• TommySoda@lemmy.world
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    3 years ago

    I have nothing against the people that are working on AI and appreciate the work they do. However every time I see an article about a company using AI like this I just get the vibe that it’s a bunch of middle aged men trying desperately to make things like the “future” they saw when they were a kid. I’ve seen amazing implementations of AI in a lot of different ways but I’m so sick of dumb ideas like this because some guy that used to watch Star Trek as a kid wants to feel like they live in the future while piggybacking on someone else’s work. It’s like the painted tunnel in cartoons where it looks like a real tunnel but in reality it’s just a very convincing lie. And that’s all that it is. Complexity does not mean sophistication when it comes to AI and never has and to treat it as such is just a forceful way to make your ideas come true without putting in the real effort.

    Sorry, I had to get that out. Also I have nothing against Star Trek and I used to watch it as a kid because my parents watched it all the time.

    • Thorned_Rose@kbin.social
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      3 years ago

      some guy that used to watch Star Trek as a kid wants to feel like they live in the future while piggybacking on someone else’s work.

      I don’t think they care about their own nostalgia. I think they ant to use other people’s dreams to make a lot of money. I’m also sure some of them genuinely just ant to push the technological envelope just cause they can, ethics be damned. But ultimately, it’s just money.

      I would love nothing more than the utopian future Trek promised but greed is killing it.

      • njordomir@lemmy.world
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        3 years ago

        I’m not sure I understand. Do you mean hearing codewords triggering actions as opposed to trying to understand the users intent through language? Or is are there a few more layers to this whole thing than my moderate nerd cred will allow me to understand?

          • Kogasa@programming.dev
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            3 years ago

            Semantic embeddings are a thing. LLMs “work with tokens” but they associate them with semantic models internally. You can externalize it via semantic embeddings so that the same semantic models can be shared between LLMs.