Seems to me that it's very hard to have a moat in LLMs without proprietary code, given that most of their training data is freely available. This is very different form the 2010's era of AI, where they were trained on large amounts of proprietary data that was specific to a given service and could not be replicated.

It's a lot easier to pat yourself on the back for releasing a paper about your techniques when your competitors can't replicate your service with it. I think that as generative AI models move past the hype phase into the competitive phase, they will be keeping a lot of innovation proprietary for at least a few years to maintain an edge over their competitors.

Let's just hope they don't move to patenting everything.

The point of OpenAI was that no single company would have a moat around LLM or foundation models in general. It was set as a non profit with this goal in mind and got money for it.

Whether Google pat itself on the back or not for releasing the paper no one could replicate, is not important, because an open research had never been their company’s goal. What happened is a for-profit company released a paper, that allowed a huge advantage to a company, whose mission was to ensure that no one has a huge advantage in the field. OpenAI was converted to for profit and established exclusive relationship with Microsoft.

Google fucked up and missed the train, but they can catch up. Much harder for smaller companies if as a result of this Fb, Google, etc AI research dept lock down their papers to tools to internal use only.