> Many clearly think of the weights as a source-like artifact. I believe releasing the weights is necessary for an open-source AI project, but don’t consider t

> Many clearly think of the weights as a source-like artifact. I believe releasing the weights is necessary for an open-source AI project, but don’t consider the weights to be source. Indeed, open source is not just about the code. For instance, the OSI definition[0] states: > The license must allow modifications and derived works If a company released source code for a project, but it was written in a new language whose compiler they held private, then making derived works would be extremely hard. Someone would have to reverse engineer how the language works from source examples, and reimplement a compiler with a similar performance. In that case, in my view, while the code was open, the project would not be open-source. The same is true of AI models: people can certainly reverse-engineer the training code and replicate a training run to get the weights, but without the weights, the project is not open-source. On the flip side, if the inference code is open and has the weights public but the training code is not, it is similar to an open-source project using a proprietary compiler (think C# before 2014). The project is open-source, but the training is not. [0]: https://opensource.org/osd/ https://opensource.org/osd/