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@proxystudio.eth
do we have companies attributing worker productivity gains to gen AI? my anecdotal experience of trying to use LLMs for writing is... zero productivity gains, no experience of writing (or thinking) better, faster. can generate mediocre writing & conventional ideas endlessly, but turning that mid text into anything I'd want to publish feels harder than just being thinking & writing about something myself from the jump
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@kia.eth
this is honestly kind of stating the obvious. oh model trained on previous ideas isn't coming up with new ideas? or it doesn't write in the 99th percentile? where it is powerful and def does do productivity gain (for me): 1. writing dumbass website copy, blogs and FAQ that a college intern could write but somehow you find yourself in the position of not having an intern. 2. asking questions on a large and confusing body of text. i've used this a lot when writing new legal contracts. there's a lot of repetitiveness there and dependency on other contracts. like you're adding a new clause: does it conflict with anything else? 3. sparring partner for ideas that are going to generate on your own. don't know about you but I personally think either in sleep or in conversation. so the bottleneck for me coming up with new stuff is finding people that'll do active listening, point out logical fallacies or point out how what i'm talking about is in contradiction or support of previously established ideas.
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@kia.eth
so the productivity gain really isn't going to come from chatGPT interface used by top of the crop R&D folks. it'll come from specific tools designed for ops and support related roles where the tool takes an input and gives out an output -- not me training a GPT and talking to it for 3 hours.
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