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I personally think it's a lot of bs

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[-] will_a113@lemmy.ml 35 points 9 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?”

[-] Daxtron2@startrek.website 11 points 9 months ago

ML literally is a subfield of AI

[-] will_a113@lemmy.ml 1 points 9 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 2 points 9 months ago

It's not a different discipline, an LLM is an example of a machine learning model.

[-] Lmaydev@programming.dev 1 points 9 months ago

LLMs are neural networks which is literally ML.

The LLM designation refers to what they are trained to do.

[-] Sanctus@lemmy.world 4 points 9 months ago

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.

this post was submitted on 04 Feb 2024
59 points (90.4% liked)

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