GAZELLE Helps Neural Networks Run 30 Times FasterNews
A novel encryption method devised by MIT researchers secures data used in online neural networks and blends two conventional techniques — homomorphic encryption and garbled circuits — in a way that helps the networks run orders of magnitude faster than they do with conventional approaches.READ MORE
Robots Can Better Influence Kids' OpinionsNews
Young children are significantly more likely than adults to have their opinions and decisions influenced by robots, according to new research. The study compared how adults and children respond to an identical task when in the presence of both their peers and humanoid robots.READ MORE
Supercomputer Simulations Shows HIV TargetsNews
HIV-1 replicates in ninja-like ways. The virus slips through the membrane of vital white blood cells. Inside, HIV-1 copies its genes and scavenges parts to build a protective bubble for its copies. Now, supercomputers have helped model a key building block in the HIV-1 protective capsid, which could lead to strategies for potential therapeutic intervention in HIV-1 replication.READ MORE
Scientists have laid the statistical foundation for calculating match statistics when using Next Generation Sequencing, which produces forensic DNA profiles that can be more useful in solving some crimes.READ MORE
A new machine-vision system can distinguish between dead irises and live ones.READ MORE
The National Institutes of Health’s Clinical Center has made a large-scale dataset of CT images publicly available to help the scientific community improve detection accuracy of lesions. While most publicly available medical image datasets have less than a thousand lesions, this dataset, named DeepLesion, has over 32,000.
A new approach to machine learning enables AI to make the rules.READ MORE
Computer scientists examine how a doctor’s “gut feeling” influences how many tests they order for patientsREAD MORE
Researchers have shown that it is possible to train artificial neural networks directly on an optical chip. The significant breakthrough demonstrates that an optical circuit can perform a critical function of an electronics-based artificial neural network and could lead to less expensive, faster and more energy efficient ways to perform complex tasks such as speech or image recognition.
Predicting genes that can cause disease due to the production of truncated or altered proteins that take on a new or different function, rather than those that lose their function, is now possible thanks to an international team of researchers that has developed a new analytical tool to effectively and efficiently predict such candidate genes.