Category Physics

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.

Some of the strangest weather in the solar system doesn’t happen on Earth or even in Jupiter’s Great Red Spot—it happens in the interiors of ice giants like Neptune and Uranus. Specifically, scientists have long believed that, at certain pressures and temperatures, it literally rains diamonds inside these planets. For the first time, scientists have mimicked the process they believe creates this phenomenon.

A new paper by physicists at Lawrence Livermore National Laboratory (LLNL), published in Nature Physics, resolves the 20-year-old scientific mystery and shows how the same physics that makes it rain diamonds inside Neptune could also help us triple our fusion energy output.

Let’s talk about the actual experiment first...

Inside every electronic device, the flow of electricity is controlled by a switch called a transistor. For decades, these switches were made from silicon. More recently, engineers have turned to a material called gallium nitride (GaN), which enables small, efficient devices like smartphone chargers.

However, at very high voltages, electric fields inside these transistors can concentrate at specific points, causing them to fail prematurely. As a result, today’s GaN devices still struggle to perform at the highest voltage levels achieved by silicon.

To overcome this limitation, researchers in the Power and Wide-band-gap Electronics Research Lab (POWERlab) in EPFL’s School of Engi...