OpenAI on Thursday released a keenly awaited new generation of its hallmark ChatGPT, touting "significant" advancements in artificial intelligence capabilities, as a global race over the technology accelerates.

Generative artificial intelligence (AI) is getting better at imitating human beings. It can create things that previously only humans could produce, like music, texts and images. AI is now also being used to imitate God, through chatbots that simulate conversation with human users and can be accessed on websites and apps.

High-quality output at low latency is a critical requirement when using large language models (LLMs), especially in real-world scenarios, such as chatbots interacting with customers, or the AI code assistants used by millions of users daily.

AI seems to be well on its way to becoming pervasive. You hear rumbles of AI being used, somewhere behind the scenes, at your doctor's office. You suspect it may have played a role in hiring decisions during your last job search. Sometimes—maybe even often—you use it yourself.

Any motorist who has ever waited through multiple cycles for a traffic light to turn green knows how annoying signalized intersections can be. But sitting at intersections isn't just a drag on drivers' patience—unproductive vehicle idling could contribute as much as 15% of the carbon dioxide emissions from U.S. land transportation.

When we look at the world, our brain doesn't just recognize objects such as "a dog" or "a car," it also understands the broader meaning, like what's happening, where it's happening, and how everything fits together. But for years, scientists didn't have a good way to measure that rich, complex understanding.

Fuel cells are energy solutions that can convert the chemical energy in fuels into electricity via specific chemical reactions, instead of relying on combustion. Promising types of fuel cells are direct methanol fuel cells (DMFCs), devices specifically designed to convert the energy in methyl alcohol (i.e., methanol) into electrical energy.

A new approach called open ad-hoc categorization (OAK) helps AI systems dynamically reinterpret the same image differently depending on the categorization context, rather than using fixed visual interpretation. A University of Michigan-led study on this topic was presented in June 2025 at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in Nashville, Tennessee.

Imagine trying to make an accurate three-dimensional model of a building using only pictures taken from different angles—but you're not sure where or how far away all the cameras were. Our big human brains can fill in a lot of those details, but computers have a much harder time doing so.

OpenAI on Wednesday said it was letting the US government use a version of ChatGPT designed for businesses for a year, charging just $1 for the service.

A team of researchers have developed and successfully tested a world-first roadside technology designed to prevent animal–vehicle collisions in regional Australia.

The Southeastern Pennsylvania Transportation Authority piloted a new enforcement tool in Philadelphia in 2023: AI-powered cameras mounted on seven of its buses. The results were immediate and dramatic: In just 70 days, the cameras flagged over 36,000 cars blocking bus lanes.

U.S. state legislatures are where the action is for placing guardrails around artificial intelligence technologies, given the lack of meaningful federal regulation. The resounding defeat in Congress of a proposed moratorium on state-level AI regulation means states are free to continue filling the gap.

While developing a tool to boost literacy and reading comprehension, researchers at Northeastern University have joined in on a beloved children's activity: storytime.

AI is a relatively new tool, and despite its rapid deployment in nearly every aspect of our lives, researchers are still trying to figure out how its "personality traits" arise and how to control them. Large learning models (LLMs) use chatbots or "assistants" to interface with users, and some of these assistants have exhibited troubling behaviors recently, like praising evil dictators, using blackmail or displaying sycophantic behaviors with users. Considering how much these LLMs have already been integrated into our society, it is no surprise that researchers are trying to find ways to weed out undesirable behaviors.

ChatGPT will tell 13-year-olds how to get drunk and high, instruct them on how to conceal eating disorders and even compose a heartbreaking suicide letter to their parents if asked, according to new research from a watchdog group.

Imagine if you could peer into the future of a machine—track its wear and tear, predict when it might fail, and fine-tune its performance—all without touching it.

OpenAI on Tuesday released two new artificial intelligence (AI) models that can be downloaded for free and altered by users, to challenge similar offerings by US and Chinese competition.

Just like when multiple people gather simultaneously in a meeting room, higher-order interactions—where many entities interact at once—occur across various fields and reflect the complexity of real-world relationships. However, due to technical limitations, in many fields, only low-order pairwise interactions between entities can be observed and collected, which results in the loss of full context and restricts practical use.

A new study has examined issues of large language models (LLMs) failing to flag articles which have been retracted or are discredited when asked to evaluate their quality.

Visual artists want to protect their work from non-consensual use by generative AI tools such as ChatGPT. But most of them do not have the technical know-how or control over the tools needed to do so.

New vulnerabilities have emerged with the rapid advancement and adoption of multimodal foundational AI models, significantly expanding the potential for cybersecurity attacks. Researchers at Los Alamos National Laboratory have put forward a novel framework that identifies adversarial threats to foundation models—artificial intelligence approaches that seamlessly integrate and process text and image data. This work empowers system developers and security experts to better understand model vulnerabilities and reinforce resilience against ever more sophisticated attacks.

Not long ago, planning a trip meant juggling guidebooks and hours of searching the web for the best restaurants and must-see sights. Now, travelers are turning to artificial intelligence tools to do the heavy lifting.

LLMs that emulate human speech are being used to cost-effectively test assumptions and run pilot studies, producing promising early results. But researchers note that human data remains essential.

The Ateneo de Manila University's Business Insights Laboratory for Development (BUILD) is looking at ways for artificial intelligence (AI) to augment and enhance—rather than replace—human labor in small businesses, which make up the bulk of the Philippine economy.

A new artificial intelligence (AI) tool could make it much easier—and cheaper—for doctors and researchers to train medical imaging software, even when only a small number of patient scans are available.

As policymakers in the U.S. and globally consider how to govern artificial intelligence technology, Berkeley researchers have joined with others to recommend opportunities to develop evidence-based AI policy.

In a world obsessed with shortcuts to success and wealth, Mia Zelu is the ultimate fantasy: A virtual influencer who skipped the everyday grind and even the basic requirement of existing. But audiences are still double-tapping.

Is it The Velvet Underground or Velvet Sundown? The fictitious rock group, Velvet Sundown, which comes complete with AI-generated music, lyrics and album art, is stoking debate about how the new technology is blurring the line between the real and synthetic in the music industry, and whether creators should be transparent with their audience.

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics that deals with constantly changing systems, explains why optimal transport theory, a mathematical framework for the optimal change of distribution to reduce cost, makes generative models optimal. As nonequilibrium thermodynamics has yet to be fully leveraged in designing generative models, the discovery offers a novel thermodynamic approach to machine learning research. The findings were published in the journal Physical Review X.