Comment on The Generative AI Con.
jrs100000@lemmy.world 2 months agoIt will. So has just about every other major technical development ever. Eventually those lost jobs should be replaced by even more jobs made possible by the new technology, but in the meantime it will suck.
Thats how you know its not just a gimmick. How many jobs did blockchain replace? Just about zero. How many jobs did computers or the Internet or the mechanical loom or the freaking steam engine replace? Tons.
amino@lemmy.blahaj.zone 2 months ago
except genAI has proven no purpose. this is like saying “look at how many jobs bankers replaced! we just used to eat for free, now we have to work our entire lives for it or starve!”
jrs100000@lemmy.world 2 months ago
Im pretty sure most of us already have to work our whole lives or starve.
amino@lemmy.blahaj.zone 2 months ago
great, now enjoy that 10 times worse when genAI is used to make skeleton crews an even bigger issue and increase worker exploitation
Greg@lemmy.ca 2 months ago
Generative AI has spawned an awful amount of AI slop and companies are forcing incomplete products on users. But don’t judge the technology by shitty implementations. There are loads of use cases where when used correctly, generative AI brings value. For example, in document discovery in legal proceedings.
sem@lemmy.blahaj.zone 2 months ago
But is it worth the cost, and is it the best option? Everyone knows that the generative models are heavily subsidized by VC.
You could have other kinds of language processing and machine learning do document discovery better.
Greg@lemmy.ca 2 months ago
It is the best option for certain use cases. OpenAI, Anthropic, etc sell tokens, so they have a clear incentive to promote LLM reasoning as an everything solution. LLM read is normally an inefficient use of processor cycles for most use cases. However, because LLM reasoning is so flexible, even though it’s inefficient from a cycle perspective, it is still the best option in many cases because the current alternatives are even more inefficient (from a cycle or human time perspective).
Identifying typos in a project update is a task that LLMs can efficiently solve.