Based on a unique deep learning architecture, ... they deal with specific light sources on a black background. ... The use of the new possibilities of machine learning is key here.

A new computing architecture enables advanced machine-learning computations to be performed on a low-power, memory-constrained edge device. The technique may enable self-driving cars to make ...

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

Machine learning applications in data centers (or “the cloud”) have pervasively changed our environment. Advances in speech recognition and natural language understanding have enabled personal ...

Looking forward, the team aims to scale these models for larger, more complex datasets and explore further optimizations in quantum state encoding and quantum machine learning architecture design.

The process of building and using machine learning architecture doesn’t move at the speed of business. In fact, data scientists and developers are attempting to build the most powerful, sophisticated ...

“AutoML goes beyond creating machine learning architecture models,” says Collins. “It can automate many aspects of machine learning workflow, which include data preprocessing, feature engineering, ...

image: This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms.