Google recently unveiled the next phase of its artificial intelligence (AI) journey: "AI mode".

As artificial intelligence takes off, how do we efficiently integrate it into our lives and our work? Bridging the gap between promise and practice, Jann Spiess, an associate professor of operations, information, and technology at Stanford Graduate School of Business, is exploring how algorithms can be designed to most effectively support—rather than replace—human decision-makers.

Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like training robots or playing complex games, rewards are few and far between, making it easy for AI to waste time on dead ends.

A team of roboticists and AI specialists at the Robotics & Artificial Intelligence Lab in Korea has designed, built and successfully tested a four-legged robot that is capable of conducting high-speed parkour maneuvers. In their paper published in the journal Science Robotics, the group describes how they gave their robot a controller capable of both planning and tracking its own movements to allow it to freely traverse a range of environments.

Frameworks are a critical, if underappreciated, component of any space exploration mission. They can range from the overall mission architecture, capturing scientific and technical goals, to the structure of messages sent between two internal components of the system.

A new supercomputer named after a winner of the Nobel Prize in chemistry will help power artificial intelligence technology and scientific discoveries from a perch in the hills above the University of California, Berkeley, federal officials said Thursday.

The New York Times has agreed a deal for Amazon to use its content to train artificial intelligence models, the leading U.S. newspaper announced Thursday in its first generative AI licensing deal.

Two and a half years since ChatGPT rocked the world, scientist and writer Gary Marcus still remains generative artificial intelligence's great skeptic, playing a counter-narrative to Silicon Valley's AI true believers.

It is not often that cold, hard facts determine what people care most about and what they believe. Instead, it is the power and familiarity of a well-told story that reigns supreme. Whether it's a heartfelt anecdote, a personal testimony or a meme echoing familiar cultural narratives, stories tend to stick with us, move us and shape our beliefs.

A small team of roboticists at Robotic Systems Lab, ETH Zurich, in Switzerland, has designed, built and tested a four-legged robot capable of playing badminton with human players.

An AI system that learns language autonomously develops a language structured in the same way as human language. And just as we humans learn from previous generations, AI models get better when they take advantage of the knowledge of older relatives.

Artificial intelligence isn't always a reliable source of information: large language models (LLMs) like Llama and ChatGPT can be prone to "hallucinating" and inventing bogus facts. But what if AI could be used to detect mistaken or distorted claims, and help people find their way more confidently through a sea of potential distortions online and elsewhere?

Many policy discussions on AI safety regulation have focused on the need to establish regulatory "guardrails" to protect the public from the risks of AI technology. In a new paper published in the journal Risk Analysis, two experts argue that, instead of imposing guardrails, policymakers should demand "leashes."

The advancement of artificial intelligence (AI) and the study of neurobiological processes are deeply interlinked, as a deeper understanding of the former can yield valuable insight about the other, and vice versa. Recent neuroscience studies have found that mental state transitions, such as the transition from wakefulness to slow-wave sleep and then to rapid eye movement (REM) sleep, modulate temporary interactions in a class of neurons known as layer 5 pyramidal two-point neurons (TPNs), aligning them with a person's mental states.

Internet giants are diving deeper into e-commerce with digital aides that know shoppers' likes, let them virtually try clothes on, hunt for deals and even place orders.

Interactive robots should not just be passive companions, but active partners—like therapy horses who respond to human emotion—say University of Bristol researchers.

Soil liquefaction—the process where saturated soil loses its structure and transforms to a fluid-like state—can have devastating outcomes, as evidenced by the Great East Japan Earthquake in 2011. Large-scale liquefaction during this disaster damaged thousands of houses in the Tokyo Bay area, posing a formidable challenge to infrastructure in Japan.

A leading large language model displays behaviors that resemble a hallmark of human psychology: cognitive dissonance.

The growing proliferation of AI-powered chatbots has led to debates around their social roles as friend, companion or work assistant.

Artificial intelligence will encourage more people to create music in the future and is not a threat to the industry, the founder and CEO of streaming giant Spotify said.

AI has already transformed industries and the way the world works. And its development has been so rapid that it can be hard to keep up. This means that those responsible for dealing with AI's impact on issues such as safety, privacy and ethics must be equally speedy.

Large language models (LLMs), such as the model underpinning the functioning of the popular conversational platform ChatGPT, are now widely used by people worldwide to source information, as well as to summarize, analyze and generate texts. Studies examining the responses provided by LLMs in different scenarios could help to gain a deeper understanding of their tendencies during social interactions, which could fuel their future advancement.

For decades, Hollywood directors, including Stanley Kubrick, James Cameron and Alex Garland, have cast artificial intelligence as a villain that can turn into a killing machine.

As the head of the Natural Language Processing Laboratory at EPFL, Antoine Bosselut keeps a close eye on the development of generative artificial intelligence tools such as ChatGPT. He looks back at their evolution over the past two years and suggests some avenues for the future.

Laser-based processes for metals are considered to be particularly versatile in industry. Lasers can be used, for example, to precision-weld components together or produce more complex parts using 3D printing—quickly, precisely and automatically. This is why laser processes are used in numerous sectors, such as the automotive and aviation industries, where maximum precision is required, or in medical technology, for example for the production of customized titanium implants.

Can large language models (LLMs) reason by analogy? Some outputs suggest that they can, but it has been argued that these results reflect mimicry of the results of analogical reasoning in the models' training data.

An experimental study suggests that people are less likely to behave in a trusting and cooperative manner when interacting with AI than when interacting with other humans. Scientists use experimental games to probe how humans make social decisions requiring both rational and moral thinking.

Can machines ever see the world as we see it? Researchers have uncovered compelling evidence that vision transformers (ViTs), a type of deep-learning model that specializes in image analysis, can spontaneously develop human-like visual attention patterns when trained without labeled instructions.

In 2024, 1,040 accidents were recorded on Spanish roads, in addition to minor collisions and other driving problems. The causes of these accidents include speeding, adverse weather conditions and substance abuse, but also distraction and stressful situations that can be mitigated by improving infrastructure design, technologies to assist drivers and road safety policies.

A new tool has been developed to better assess the performance of AI models. It was developed by bioinformaticians at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and the Helmholtz Institute for Pharmaceutical Research Saarland (HIPS).