Proton is transitioning towards a non-profit structure | Proton
Proton is transitioning towards a non-profit structure | Proton
I think it might be because AI (aka LLMs) is genuinely useful when used properly.
I use AI all the time to write emails. I give the LLM the email thread along with instructions like “I can’t make it Tuesday ask if they can do Wednesday at 2pm”
The AI will write out an email that’s polite and relevant in context. Totally worth it.
I think the problem is people/companies trying to shove LLMs where they don’t make sense.
Then just write that.
I don’t understand why we’re having AIs verboseify simple information?
Why do many word if few word do trick.
How long until we start using LLMs to summarize messages over-verbalized by LLMs?
And offloading the accounting for context WILL bite you in the ass. If you can’t remember what a discussion was about and what needs considering, you’re no longer doing the thinking.
Being formal and considerate does not require being that much more verbose.
Do you really save time running messages through an LLM vs just writing them as you think of what to say?
The LLM responses are more verbose but not a crazy amount so. It’s mostly adding polite social padding that some people appreciate.
As for time totally. It’s faster to write “can’t go to meeting, suggest rescheduling it for Thursday.” And proofread than to write a full boomer style letter.
I feel like we might write at very different WPMs. For me, proofreading and fixing AI slop takes longer than just writing things myself.
And another difference might be that to me and everyone I work with, writing in full on “boomer” is considered an insulting waste of everyone’s time.
Which it is.
It’s a waste of everyone’s time for sure. It’s just good business sense to make your customers happy though.
As for typing speed perhaps ya lol. You could be faster. But I think the best approach here is using high quality locally run LLMs that don’t produce slop. For me I can count on one hand how many times I’ve had to correct things in the past month. It’s a mater of understanding how LLMs work and fine tuning. (Emphasis on the fine tuning)