Microsoft on Monday said it was enhancing its AI offerings with new autonomous agent capabilities as the tech titan aims to accelerate business adoption of artificial intelligence.

Social media has revolutionized the way information is shared throughout communities, but it can also be a cesspit of hateful content. Current research on hateful content detection focuses on text-based analysis, while hateful video detection remains underexplored.

Researchers from ETH Zurich, the Bulgarian AI research institute INSAIT—created in partnership with ETH and EPFL—and the ETH spin-off LatticeFlow AI have provided the first comprehensive technical interpretation of the EU AI Act for General Purpose AI (GPAI) models. This makes them the first to translate the legal requirements that the EU places on future AI models into concrete, measurable and verifiable technical requirements.

Despite their impressive capabilities, large language models are far from perfect. These artificial intelligence models sometimes "hallucinate" by generating incorrect or unsupported information in response to a query.

While artificial intelligence (AI) systems, such as home assistants, search engines or large language models like ChatGPT, may seem nearly omniscient, their outputs are only as good as the data on which they are trained. However, ease of use often leads users to adopt AI systems without understanding what training data was used or who prepared the data, including potential biases in the data or held by trainers.

Irish writer John Connolly once said: "The nature of humanity, its essence, is to feel another's pain as one's own, and to act to take that pain away."

It's not surprising that technology regulation is an important issue in the 2024 U.S. presidential campaign.

Artificial intelligence's recent rise to the forefront of business has left most office workers wondering how often they should use the technology and whether a computer will eventually replace them.

Generative artificial intelligence (AI) tools like ChatGPT or Dall-E are changing how creative work is done, particularly in industries that rely on innovation.

You know we've reached peak interest in artificial intelligence (AI) when Oprah Winfrey hosts a television special about it. AI is truly everywhere. And we will all have a relationship with it—whether using it, building it, governing it or even befriending it.

University of Virginia School of Engineering and Applied Science professor Nikolaos Sidiropoulos has introduced a breakthrough in graph mining with the development of a new computational algorithm.

Large language models (LLMs) are machine-learning models designed to understand and generate human language. State-of-the-art LLMs have demonstrated outstanding potential in open-domain question answering (ODQA), where the model is tasked with providing answers to factual questions.

Ensuring the security of network systems and infrastructure is a critical aspect of cybersecurity. Penetration testing (pentesting) is an effective method for evaluating the network security posture.

A team of AI researchers with Google's DeepMind London group has found that certain large language models (LLMs) can serve as effective mediators between groups of people with differing viewpoints regarding a given topic. The work is published in the journal Science.

Earlier this year, OpenAI and other artificial intelligence companies wooed Hollywood studios with the futuristic promise of AI tools that they said could help make the business of creating movies and television shows faster, easier and cheaper.

Today, our understanding and assessment of the physical characteristics of the world around us relies less and less on human intelligence and more and more on artificial intelligence.

In the current AI zeitgeist, sequence models have skyrocketed in popularity for their ability to analyze data and predict what to do next. For instance, you've likely used next-token prediction models like ChatGPT, which anticipate each word (token) in a sequence to form answers to users' queries. There are also full-sequence diffusion models like Sora, which convert words into dazzling, realistic visuals by successively "denoising" an entire video sequence.

In his article, "Trust is Not a Virtue: Why We Should Not Trust," Matthew L. Bolton, an associate professor of systems and information engineering at the University of Virginia, critically challenges the emphasis on fostering trust in human-machine interactions. He focuses particularly on systems using AI, machine learning and automation.

In an Imperial College London study, humans displayed sympathy towards and protected AI bots who were excluded from playtime. The researchers say the study, which used a virtual ball game, highlights humans' tendency to treat AI agents as social beings—an inclination that should be considered when designing AI bots.

A tribal casino in Oklahoma is using an app tied to its surveillance camera system that uses artificial intelligence to detect patrons carrying firearms.

For Deaf people, train travel can be a gamble. On an average day, nothing goes wrong: they catch their train to their destination and carry on with their business.

What if a security camera could not only capture video but understand what's happening—distinguishing between routine activities and potentially dangerous behavior in real time? That's the future being shaped by researchers at the University of Virginia's School of Engineering and Applied Science with their latest breakthrough: an AI-driven intelligent video analyzer capable of detecting human actions in video footage with unprecedented precision and intelligence.

In recent years, artificial intelligence (AI) and deep learning models have advanced rapidly, becoming easily accessible. This has enabled people, even those without specialized expertise, to perform various tasks with AI. Among these models, generative adversarial networks (GANs) stand out for their outstanding performance in generating new data instances with the same characteristics as the training data, making them particularly effective for generating images, music, and text.

Researchers at the University of Virginia have made a significant advancement in manufacturing technology by developing an AI-driven system that could transform how factories operate. Using Multi-Agent Reinforcement Learning (MARL), the team has created a more efficient way to optimize manufacturing systems, improving both speed and quality while reducing waste.

Thanks to a technique developed by researchers at NC State University, autonomous vehicles might one day be able to navigate the roadways much better. The technique allows artificial intelligence programs to more accurately map three-dimensional spaces using two-dimensional images.

From the mind-bending reality warps of Doctor Strange in the Multiverse of Madness (2022) to the breathtaking alien vistas of Avatar: The Way of Water (2022), visual effects have transported us to worlds beyond imagination. Yet the future of visual effects (VFX) could hang in the balance as artificial intelligence is subsumed into screen production processes.

The advent of generative artificial intelligence (AI) has sparked concerns about the diminishing value of traditional art forms and the potential for substitution. Nonetheless, through their fusion, they offer new avenues for conserving art and culture while also igniting interest in passing down the heritage from generation to generation.

Researchers at Apple Computer Company have found evidence, via testing, showing that the seemingly intelligent responses given by AI-based LLMs are little more than an illusion. In their paper posted on the arXiv preprint server, the researchers argue that after testing several LLMs, they found that they are not capable of performing genuine logical reasoning.

A wave of touching photos showing great moments in time is fascinating amateur historians online. The problem? They are not real—and may be clouding our view of the past.

If you've been using artificial intelligence (AI) for a while, you may have noticed that both the texts and images it creates can be a bit generic and polished. Some would call them soulless.