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Comment on Hertz' AI System That Scans for "Damage" on Rental Cars Is Turning Into an Epic Disaster

entropicdrift@lemmy.sdf.org ⁨3⁩ ⁨weeks⁩ ago

Agreed. But most people have neither the time nor capacity to track all of these specifics, so popular discussions of AI-related technologies inevitably break down into a mud pit of people talking past each other about various different topics.

Which, if you think about it, is true of most public discussions about any complex topic. It almost invariably revolves into a miscommunication or a discussion about semantics.

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sugar_in_your_tea@sh.itjust.works ⁨3⁩ ⁨weeks⁩ ago
People have the capacity to track genres and whatnot, what’s so different about this?

I think people could understand if explained probably, but unfortunately journalists rarely dive deeply enough to do that. It really doesn’t need to get too involved:

machine learning - tell an algorithm what it’s allowed to change and what a “good” output is and it’ll handle the rest to find the best solution

Bayesian networks - probability of an event given a previous event; this is the underpinnings of LLMs

LLM - similar to Bayesian networks, but with a lot more data

And so on. If people can associate a technology with common applications, it’ll work a lot more like genres and people will start to intuit limitations of various technologies.
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- entropicdrift@lemmy.sdf.org ⁨3⁩ ⁨weeks⁩ ago
  What’s different is that most people will see it as “tech stuff” and mentally file it in a drawer with spare extension cords and adapters. They don’t care to deeply study or catalog things.
  
  People writ-large don’t care about proper genre labels either, they just kinda pick a vibe and guess off of it. Look at all the -core suffixed aesthetic names that cropped up in the last decade.
  
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  - sugar_in_your_tea@sh.itjust.works ⁨3⁩ ⁨weeks⁩ ago
    Yeah, I think it’s unfortunate that tech is something people refuse to learn about. I’ve been able to explain technical topics to less technical people, they just need to care.
    
    For example, I’m into finance, and have been able to explain pretty complex topics (compounding, Social Security benefits, derivatives, etc) to people with no background in a way that they know how things work at a high level. They may not be able to trade options or predict portfolio performance, but they can at least tell if their “financial advisor” knows their stuff.
    
    Learning a bit about key technologies can help cut through the BS from marketing departments. But as soon as I mention something remotely technical, people shut down. If people understood that LLMs basically do keyword association to generate text from a prompt, they wouldn’t believe the lies that claim they “think.” Just a little bit of high level knowledge would change it from “magic” to a sometimes useful everyday tool.
    
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