Decentralized inferencing perhaps, but the training is very much centralized around Metas continued willingness to burn obscene amounts of money. The open source community simply can't afford to pick up the torch if Meta stops releasing free models.
There's plenty of open source AI out there that isn't Meta. It's just not as good. The #1 problem is not compute, but data and the manpower required to clean that data up. The main thing you can do is support companies and groups who are releasing open source models. They are usually using their own data.
The #1 problem is absolutely compute. People barely get funding for fine tunes, and even if you physically buy the GPUs it'll cost you in power consumption.
That said, good data is definitely the #2 problem. But nowadays you can just get good synthetic datasets from calling closed model APIs or just using existing local LLMs to sift through trash. That'll cost you too.