A new 3D printing system designed by MIT researchers enables realistic variations in glossiness across a 3D printed surface. The advance could aid fine art reproduction and the design of prosthetics.
Deep learning neural networks can be massive, demanding major computing power. In a test of the "lottery ticket hypothesis," MIT researchers have found leaner, more efficient subnetworks hidden within BERT models. The discovery could make natural language processing more accessible.
A groundbreaking study published in Information & Communications Technology Law by experts at the Centre for Law and Development at Qatar University discusses the legal and ethical implications of Big Tech's development of "digital thought clones." Digital thought clones can allow technology companies to accurately predict and influence people's behavior according to their digital habits. The authors call for legislation to protect people from technology companies' malicious use of their digital footprint.
A machine learning model developed in Finland can help us treat cancer more effectively.
The UPV/EHU's IXA group has use natural language processing techniques to overcome one of the major difficulties associated with smart homes, namely that the systems developed to infer activities in one environment do not work when they are applied to a different one, because both the sensors and the activities are different. The group has come up with the innovative idea of using words to represent the activation of both sensors and human activity.
SUTD researchers develop technology which allows for photonic integrated circuits to unlock their potential as high resolution 3D photonic structures in ultra-high speed communications.
Instead of simply applying an AI coach to the entire workforce, managers ought to prudently design it for targeted sales agents.
USC researchers have designed a system that lets robots autonomously learn complicated tasks from a very small number of demonstrations--even imperfect ones. While current state-of-art methods need at least 100 demonstrations to nail a specific task, this new method allows robots to learn from only a handful of demonstrations.
MIT researchers have developed a way for deep learning neural networks to rapidly estimate confidence levels in their output. The advance could enhance safety and efficiency in AI-assisted decision making, with applications ranging from medical diagnosis to autonomous driving.
Researchers at DTU and the University of Copenhagen have developed a ground-breaking model that provides a completely new understanding of our movement patterns. The model can come to play an important role when designing tomorrow's green modes of transport and has just been published in Nature.