I see a lot of discussion here about over-hyped AI, and then I see the huge AI bubble at my workplace, in news, in PR statements, etc.

Are there folks who work at companies – especially interested in those in tech – that have a reasonable handle on AI’s practical uses and its limitations?

Where I work, there’s:

  • a dashboard of AI usage by team and individual, which will definitely not affect performance review in any way
  • a mandate to use one AI tool last month, and this month a new one to abandon that tool and adopt a different one
  • quarterly goals where almost every one has some amount of “with AI” in it
  • letters from the CEO asking which teams are using AI to implement features from ticket descriptions, or (inspired by the news) use flocks of agents, asking for positives without mention of asking for negatives
  • a team creating a review pipeline for AI-generated output in our product, planning to review the quality of the output… using AI
  • teammates are writing code and designs and sending them for review without ensuring functionality or pruning irrelevant portions, despite a statement that everyone is responsible for reviewing AI output

Is all the resistance to overuse of AI grassroots and is the pressure for rampant adoption uniform among executives/investors? Or are some companies or verticals not drinking the koolaid?

  • CodexArcanum@lemmy.dbzer0.com
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    10 hours ago

    “Artificial Intelligence” is a very broad term that, within computer science, covers a range of techniques and tools that broadly cover the study of “human-like behavior and impersonation.” Before the current fad of calling LLMs “AI”, the term was most often used in video games and covered techniques for pathfinding, decision making, reacting, seeming to speak, etc. Before that, pre-90s basically, “AI” had already undergone a few boom and bust cycles of hype with chess playing machines and, as always, chat bots.

    In many fields, many of these same techniques and their descendants are being used to model and simulate and predict. All of them have trade-offs and limitations, that’s what computer science is all about.

    • leoj@piefed.social
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      9 hours ago

      I do remember talking to chatbots on AIM back in the day, so I think I had a leg up on other people in already understanding that the technology has existed for decades, which made me more cautious about the claims.

      • chunes@lemmy.world
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        5 hours ago

        They made such a big leap so quickly, though. I remember even in 2018 thinking no bot would ever pass the Turing test.