Category Physics

William Overman began his Ph.D. program at Stanford Graduate School of Business at an auspicious moment: just two months before ChatGPT launched publicly in November 2022, exploding the widely held understanding of what machines are capable of.

Even as Overman began enlisting AI for his research, he grew wary of where the technology was headed. “This isn’t only about the apocalyptic potential of what could happen; I’m also thinking a lot about the future of human flourishing,” Overman says. He fears that misaligned AI could overstep its bounds—not necessarily maliciously—and inflict subtle yet real harms on people.

“To prevent that, we need to get this right,” Overman says.

“We must set up the proper interactions and training and incentive...

Within tiny halos of light clinging to a vanishingly thin wisp of optical fiber, scientist Jongmin Lee guides atoms like marbles through a narrow pipe. Rock the fiber and the atoms shift side by side; they just don’t fall off. But don’t be deceived by the seemingly delicate nature of his experiment. Lee is exploring how to measure motion precisely in rough-and-tumble environments.

A quantum sensing scientist at Sandia National Laboratories, Lee is an expert in a type of motion sensor...

The results are in: Which AI model is the most fallible? Persuadable? Correctible? University of Arizona researchers assessed seven different generative AI large language models, or LLMs, for these three qualities during lengthy conversations. Their work, published in Nature’s Scientific Reports, reveals intrinsic limitations that might go undetected during one-off interactions.

Among the seven LLMs tested—ChatGPT (GPT-3.5, GPT-4o and GPT-4o-mini), Claude 3.5 Sonnet, Gemini 1.5 Pro, Llama-3-70B and DeepSeek-R1—they found that:

ChatGPT 3.5 was most vulnerable to reaffirming misinformation during a conversation containing repeated false statements; Claude 3.5 Sonnet was the least.
All seven were more susceptible to misinformation on obscure top...

There may soon be a new kind of artificial intelligence in town, one that uses a novel approach to thinking that could save massive amounts of computing power and money.

The AI that most people use every day, like ChatGPT, Claude or Google Gemini, relies on large language models that can work through difficult problems step by step. While this may ultimately give us the answers we are searching for, the process can increase response times and use a lot of computing power.