

💡 Open training frameworks are essential for advancing ML and AI research, as they enable the development of better algorithms and facilitate collaboration and innovation

🚀 Open training frameworks can accelerate ML & AI research by making training processes visible, understandable, and modifiable #OpenML #AIresearch