alt Hacker NewsIt's funny how AI sometimes feels like it went full circle:
— "Let's build efficient classifiers"
— "Forget about the silly classifiers, LET'S BUILD A MACHINE GOD"
— "Ah, that machine god is often too expensive and underwhelming. Let's build efficient classifiers"
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If you were actually involved in that work pre-LLM, you know it didn't go in a circle. Most projects died at training data and problem definition. That isn't the case with LLM applications which can ship with zero data collection and labelling effort.
Now you can iterate on your 20 ticket categories in days against real workloads and not commit to training an efficient model until you've proven the prototype in production.
"Let them eat cake"-and-find-out-phase is what I'd like to call step 2.
The key is that the circle takes a few weeks instead of a decade.