Both open-source and closed-source AI algorithms are trained on immense datasets that include medical textbooks, peer-reviewed research, clinical-decision support tools, and anonymized patient data, such as case studies, test results, scans, and confirmed diagnoses.
And even so, they weren't perfect. So you wouldn't want to trust them completely. The point of this article is that it's the data and the training, not necessarily the size of the architecture.The open-source model exhibited genuine depth: Llama made a correct diagnosis in 70 percent of cases, compared with 64 percent for GPT-4. It also ranked the correct choice as its first suggestion 41 percent of the time, compared with 37 percent for GPT-4. For the subset of 22 newer cases, the open-source model scored even higher, making the right call 73 percent of the time and identifying the final diagnosis as its top suggestion 45 percent of the time.
Oregon lawmakers, ladies and gentlemen.As for Oregon, SB 611 is being put forward as the state is confronting potential federal funding cuts, everybody and their brother seems to want higher spending on schools, affordable housing, transportation and healthcare, Trump tariffs could lead to a trade war that hurts export-heavy Oregon and fears of a national recession are growing.
But what stands out even more in the current debate over the bill? All of its enthusiastic supporters haven’t the faintest idea what it would cost the state.