The distinction in this case is decidedly not trivial. Open weights are great, we can fine tune them and mold them to our needs. But we don't have the training code, training data, etc, to be able to reproduce or tweak things at a more fundamental level.

"But not everyone is going to spend the money or time to train their own models from scratch!" I hear you say. And there's some truth to that. But if we had truly open source LLMs, then AuroraGPT development would be fast tracked and we would have a fully government funded scientific frontier model instead of only fine-tuning models.