It has become impossible to tell managers mesmerised by artificial intelligence that the tools are not, in fact, helpful. So employees just play along with the fiction to keep their jobs, writes our tech columnist
  • TheLegendaryAssholeOfJushinLiger@sh.itjust.worksEnglish
    02·
    3 months ago

    In other words, corporate leadership is starting from the premise that AI has (or will) radically change the business, and they’re working backwards from that premise to find the evidence to support this article of faith.

    This quote is quite funny in this context, because it’s literally what people do with AI. Half of the frontpage of lemmy is AI. The other half is people saying AI is bad with no realization of the irony, because they don’t see good AI. It’s like CGI. Everybody hates CGI, except they don’t. CGI is everywhere. They just hate bad CGI.

    • muusemuuse@sh.itjust.worksEnglish
      1·
      3 months ago

      What is AI? Explain as if i just woke up from a coma. We don’t have flying cars, we have dumpster deloreans, but everyone is talking about AI. What is it?

      • TheLegendaryAssholeOfJushinLiger@sh.itjust.worksEnglish
        02·
        3 months ago

        Since that was a lazy question I decided to be lazy and just copy paste it into Gemini. Enjoy! I have no idea what the point of this is!

        Artificial Intelligence isn’t a single technology; it has been a massive umbrella term since the 1950s. Broadly, it means creating computer systems capable of performing tasks that typically require human intelligence.

        If LLMs are just one tiny branch on the tree, here is what the rest of the tree looks like:

        Machine Learning (ML): This is the engine driving most modern AI. Instead of a human programmer writing strict "if/then" rules, we feed the computer massive amounts of data and let it figure out the rules itself. This is what powers your Netflix recommendations, credit card fraud detection, and the algorithm deciding what you see on social media.

Computer Vision: Teaching computers to "see" and interpret the visual world. This is how self-driving cars identify stop signs versus pedestrians, how your phone unlocks when it sees your face, and how medical software spots anomalies in X-rays faster than human doctors.

Robotics: The physical application of AI. This isn't just mechanical engineering; it is the software that allows a machine to navigate the unpredictable, physical world. This covers everything from the Roomba vacuuming your floor to automated factory arms and those creepy, dog-like robots from Boston Dynamics.

Natural Language Processing (NLP): This is the branch focused on understanding and generating human language. LLMs live here, but so do older, simpler technologies like spellcheck, Google Translate, and the early versions of Siri or Alexa.

Expert Systems & Rule-Based AI: This is the older, "classic" AI. It relies on a massive database of human knowledge programmed as logical rules. When the IBM computer Deep Blue beat the world chess champion in 1997, it wasn't using an LLM; it was using raw computational power to calculate millions of possible moves and their outcomes based on strict rules.

Predictive Analytics & Optimization: The invisible math running the modern world. This is AI used by logistics companies to find the absolute most efficient routes for delivery trucks, or by hedge funds to execute high-frequency stock trades based on market micro-fluctuations.