While we're at the point where traditional software is pretty much fast enough for all but extreme use-cases, with LLM's it feels like we're back to the days where you press compile and go have a coffee or chat to your colleague.
While we're at the point where traditional software is pretty much fast enough for all but extreme use-cases, with LLM's it feels like we're back to the days where you press compile and go have a coffee or chat to your colleague.
It takes a lot of expensive hardware, and most people don’t have extreme enough requirements to recoup that investment.
That might change, but it would require either that hardware gets much cheaper or everyone’s demands for LLMs increase significantly.
And given how fast the hardware and software is evolving, I can easily imagine a future where we all have very capable models running on our own devices for an embedded intelligence layer that's doing most of the day-to-day tasks, and only have to outsource to a super-smart cloud model for specific things.