Early attempts at making dedicated hardware to house artificial intelligence smarts have been criticized as, well, a bit rubbish. But here’s an AI gadget-in-the-making that’s all about rubbish, literally: Finnish startup Binit is applying large language models’ (LLMs) image processing capabilities to tracking household trash.

  • plinky [he/him]@hexbear.net
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    6 months ago

    why on gods green earth you need llm to do image recognition, and to just analyze your trash, not even sort it, what is this shit

    • RBG
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      6 months ago

      Because that’s how you get big investors on board before you develop nothing, advertise how you have big investors and get yourself acquired before people realise you’ve been spewing more trash verbally than your product can even recycle.

  • NuraShiny [any]@hexbear.net
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    6 months ago

    Yes, let’s run a giant server that wastes energy so people can throw away their trash in the right bin (somehow), only for that trash to then not be recycled properly later regardless. Great business model, guys!

  • JelloBrains@lemmy.zip
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    6 months ago

    Basic analytics will be free but it’s intending to introduce premium features via subscription.

    Nickled and dimed by a thousand subscriptions… Seriously who would want this? Who is going to pay to have their trash monitored by some data company?

  • Baggins@beehaw.org
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    6 months ago

    I can actually see this as being useful further down the line. It can suggest which bin to put things into.

    In The Expanse they have bins that they drop anything into for recycling - Binit could be sat at the top of a similar system and just steer items to the relevant bin. Anything not positively identified or mixed goes to the general waste bin.

  • rufus
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    6 months ago

    Yeah. I’d say if you’re throwing away paper coffee cups regularly, you’re already way worse than me who uses regular porcelain cups with nerdy text on them or my trusty stainless steel travel mug. Maybe you really need to be lectured by some ChatGPT smart appliance. (Disclaimer: There might be some circumstances where you can’t avoid them.)