It seems like the killer apps for generative AI right now are:<p>1) Automating boring reading and writing tasks. Think marketing copy, recommendation letters, summarizing material, writing proposals, etc. LLMs are pretty good at this stuff but these are not many people's core job responsibilities (though they may take up a lot of their time). Consider it a productivity booster for the most part. Some entry level jobs will be eliminated, and this may create problems down the road as the pipeline of employees to oversee LLMs erodes.<p>2) Code writing tools a la Copilot for certain "boilerplate" code in commonly used languages. I think the impact is similar to (1) where entry level jobs erode and this may impact employee pipelines.<p>The core problem (as I see it) is that LLMs don't produce outputs good enough to be used without human oversight except on a small subset of tasks. So you end up needing humans (maybe fewer of them) to check the LLM output is headed in the right direction before you let it out into the world.<p>Consider voice interface LLMs for customer service. When will they get good enough to do the job with real money on the line? If your airline help desk keeps giving away free flights or on the flip side infuriating passengers by refusing allowed changes, can you really use it in production? My sense is they aren't good enough to replace the usual phone tree just yet.<p>When accuracy doesn't matter that much, LLMs will really shine because then they can be used without a human in the loop. Think some marketing/advertising and especially, especially propaganda.<p>I think the existing killer apps don't yet have enough money/savings in them to justify the spend. If generative AI technologies can get good enough on the accuracy front to remove humans from the loop in more contexts, we will be talking about much more dramatic value.