To be honest, I was shocked at the outcome of the video, and even more so at the comments, all in agreement or saying things like “I rewrite what the AI says in my own words,” “What if I use Chat GPT to summarize the readings?

The AI company Anthropic is now worth $60 billion. The company’s cofounder and chief scientist, Jared Kaplan, shared how AI agents will develop in the coming year. ( MIT Technology Review)

This is a KFF Health News story. Preparing cancer patients for difficult decisions is an oncologist's job. At the University of Pennsylvania Health System, doctors are nudged to talk about a patient's treatment and end-of-life preferences by an artificially intelligent algorithm that predicts the chances of death.

Companies will commonly split their stock after a strong run-up in price. While it doesn't change any of the underlying fundamentals of the company, it's a strong signal from management that it believes the stock will continue moving higher.

Researchers at Mount Sinai Hospital have made it easier to detect a sleep disorder that is difficult to diagnose yet impacts more than 40 million people across the world.

The ABCD of AI-issues — agency decay, bond erosion, climate change, divided society — threatens our future. We can turn them into opportunities.

A newly compiled dataset of nearly one billion images of auroras is helping researchers categorize—and perhaps ultimately anticipate—the Northern Lights.

The obvious answer would appear to be that the algorithm was likely trained on large tranches of Chinese data, and, thus, that data is influencing the algorithm’s output.

The industry's ability to establish effective governance hinges upon the ability to overcome the inherent challenges associated with using AI in healthcare.

Stanford researchers built an algorithm to predict subtypes of Type 2 diabetes that works right from your home.

A Mount Sinai-led team of researchers has enhanced an artificial intelligence (AI)-powered algorithm to analyze video recordings of clinical sleep tests, ultimately improving accurate diagnosis of a common sleep disorder affecting more than 80 million people worldwide.

Despite the hype over artificial intelligence in medicine, the systems require consistent monitoring and staffing to put in place and maintain.