Page 15: Research news on Human-centered AI interfaces

Human-centered AI interfaces encompass computational systems that use machine learning, generative models, and multimodal sensing to mediate, augment, or interpret human communication and behavior. Work in this area spans assistive communication for speech, hearing, and motor impairments, real-time sign language and speech technologies, and social robots that adapt behavior and express empathy. Vision-language models and video analytics support long-video reasoning, activity recognition, and error detection, while interactive agents, privacy-aware speech systems, and affect-sensitive tools enable more accessible, expressive, and context-aware human–AI interaction across physical and virtual environments.

Computer Sciences

Computer model mimics human audiovisual perception

A new computer model developed at the University of Liverpool can combine sight and sound in a way that closely resembles how humans do it. This model is inspired by biology and could be useful for artificial intelligence ...

Engineering

AI bots could match scientist-level design problem solving

Engineers at Duke University have constructed a group of AI bots that together can solve complex design problems nearly as well as a fully trained scientist. The results, the researchers say, show how AI might soon automate ...

Machine learning & AI

AI teaches itself and outperforms human-designed algorithms

Like humans, artificial intelligence learns by trial and error, but traditionally, it requires humans to set the ball rolling by designing the algorithms and rules that govern the learning process. However, as AI technology ...

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