decades ago you would train a classifier over a fixed set of classes. decision models are flexible regarding the possible outputs they can produce. also, you get text and images in input
[−]MisterMunchkin · 2026-10-11 Sun 08:19 UTC ·
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But they’re only flexible because they can hallucinate an answer for anything. It’s like if you asked Gary Oldman to make all your decisions for you. He could do it, but he might have to make up answers when you get to more difficult topics
On a side note - this would make a brilliant TV show. Gary Oldman for a day making life changing decisions then we come back one year later to see how it all went. A bit like Grand Designs.
A coin flip can make infinite decisions on all possible input taxonomies.
Zero-shot is indeed very cool. And it's super useful/useful for the developer masses that don't know, care, or work pressures don't allow, for proper evaluation and calibration.
But it would be good that we don't over-hype these things.
Decision models can perform zero-shot classification over almost unlimited text-input domains. This was science fiction decades ago.
Zero-shot is indeed very cool. And it's super useful/useful for the developer masses that don't know, care, or work pressures don't allow, for proper evaluation and calibration.
But it would be good that we don't over-hype these things.