I think the general trend is that actual useful applications are emerging from enormous models trained and owned by billion dollar companies only. Even projects that aim to run models on private consumer hardware are dependent on commercial orgs to produce them. It doesn't seem like that is likely to change.
I don't think there are many positions/jobs/roles for people doing integral, foundational work that requires a deep understanding of ML. Becoming a world expert in ML will probably only open up opportunities at a dozen companies.
A very shallow surface-level understanding of ML already puts you leagues ahead of the general population. In terms of job security, figuring out how to use an ML API will get you hired faster than knowing how to advance the field.
We don't actually need that many Fabrice Bellards.