[syrrim]

This is a facile and pointless discussion. The hard work in building source code is paying millions of dollars to software engineers to write it. "Open source" allows others to benefit from this expenditure. The hard work in building an ai model is spending millions of dollars on training. "Open source" models allow others to benefit from this expenditure. Regardless of whether you had access to the complete training data and architecture of a model, you would never retrain from scratch in order to make a modification to the model. You would fine-tune in whatever behaviour you wanted. Just like open source software is when you are allowed to modify it, open source models are when you are allowed to fine tune like this.

[dspillett]

> Regardless of whether you had access to the complete training data and architecture of a model, you would never retrain from scratch in order to make a modification to the model.

Just because the concept is (currently) impractical in a given realm, doesn't mean we should just use the concept's name for something different in that realm, surely? Using the phrase "open source" for something that arguably isn't for essentially marketing purposes feels at best disingenuous.

Also, recreating from scratch is far from always the purpose of being able to see/investigate how something works and was created.

[ece]

Controlling how to train, not over fitting, making sure training data is good, and being able to do distributed training are all reasons why open weight isn't like open source. You can't fork during pre-training with open weight-only models.