Local privacy respecting inference can be worth it. I use a local model to log everything I do all week to automate my timesheet. I also have it do a bunch of other data tasks. I won't say that larger SOTA models wouldn't do these tasks better than a local model but PII is a concern and my employer wouldn't approve of me just setting tokens on fire everyday to do what I could do myself.
Not at all! My company has 100s of clients and we track time in 6 minute increments. I feed in my browser history, terminal logs, session scripts, calendar, git commits, etc etc into it and voila it produces a highly accurate timesheet in no time flat.
Automating it has been way better for me than the alternative of breaking my flow whenever I'm switching tasks to chart my time, or logging all my hours for the week in one sitting. Different strokes for different folks I suppose.
> My company has 100s of clients and we track time in 6 minute increments.
That’s an insane level of detail and I can understand why it makes sense to use an LLM to remove that busywork, otherwise you’d be spending half of your time on this bureaucracy.
For the company I would imagine it could be more cost efficient to stop being so onerous instead of burning tokens.