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Comment by sidcool | Hacker News Reader

Jev really shook up the industry. This seems obvious in hindsight

All this is for extraordinarily simple decisions. Real world problems often are a lot more complex requiring highly structured outputs covering many output attributes and substructures, for which a conventional structured output via a documented schema is better. If instead you make twenty independent calls to a decisions API, you lose coherence among your twenty decisions. I think any hype surrounding decisions will be forgotten soon enough.

I don’t think so. People want more determinism and this is just another step in that direction.

Can't wait to read about BERT on the front-page!

Deterministic predictions are sought by those looking to offload their decision responsibility to AI, whether to lower perceived legal risk or otherwise. This is fake risk reduction, i.e. "risk theater".

Unfortunately, a deterministic prediction utterly fails to yield an uncertainty measurement which is critical to have in actual risk reduction. If you want the variance in measurement, it is vital to obtain multiple measurements. This also gives a confidence interval.

"temperature=0 & sampler=deterministic is all you need".

There's plenty of business applications for a deterministic scoring/decision systems such as:

* Pass/Fail evaluation of a assortment of work product againt a given standard. * Document classification without OMRs. Luna can take image inputs.

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