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6 comments
  • We know exactly why 🤣

    Anyone who is making this out to be a big mystery either has no direct knowledge of how this all works, or is in complete denial. You can't keep training on expanded sets of data without having a source of truth. You also can't keep feeding these models training data that isn't deduplicated, for the simple fact that base libraries that emulate neural networks will absolutely eventually draw links to conflicting information.

    This all links back to the next phase of freakout of this whole race to the bottom: data convergence and contraction. I've heard some of my peers just reference it as "Contraction". If models want to improve, you either need the hardware processing their work to expand lanes if bandwidth to work on more channels of data or once (not really possible right now), or you need to reduce the total amount of data being processed at once. If you don't care about providing a quick response as part of a product, this obviously doesn't matter, but that's all the companies want. You ALSO need a source of truth to even begin to have reasoning logic not just constantly regurgitate bullshit back on itself.

    Either way, there's going to be reckoning or data sliming to make all of these shitty products hallucinate less, and provide more reliable working responses. It's seriously the only possible way at current unless there is constant feedback in training from humans, which is also not really possible for various reasons right now.

  • Because this shit doesn't work and it never did work in the way the liars shilling it implied. They're training it on garbage on top of that.

6 comments