Comment by petcat
21 hours ago
That's certainly one factor, yes. But even before getting to that part I think the bigger issues for Big Corp legal teams is mostly around the legal ambiguity of the models themselves. What representations are made about the training data? What jurisdiction governs the license? If somebody alleges that the model infringes their IP, what rights does AT&T have?
Counterparty risk is a lot more straight-forward to evaluate when dealing entirely within the US, with US companies.
To me, the legal concerns seem blown out of proportion. If you use open weight models (of dubious origin) to generate code, you can still verify them with code review and tests and other methods, used to verify human output, right? That is still a great win, maybe not as much as having AI write all the code, but that would be a reasonable point in control vs quantity spectrum for most solid and well made products.
But if you let LLMs talk to people (customers, for example) directly, then yes, you need an LLM provider that you can hold responsible.
Haven't american companies outsourced manufacturing to China for a long time now? I think they have enough experience with dealing with China.
My knowledge is a few years outdated by now, but I remember digging into this and realizing that most of the chinese open-source libs were license-washing software. E.g. PaddleOCR is licensed under Apache 2.0, a very permissive license, however its models were often-times built on/fine-tunes of less permissively licensed foundation models such as Microsoft's LayoutXLM (Creative Commons Attribution Non Commercial Share Alike 4.0). (Which in my laymans understanding is also a kind of viral license in that changes need to be shared back under a similar license?)
The link is annoying enough to find that I can imagine "Mea Culpa" being an effective enough strategy for businesses moving into the ML/AI field, changing their tune after they get caught, but matured their own software to stand on its own feet.