Machine Learning Paves Way for Smarter Particle Accelerators

Scientists have developed a new machine-learning platform that makes the algorithms that control particle beams and lasers smarter than ever before. Their work could help lead to the development of new and improved particle accelerators that will help scientists unlock the secrets of the subatomic world.

Tiny Limbs and Long Bodies: Coordinating Lizard Locomotion

Using biological experiments, robot models, and a geometric theory of locomotion, researchers at the Georgia Institute of Technology investigated how and why intermediate lizard species, with their elongated bodies and short limbs, might use their bodies to move. They uncovered the existence of a previously unknown spectrum of body movements in lizards, revealing a continuum of locomotion dynamics between lizardlike and snakelike movements.

Scientists Create a Labor-Saving Automated Method for Studying Electronic Health Records

Scientists at the Icahn School of Medicine at Mount Sinai described the creation of a new, automated, artificial intelligence-based algorithm that can learn to read patient data from electronic health records. In a side-by-side comparison, they showed that their method, called Phe2vec (FEE-to-vek), accurately identified patients with certain diseases as well as the traditional, “gold-standard” method, which requires much more manual labor to develop and perform

Developing Smarter, Faster Machine Intelligence with Light

SUMMARYResearchers at the George Washington University, together with researchers at the University of California, Los Angeles, and the deep-tech venture startup Optelligence LLC, have developed an optical convolutional neural network accelerator capable of processing large amounts of information, on the…

Photon-Based Processing Units Enable More Complex Machine Learning

Machine learning performed by neural networks is a popular approach to developing artificial intelligence, as researchers aim to replicate brain functionalities for a variety of applications. A paper in the journal Applied Physics Reviews proposes a new approach to perform computations required by a neural network, using light instead of electricity. In this approach, a photonic tensor core performs multiplications of matrices in parallel, improving speed and efficiency of current deep learning paradigms.

Silicon ‘neurons’ may add a new dimension to computer processors

When it fires, a neuron consumes significantly more energy than an equivalent computer operation. And yet, a network of coupled neurons can continuously learn, sense and perform complex tasks at energy levels that are currently unattainable for even state-of-the-art processors.What does a neuron do to save energy that a contemporary computer processing unit doesn’t?Computer modelling by researchers at Washington University in St.