Plus: how wastewater tracking could help curb measles' rise in the US. Can ChatGPT Health do better? For the past two decades, there's been a clear first step for anyone who starts experiencing new medical symptoms: Look them up online. The practice was so common that it gained the pejorative moniker "Dr. But times are changing, and many medical-information seekers are now using LLMs. According to OpenAI, 230 million people ask ChatGPT health-related queries each week.

A new survey finds 95% of faculty worry artificial intelligence makes students overly reliant on AI, with 90% saying it decreases critical thinking.

Deep neural networks (DNNs) typically involve a large number of parameters and are trained to achieve zero or near-zero training error. Despite such interpolation, they often exhibit strong generalization performance on unseen data, a phenomenon that has motivated extensive theoretical investigations. Comforting results show that interpolation indeed may not affect the minimax rate of convergence under the squared error loss. In the mean time, DNNs are well known to be highly vulnerable to adversarial perturbations in future inputs. A natural question then arises: Can interpolation also escape from suboptimal performance under a future $X$-attack? In this paper, we investigate the adversarial robustness of interpolating estimators in a framework of nonparametric regression. A finding is that interpolating estimators must be suboptimal even under a subtle future $X$-attack, and achieving perfect fitting can substantially damage their robustness. An interesting phenomenon in the high interpolation regime, which we term the curse of simple size, is also revealed and discussed. Numerical experiments support our theoretical findings.

Functional bilevel optimization (FBO) provides a powerful framework for hierarchical learning in function spaces, yet current methods are limited to static offline settings and perform suboptimally in online, non-stationary scenarios. We propose SmoothFBO, the first algorithm for non-stationary FBO with both theoretical guarantees and practical scalability. SmoothFBO introduces a time-smoothed stochastic hypergradient estimator that reduces variance through a window parameter, enabling stable outer-loop updates with sublinear regret. Importantly, the classical parametric bilevel case is a special reduction of our framework, making SmoothFBO a natural extension to online, non-stationary settings. Empirically, SmoothFBO consistently outperforms existing FBO methods in non-stationary hyperparameter optimization and model-based reinforcement learning, demonstrating its practical effectiveness. Together, these results establish SmoothFBO as a general, theoretically grounded, and practically viable foundation for bilevel optimization in online, non-stationary scenarios.

Humanoid robots, space travel, the science of aging--Musk was willing to weigh in on all of it at this week's World Economic Forum. But his predictions rarely work out the way he says they will. Elon Musk speaks during the World Economic Forum Annual Meeting in Davos, Switzerland on Thursday. Elon Musk, the richest man on Earth, is very good at making money. His track record of predicting the future is less stellar.

Advances in artificial intelligence are creating a perfect storm for those seeking to spread disinformation at unprecedented speed and scale. And it's virtually impossible to detect. In 2016, hundreds of Russians filed into a modern office building on 55 Savushkina Street in St. Petersburg every day; they were part of the now-infamous troll farm known as the Internet Research Agency . Day and night, seven days a week, these employees would manually comment on news articles, post on Facebook and Twitter, and generally seek to rile up Americans about the then-upcoming presidential election. When the scheme was finally uncovered, there was widespread media coverage and Senate hearings, and social media platforms made changes in the way they verified users.

WIRED spoke with Boris Cherny, head of Claude Code, about how the viral coding tool is changing the way Anthropic works. Engineers in Silicon Valley have been raving about Anthropic's AI coding tool, Claude Code, for months. But recently, the buzz feels as if it's reached a fever pitch. Earlier this week, I sat down with Boris Cherny, head of Claude Code, to try to understand how the company is meeting this moment. "We built the simplest possible thing," said Cherny. "The craziest thing was learning three months ago that half of the sales team at Anthropic uses Claude Code every week."

OpenAI’s newest product, which is intended to provide health advice, is no replacement for a doctor. But it might be better than searching the web for your symptoms.

Johansson was dragged into the AI debate after OpenAI's voice assistant used her vocal likeness, prompting the actor to say she was'angered' by the move. Johansson was dragged into the AI debate after OpenAI's voice assistant used her vocal likeness, prompting the actor to say she was'angered' by the move. Scarlett Johansson, Cate Blanchett, REM and Jodi Picoult are among hundreds of Hollywood stars, musicians and authors backing a new campaign accusing AI companies of "theft" of their work. The "Stealing Isn't Innovation" drive launched on Thursday with the support of approximately 800 creative professionals and bands. It adds: "Artists, writers, and creators of all kinds are banding together with a simple message: Stealing our work is not innovation.

Apple's Google artificial intelligence partnership will launch a Siri overhaul using Gemini's large language models, the tech giants announced.