Category Physics

Over the past years, computer scientists have introduced increasingly sophisticated generative AI models that can produce personalized content following specific inputs or instructions. While image generation models are now widely used, many of them are unpredictable and precisely controlling the images they create remains a challenge.

In a recent paper presented at this year’s Conference on Computer Vision and Pattern Recognition (CVPR 2025), held in Nashville, June 11–15, researchers at NVIDIA introduced DiffusionRenderer, a new machine learning approach that could advance the generation and editing of imag...

Researchers have developed a technique that significantly improves the performance of large language models without increasing the computational power necessary to fine-tune the models. The researchers demonstrated that their technique improves the performance of these models over previous techniques in tasks including commonsense reasoning, arithmetic reasoning, instruction following, code generation, and visual recognition.

Large language models are artificial intelligence systems that are pretrained on huge data sets. After pretraining, these models predict which words should follow each other in order to respond to user queries...

Researchers at Helmholtz Munich have developed an artificial intelligence model that can simulate human behavior with remarkable accuracy. The language model, called Centaur, was trained on more than ten million decisions from psychological experiments—and makes decisions in ways that closely resemble those of real people. This opens new avenues for understanding human cognition and improving psychological theories.

For decades, psychology has aspired to explain the full complexity of human thought. Yet traditional models could either offer a transparent explanation of how people think—or reliably predict how they behave. Achieving both has long seemed out of reach.

The team le...

Researchers have demonstrated a new way of attacking artificial intelligence computer vision systems, allowing them to control what the AI “sees.” The research shows that the new technique, called RisingAttacK, is effective at manipulating all of the most widely used AI computer vision systems.

At issue are so-called “adversarial attacks,” in which someone manipulates the data being fed into an AI system to control what the system sees, or does not see, in an image. For example, someone might manipulate an AI’s ability to detect traffic signals, pedestrians or other cars—which would cause problems for autonomous vehicles. Or a hacker could install code on an X-ray machine that causes an AI system to make inaccurate diagnoses.

“We wanted to find an eff...