Use of ChatGPT, Claude and other large language models, or LLMs—what most people call "AI"—has surged since ChatGPT debuted publicly in 2022. Hundreds of millions of people now use these tools weekly, according to recent estimates.

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational resources. Traditionally, obtaining a smaller, faster model either requires training a massive one first and then trimming it down, or training a small one from scratch and accepting weaker performance.

The conflict in Iran—but also the war in Ukraine—show not only that AI is radically changing the economics of war (which may be good news), but also that we may be heading toward some kind of "Chernobyl moment." We may soon experience a disaster that will force us to belatedly realize we should have drawn up some shared rules to govern a technological development that we ourselves triggered.

Researchers at the University of Florida are developing artificial intelligence models to pinpoint early signs of sinkholes before they appear. "I'm always looking for real-world problems," said Minhee Kim, Ph.D., an assistant professor with the Department of Industrial and Systems Engineering, known as ISE. "We're engineers, so we are always thinking, 'What kind of new problem can we solve using data?' And one of the more promising and relatively unexplored research areas is geomatics."

A US appeals court on Wednesday denied Anthropic's request to put on hold a move by the Pentagon to label it a supply chain risk, but ordered the AI startup's legal battle with the Department of War to be put on a fast track.