If there’s been one recurring theme during the “AI” (read, language learning models) revolution, it’s that the tech sector and greedy financiers are prematurely rushing unde…

LLMs certainly hold potential, but as we’ve seen time and time again in tech over the last fifteen years, the hype and greed of unethical pitchmen has gotten way out ahead of the actual locomotive. A lot of people in “tech” are interested in money, not tech. And they’re increasingly making decisions based on how to drum up investment bucks, get press attention and bump stock, not on actually improving anything.

The result has been a ridiculous parade of rushed “AI” implementations that are focused more on cutting corners, undermining labor, or drumming up sexy headlines than improving lives. The resulting hype cycle isn’t just building unrealistic expectations and tarnishing brands, it’s often distracting many tech companies from foundational reality and more practical, meaningful ideas.

  • @[email protected]English
    42•5 months ago

    An LLM can somewhat smooth over variances in language without having to have all possible variances known just the valid options and the raw input.

    • I would like a Big Mac, no lettuce, no tomato, no cheese.
    • I would like a Big Mac, no vegies, hold the cheese.
    • I would like a Big Mac, no vegies, no dairy
      • @[email protected]English
        29•5 months ago

        Natural language is really messy… Could go through many variants on things. Then you get text to speech issues due to audio quality / accents… And you need an engine that can “best guess / best match” based on what it has or ask for clarification.

        Similarly you can ask for TWO of a complex thing: I would like Two… meals, with, XXXX