A.I. is on a collision course with white-collar, high-paid jobs — and with unknown impact::Technology has disrupted many workplaces. Artificial intelligence like ChatGPT may have an outsized impact on higher-paid office jobs, experts said.

  • astronaut_sloth
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    1 year ago

    This is one of the best takes I’ve seen for a while. LLMs seem like they are the “new Google” in that just searching for information super-charged productivity. Now, instead of using some google fu and having to wade through some links and read, someone can just ask a direct question to an LLM and get a reasonably good answer that may or may not need some work to fix up.

    In fact, I’ve started using GPT to summarize large reports/emails and generate the base code for projects so that I just have to tweak it. It has made work that would take hours or days into an hour or two. Honestly, GPT and Llama have made me a much more productive person. Understanding how to use LLMs to one’s advantage is going to be a skill going forward just like how effectively using a search engine is a skill now. It’s not a skill that will likely be appreciated (much like how effectively googling isn’t), but it will set workers apart.

    • j4k3@lemmy.world
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      1 year ago

      My favorite has been exploring models and obscure software that is challenging to get working. When I get the inevitable failure, I just paste the entire error message into a WizardLM 30B model and I usually get quite helpful insights. I’ve gotten much further into compilation and finished installing projects I never would have managed otherwise. It has expanded my bashrc, and commands knowledge substantially. Sed, awk, and regex are easy now. I can practically get an AI to exit vim for me.

      I just doubled the sysRAM in my machine 30min ago and am a quarter of the way into a 70B Llama 2 instruct GGLM. If the jump from 13B to 30B is any indication, this should be around 95%-98% accurate even with obscure technical questions.

      • astronaut_sloth
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        1 year ago

        Yeah! This is a great use! For me, I needed to get a prototype webapp with integrated prediction model up and working using various libraries, and I was way behind. Instead of just trudging through the documentation to learn how everything worked, I just had GPT-3 spit out a starting point, and then I just debugged from there and added features as needed. The only downside is that it’s made me impatient with developing other software with private libraries.