Is this not what's referred to as an open-data (& open-source) solution?
- Open Source: The architecture of the model is available, so you can bring your own data and compute to train a similar model.
- Open Weights: The trained model itself is available for you to use. You can download it and run it on your own hardware without needing to train anything from scratch.
- Open Data: You get access to the data that was used to train the model. With this, you can completely reproduce the training process, which is super helpful if you want to fine-tune the model or see exactly how it was trained.
There are some other nuances around hyperparams, training methodology, etc. but that's basically the 3 main categories.
I think open-weight is somewhere between open source and binary.
Reason: cannot be reproduced or practically modified without the source data collection.
The difference between metas llama and open ai is akin to the difference between ms excel installed on your machine and google sheets running in the cloud.
From the point of view of academia, free transformative products that build on other stuff, transparency, possibility of building even better models in the future and a big etc, there's NO difference between ms excel and Google sheets.
OTOH, the llama models have allowed all of the above and has helped us immensely in both developing new things and being able to understand these new generation of LLMs...all of which would be impossible with openai.
Open weight means you get both the details of the architecture and a way to freely iterate to build new things.
For example, Minecraft was never distributed with source code, it was binary-only from day one. But the modding community would hard disagree with you if you say there was no way to "freely iterate to build new things", probably in GenZ term, "skill issue" :p
... but they did not specify their pov?