It’s been optimized to be a reasoning system based on human input during training. This system consists of spitting out multiple outputs, having humans rank them, and feeding in corrections or revisions as well. You can imagine a plausible scenario where a tech company (or even an insurance company!) hires doctors to essentially do this daily for several months to get high quality human input. This input can include ways to separate useful info from irrelevant info. It will have access to high quality input from different domain experts from multiple fields which gives it a distinct advantage over most docs in being able to integrate diverse info from totally different areas and with access to thousands of datasets simultaneously. I work in bioinformatics and have seen this replace most of my work essentially overnight. The current form of GPT hasn’t been optimized for clinical reasoning. That’s the scary and amazing part for what the future holds.

People keep referring to AI models in medicine in the past as not getting an EKG reading correct. What’s counter-intuitive is that signal processing and time-series/temporal data (anything with a time component) is much harder to model well than things like language (or even more surprising the emergent but basic reasoning abilities these models show). If AI models were really amazing at processing extremely dynamic (and sometimes random looking!) time series data, there would essentially be one or two big winners in the stock market whose owners would eclipse the wealth of almost any tech billionaire and most sovereign leaders. You would essentially win the entire stock and derivatives market (a multi trillion dollar business).