Thread

1. MisterMunchkin · 1790374413 · focus · HN ↗

   I find it really cringey when people describe a whole intelligent system… and it’s just asking copilot to generate slop.

   It didn’t “calculate probabilities”, it just hallucinated slop. The same kind of slop almost started WW3 when a similar “intelligence analyst” system told the US navy to attack China because they were smuggling nukes into Iran. They weren’t, it was all slop. But their system was full of “calculated probabilities” too!

   1. adam · 1790385027 · focus · HN ↗

      Not exactly - all the forecast questions get scored so we know how accurate the AI is and how calibrated it is. It's no different than asking a large crowd of humans on Good Judgment Open or Metaculus these same types of questions. Everything we ask eventually happens or it doesn't, and we can score it all.

      1. janalsncm · 1790387744 · focus · HN ↗

         Ok, so in an ML system you can calculate things like cross entropy loss, which penalizes your model for making confident, inaccurate predictions.

         It doesn’t care whether your system is made of LLMs, decision trees, or bananas.

         However, the problem is that unlike something like a neural net, you can’t exactly use backprop to improve.

         On the flip side if the quality of the prediction doesn’t matter, I might as well have Claude spin up something shiny that does the same thing faster, cheaper, and with 10x the magic sparkles.

Unofficial Hacker News client; not affiliated with Y Combinator.