Many gen AI end users are finding that large language models (LLMs) defy easy infrastructure setup and affordable management costs. One budding option may be to go with small language models (SMLs) instead. 

If there’s an economic sector whose workforce is largely AI-proof, healthcare is it. 

Just by taking notes during patient visits, generative AI could save a five-physician primary care practice $291,200 in one year. The practice would see a return on its AI investment of 94.13% and reach the breakeven point in a bit more than six months. 

An HHS agency is developing ways to keep aging AI-enabled medical devices up to snuff for the long haul. 

A new survey shows that, in the generative AI era, two of every three U.S. hospitals let the CIO’s office handle the selection and acquisition of data analytics platforms.

Cardio-rheumatology clinics use a heart team-like approach to enhance care for patients with chronic conditions such as lupus, psoriasis and rheumatoid arthritis. "It's not just about cardiology," the director of one clinic explains. "We work closely with rheumatologists, dermatologists and even primary care physicians to provide comprehensive care."

Buzzworthy: Mayo Clinic has more than 200 algorithms under development.

A lot of people from a lot of organizations in a lot of countries are working to coordinate oversight of AI’s risks. A budding project seeks to bring many of these minds together to advance the worthy goal of building global consensus with scientific rigor.