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[-] mountainriver@awful.systems 17 points 2 months ago* (last edited 2 months ago)

I have so far seen two working AI applications that actually makes sense, both in a hospital setting:

  1. Assisting oncologists in reading cancer images. Still the oncologists that makes the call, but it seems to be of use to them.
  2. Creating a first draft when transcribing dictated notes. Listening and correcting is apparently faster for most people than listening and writing from scratch.

These two are nifty, but it doesn't make a multi billion dollar industry.

In other words the bubble is bursting and the value / waste ratio looks extremely low.

Say what you want about the Tulip bubble, but at least tulips are pretty.

[-] dgerard@awful.systems 17 points 2 months ago

This is why you should never allow the use of the marketing term "AI", and instead always refer to the specific technologies.

The use case for the term "AI" is to conflate things that work (ML) with things that don't work (LLMs).

[-] mountainriver@awful.systems 4 points 2 months ago

Ok, point on language.

But I thought LLMs were machine learning, or rather a particular application of it? Have I misunderstood that? Isn't it all black boxed matrixes of statistical connections?

[-] dgerard@awful.systems 2 points 2 months ago

they're related in that sense, but what they learn is which token to generate next.

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this post was submitted on 07 Sep 2024
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