Birds flock in order to forage and move more efficiently. Fish school to avoid predators. And bees swarm to reproduce. Recent advances in artificial intelligence have sought to mimic these natural behaviors as a way to potentially improve search-and-rescue operations or to identify areas of wildfire spread over vast areas—largely through coordinated drone or robotic movements. However, developing a means to control and utilize this type of AI—or "swarm intelligence"—has proved challenging.

ChatGPT-maker OpenAI is backing the production of a feature-length animated film created largely with artificial intelligence tools, aiming to prove the technology can revolutionize Hollywood filmmaking with faster timelines and lower costs.

France's Mistral on Tuesday cemented its position as Europe's top AI hope against far larger US and Chinese competitors after a record fundraising round and a tie-up with chipmaking equipment heavyweight ASML.

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of large AI models, integration with graph databases is now required. This process, however, reveals limitations such as cost burden, data inconsistency, and the difficulty of processing complex queries.

A team at the University of Florida has developed a new kind of computer chip that uses light with electricity to perform one of the most power-intensive parts of artificial intelligence—image recognition and similar pattern-finding tasks. Using light dramatically cuts the power needed to perform these tasks, with efficiency 10 or even 100 times that of current chips performing the same calculations. Using this approach could help rein in the enormous demand for electricity that is straining power grids while enabling higher performance AI models and systems.

A federal judge has begun reviewing a landmark class-action settlement agreement between the artificial intelligence company Anthropic and book authors who say the company took pirated copies of their works to train its chatbot.

Back in the 2000s, the American pharmaceutical firm Wyeth was sued by thousands of women who had developed breast cancer after taking its hormone replacement drugs. Court filings revealed the role of "dozens of ghostwritten reviews and commentaries published in medical journals and supplements being used to promote unproven benefits and downplay harms" related to the drugs.

The constant scaling of AI applications and other digital technologies across industries is beginning to tax the energy grid due to its intensive energy consumption. Digital computing's energy and latency demands will likely continue to rise, challenging their sustainability.

Skoltech scientists have devised a mathematical model of memory. By analyzing its new model, the team came to surprising conclusions that could prove useful for robot design, artificial intelligence, and for better understanding of human memory. Published in Scientific Reports, the study suggests there may be an optimal number of senses—if so, those of us with five senses could use a couple more.

Today's AI vision is effective at recognizing simple images in isolation—such as buildings, cars, and people. But when it's called upon to identify more complex terrain, its accuracy becomes questionable. This is one of the challenges facing self-driving car technology. AI visual systems must correctly spot buildings, cars, and people—all at the same time and in a fluid environment, such as a busy intersection.

Vibe coding. It's a term that's bubbling around to describe a new wave of app creation. It means instead of writing code line by line, you build software by describing what you want in plain language—and an AI agent generates the code for you.

Artificial intelligence (AI) is transforming how companies set prices—but experts warn algorithm-driven personalized pricing risks alienating consumers and inviting regulatory backlash.

Armen Kirakosian remembers the frustrations of his first job as a call center agent nearly 10 years ago: the aggravated customers, the constant searching through menus for information and the notes he had to physically write for each call he handled.

A year ago, Google faced the prospect of being dismantled. Today, artificial intelligence (AI) and a new court judgment has helped it avoid this fate. Part of the reason is that AI poses a grave threat to Google's advertising revenues.

Anthropic will pay at least $1.5 billion to settle a US class action lawsuit over allegedly using pirated books to train its artificial intelligence models, according to court documents filed Friday.

It's not just what is said but how it's articulated that shapes the meaning of human communication, and people use intonation to highlight the most important part of a sentence. Take, for instance, the sentence "Molly mailed a melon." If someone asks, "Who mailed the melon?" people are most likely to stress "Molly mailed a melon." If someone inquired what Molly did with the melon, it would be "Molly mailed a melon." If the question was what Molly mailed, the response is "Molly mailed a melon."

Criminals can use artificial intelligence, specifically large language models, to autonomously carry out ransomware attacks that steal personal files and demand payment, handling every step from breaking into computer systems to writing threatening messages to victims, according to new research from NYU Tandon School of Engineering posted to the arXiv preprint server.

Europe's fastest supercomputer Jupiter was inaugurated Friday in Germany with Chancellor Friedrich Merz saying it could help the continent catch up in the global artificial intelligence race.

As generative AI models move from massive cloud servers to phones and cars, they're stripped down to save power. But what gets trimmed can include the technology that stops them from spewing hate speech or offering roadmaps for criminal activity.

New research has found similarities in how humans and artificial intelligence integrate two types of learning, offering new insights about how people learn as well as how to develop more intuitive AI tools.

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of robotic arms to work together faster and smarter in busy industrial settings, potentially saving manufacturers hundreds of hours of planning time and unlocking new levels of flexibility and efficiency.

Making AI quicker, smarter and better is proving to be a very expensive business. Companies like OpenAI are investing billions of dollars in hardware, and the likes of Meta are offering top (human) talent huge salaries for their expertise.

Next time a Starbucks barista tells you that your favorite latte flavor is out of stock, blame artificial intelligence.

A team of computer scientists at the University of Toronto recently discovered that a certain type of hardware attack is effective against graphics processing units (GPUs), the core computing engines that power today's artificial intelligence models and cloud-based machine learning services.

Artificial intelligence is growing fast, and so are the number of computers that power it. Behind the scenes, this rapid growth is putting a huge strain on the data centers that run AI models. These facilities are using more energy than ever.

For all their technological brilliance, from navigating distant planets to performing complex surgery, robots still struggle with a few basic human tasks. One of the most significant challenges is dexterity, which refers to the ability to grasp, hold and manipulate objects. Until now, that is. Scientists from the Toyota Research Institute in Massachusetts have trained a robot to use its entire body to handle large objects, much like humans do.

Disclosure, consent and platform power have become newly invigorated battlefields with the rise of AI.

Synthetic data are artificially generated by algorithms to mimic the statistical properties of actual data, without containing any information from real-world sources. While concrete numbers are hard to pin down, some estimates suggest that more than 60% of data used for AI applications in 2024 was synthetic, and this figure is expected to grow across industries.

Professional sports teams pour millions of dollars into data analytics, using advanced tracking systems to study every sprint, pass, and decision on the field. The results of that analysis, however, are industry secrets, making many sports difficult for researchers to study.

In everyday life, it's a no-brainer to be able to grab a cup of coffee from the table. Multiple sensory inputs such as sight (seeing how far away the cup is) and touch are combined in real-time. However, recreating this in artificial intelligence (AI) is not quite as easy.