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.

Online continual learning (OCL) methods adapt to changing environments without forgetting past knowledge. Similarly, online time series forecasting (OTSF) is a real-world problem where data evolve in time and success depends on both rapid adaptation and long-term memory. Indeed, time-varying and regime-switching forecasting models have been extensively studied, offering a strong justification for the use of OCL in these settings. Building on recent work that applies OCL to OTSF, this paper aims to strengthen the theoretical and practical connections between time series methods and OCL. First, we reframe neural network optimization as a parameter filtering problem, showing that natural gradient descent is a score-driven method and proving its information-theoretic optimality. Then, we show that using a Student's t likelihood in addition to natural gradient induces a bounded update, which improves robustness to outliers. Finally, we introduce Natural Score-driven Replay (NatSR), which combines our robust optimizer with a replay buffer and a dynamic scale heuristic that improves fast adaptation at regime drifts. Empirical results demonstrate that NatSR achieves stronger forecasting performance than more complex state-of-the-art methods.

Scientists discover how a vitamin A byproduct may weaken immune responses against cancer, potentially explaining why some immunotherapies fail in patients.

More and more Chinese adoptees in the US are trying to reunite with their birth parents. For Youxue, it took more than a decade, and a remarkable coincidence. A girl is found on a street in Ma'Anshan, China, in May 1993. Her paternal grandfather, the story goes, set her down and walked away. It's unclear how long she's been outside when somebody arrives and takes her to the orphanage. A white woman adopts the girl and brings her to America in August 1994. She gives her an English name. In spring 2010, when Youxue (her Chinese name) was a high school sophomore in Dallas, Texas, she decided to start searching for her birth parents.

Thousands of Companies Are Driving China's AI Boom. How the Cyberspace Administration of China inadvertently made a guide to the country's homegrown AI revolution. When DeepSeek burst onto the global stage in January 2025, it seemed to appear out of nowhere. But the large language model was just one of the thousands of generative AI tools that have been released in China since 2023--and there's a public archive of every single one of them. Here are 23 ways China is rewiring the future .

His research focuses on multi-modal learning, specifically advancing large vision-language models, embodied intelligence, and out-of-distribution detection. Xiang has published over 40 papers in top-tier venues, including CVPR, NeurIPS, ICML, AAAI, and ACM MM. He is the recipient of multiple awards, including the NTU Research Excellence Award and Best Student Paper at MIPR 2024, and serves as a reviewer for major AI conferences."

The most powerful artificial intelligence tools all have one thing in common. Today's most powerful AI tools - the ones that can summarise documents, generate artwork, write poetry or predict how incredibly complex proteins fold - all stand on the shoulders of the "transformer" . This neural network architecture, first announced in 2017 at an unassuming conference centre in California, enables machines to process information in a way that reflects how humans think. Previously, most state-of-the-art AI models relied on a technique called a recurrent neural network . This worked by reading text in tight windows, left to right, remembering only what came just before.

Lego also recognized that it had to build a course that'll work regardless of a teacher's fluency in such subjects. So a big part of developing the course was making sure that teachers had the tools they needed to be on top of whatever lessons they're working on. "When we design and we test the products, we're not the ones testing in the classroom," Silwinski said. "We give it to a teacher and we provide all of the lesson materials, all of the training, all of the notes, all the presentation materials, everything that they need to be able to teach the lesson." Lego also took into account the fact that some schools might introduce its students to these things starting in Kindergarten, whereas others might skip to the grade 3-5 or 6-8 sets.

Amateur mathematicians are using artificial intelligence chatbots to solve long-standing problems, in a move that has taken professionals by surprise. While the problems in question aren't the most advanced in the mathematical canon, the success of AI models in tackling them shows that their mathematical performance has passed a significant threshold, say researchers, and could fundamentally change the way we do mathematics. The questions being solved by AI originate from Hungarian mathematician Paul Erdős, who was famous for his ability to pose useful but difficult questions during a career that spanned over six decades. "The questions tended to be very simple, but very hard," says Thomas Bloom at the University of Manchester, UK. By his death in 1996, there were more than 1000 of these unsolved Erdős problems, spanning a wide range of mathematical disciplines, from combinatorics (the study of combinations) to number theory.

If your New Year's resolution is to understand quantum computing this year, take a cue from a 9-year-old podcaster talking to some of the biggest minds in the field, says quantum columnist Karmela Padavic-Callaghan Quantum computing seems to pop up in the news pretty often these days. You've probably seen quantum chips gracing your feeds and their odd, steampunk-ish cooling systems in the pages of magazines and newspapers. Politicians and business leaders are peppering their announcements with the word "quantum" more frequently, too. If you're feeling a little confused about it all, it's a good year for a New Year's resolution to finally figure out what quantum computing is all about. This is an ambitious goal, and the timing certainly makes sense.