Yeah, I’m not talking about a language model AI. But rather something like the stuff the insurance companies are using to assess risk – they take a lot of data in and cluster them together. Humans are sometimes really bad at recognizing patterns if you don’t have enough data. A pattern that goes: “oh, all these people in this region with this specific digestive problem spatially maps to this insect” is the sort of thing ML should be good at. But where it will be really good is in turning proteins into diagnosis: “if this protein is detected in the blood in an general scan, combined with symptoms, then diagnose X” – right now you only get tested for the things the doctor orders. Even more promising yet: with enough data, the AI should figure out which proteins actually do specific functions in the body, which will advance the research side (see, for example, Alphafold).
Yeah, I’m not talking about a language model AI. But rather something like the stuff the insurance companies are using to assess risk – they take a lot of data in and cluster them together. Humans are sometimes really bad at recognizing patterns if you don’t have enough data. A pattern that goes: “oh, all these people in this region with this specific digestive problem spatially maps to this insect” is the sort of thing ML should be good at. But where it will be really good is in turning proteins into diagnosis: “if this protein is detected in the blood in an general scan, combined with symptoms, then diagnose X” – right now you only get tested for the things the doctor orders. Even more promising yet: with enough data, the AI should figure out which proteins actually do specific functions in the body, which will advance the research side (see, for example, Alphafold).