GANs are so much fun and so tedious. I trained one on dungeon generation in college. It sucked but it worked in the end mostly. I dont know exactly how an LLM works but GANs are way different.
Comment on Article suggests that 1 million ML specialists will be needed in 2027. What do you think of that?
will_a113@lemmy.ml 4 months ago
ML =/= AI. There are legit uses for ML that don’t have anything to do with LLMs and the cloud. I worked on an ML project 3 or 4 years ago to listen for fan noise that might indicate that it was about to fail soon. We trained a tiny GAN on good and bad noises. It runs on a tiny CPU, locally. Highly specialized work, and I have to imagine there are and will continue to be lots of similar opportunities to bring efficiencies by getting computers to make good observations and decisions - even if only about “simple” things like “does this thing seem like it’s about to break?”
Sanctus@lemmy.world 4 months ago
Daxtron2@startrek.website 4 months ago
ML literally is a subfield of AI
will_a113@lemmy.ml 4 months ago
Fair enough. ML ⊆ AI then. But these days when everyone talking breathlessly about AI taking away jobs they’re almost always taking about LLMs. This article is about ML in particular which is a different discipline with different applications.
infinitepcg@lemmy.world 4 months ago
It’s not a different discipline, an LLM is an example of a machine learning model.
Lmaydev@programming.dev 4 months ago
LLMs are neural networks which is literally ML.
The LLM designation refers to what they are trained to do.