The key factor in deciding how to incorporate AI recommenders is whether consumers are focused on the functional and practical aspects of a product (its utilitarian value) or on the experiential and sensory aspects of a product (its hedonic value).
Multimaterial fibers that integrate metal, glass and semiconductors could be useful for applications such as biomedicine, smart textiles and robotics. But because the fibers are composed of the same materials along their lengths, it is difficult to position functional elements, such as electrodes or sensors, at specific locations. Now, researchers reporting in ACS Central Science have developed a method to pattern hundreds-of-meters-long multimaterial fibers with embedded functional elements.
POSTECH-Stanford joint research team develops multimodal ion-electronic skin that distinguishes temperature from mechanical stimuli. This skin can detect various movements and is applicable in fields including humanoid skin and temperature sensors.
An NTU Singapore study has found that one in three Singaporeans who said they were aware of deepfakes believe they have circulated deepfake content on social media which they later found out was a hoax. When compared to a similar demographic in the United States, the study found that those in the US were more aware of deepfakes. More reported sharing content that they later learnt was a deepfake in the US than in Singapore.
In a noisy room with many speakers, hearing aids can suppress background noise, but they have difficulties isolating one voice - that of the person you're talking to at a party, for instance. Researchers at KU Leuven, Belgium, have now addressed that issue with a technique that uses brainwaves to determine within one second whom you're listening to.
Researchers at ETH Zurich have developed a technique for manufacturing micrometre-long machines by interlocking multiple materials in a complex way. Such microrobots will one day revolutionize the field of medicine.
When the words "artificial intelligence" (AI) come to mind, your first thoughts may be of super-smart computers, or robots that perform tasks without needing any help from humans. Now, a multi-institutional team including researchers from the National Institute of Standards and Technology (NIST) has accomplished something not too far off: They developed an AI algorithm called CAMEO that discovered a potentially useful new material without requiring additional training from scientists.
Northwestern University researchers have developed a new artificial intelligence (A.I.) platform that detects COVID-19 by analyzing X-ray images of the lungs.
Researchers have developed artificial intelligence (AI) models that help them better understand the brain computations that underlie thoughts.
Machine learning has delivered amazing results, but there also have been failures, ranging from the harmless to potentially deadly. New work from University of Houston philosopher Cameron Buckner suggests that common assumptions about the cause behind these supposed malfunctions may be mistaken, information that is crucial for evaluating the reliability of these networks.