A USC Viterbi undergraduate and her professor developed a method that allows AI to fix its own knowledge gaps in real time.
Category: robotics/AI – Page 5
Rethinking brain-like artificial intelligence: New study reveals hidden mismatches
A new study by York University researchers has found a potential striking flaw in artificial intelligence (AI) models. Artificial neural networks (ANNs), a type of AI model built to solve vision tasks for computers, have surprisingly emerged as the current best understanding of how our own brainâs visual system works, in the last decade. But does current AI really work like a primate brain?
âArtificial intelligence systems are often described as âbrain-likeâ because they can predict activity in parts of the brain that help us recognize objects,â says York University Assistant Professor Kohitij Kar, senior author of a new study. âUntil now, scientists mostly tested this in one direction. They asked whether AI models can predict brain activity.â
In this study, the researchers flipped the questionâif AI truly mirrors the brain, shouldnât brain activity also be able to predict whatâs happening inside the AI model?âand developed a reverse predictivity test to find the answer. The findings are published in the journal Nature Machine Intelligence.
The influencers with millions of followers who donât actually exist
Lil Miquela has 2.5 million Instagram followers, a high-fashion wardrobe, and a clear political voice. She has advocated for Black Lives Matter and the LGBTQI+ community, fronted major brand campaigns, and built a devoted global fanbase. She also has no pulse.
Lil Miquela is a virtual influencer, a computer-generated character designed to look, sound, and behave like a real person. And she is not alone.
In China, Liu Yexi blends traditional aesthetics with cyberpunk visuals to amass a huge following. Ling, created by Chinese AI startup Xmov, has promoted Tesla, Vogue, and luxury tea brand Nayuki.
Chip-scale light technology could power faster AI and data center communications
Researchers at Trinity have developed a new light-based technology on a tiny chip that could help make the data centers behind cloud computing, artificial intelligence, and global internet services faster and more efficient. In the new research, recently published in Nature Communications, the Trinity team reported one such promising advance with collaborators at the University of Bath and the Swiss Federal Institute of Technology Lausanne (EPFL).
The team developed a new way to generate extremely stable signals of light using microscopic ring-shaped devices called âmicroresonators.â These signals form what scientists call optical frequency combs, sometimes described as âoptical rulersâ because they produce a series of evenly spaced colors of light that can be used to measure light with remarkable precision.
The researchers also demonstrated a new type of light pulse called a âhyperparametric soliton.â This stable pulse is the key behind the major advancement in this work, as it allows the comb signals to be produced at different colors of light from the laser that powers the device.
