zakkor1
Regular LLMs can already do this, by prefilling the start of the assistant's response.
But there is actually something even better: you can constrain the LLM's output to a specific grammar (like JSON), so it'll only be able to answer with syntactically valid JSON.
1) She was already correctly diagnosed with the first issue (babesiosis), which causes anemia.
2) As a result of the babesiosis, she developed a secondary complication (immune disorder), which worsened the anemia. Note that this can also occur as a standalone disease, which is actually the google result you're getting.
3) You would have had to google "secondary complications causing anemia as a result of canine babesiosis", and at this point, google stops helping you. Not that I would have known to google that anyway.
Sure, if you know exactly what you want to google for, you can google it. But that requires you to interpret all the information and piece together a theory, whereas with GPT I just stated all the facts and received accurate (in this case) info back
If we continued staying with the first vet without getting a second opinion, she definitely would have died. On the other hand, if the first vet had access to specialized AI medical diagnostics tools, she wouldn't have died. I think that's the key takeway here.
I think it's also worth pointing out this was less about GPT placing a certain diagnosis, and more about it swaying me in the right direction (i.e. away from listening to bad doctor's advice, and towards looking for a second/opinion trying something else). When the first vet said "welp, don't know what else to do, we gave her the treatment and there's nothing else it can possibly be, so we're just going to monitor her and see how things go", I stayed up all night asking GP4 various things, and no matter which way I sliced it, it was obvious something didn't add up