An innovative approach to artificial intelligence (AI) now enables the reconstruction of extensive datasets, such as overall ocean temperature, from a small number of field-deployable sensors using low-powered edge computing. This method holds broad applications across industry, science, and medicine.

“We developed a neural network that allows us to represent a large system in a very compact way,” said Javier Santos, a researcher at Los Alamos National Laboratory. “That compactness means it requires fewer computing resources compared to state-of-the-art convolutional neural network architectures, making it well-suited to field deployment on drones, sensor arrays, and other edge-computing applications that put computation closer to its end use.”

When considering a pair of premium headphones or earbuds, two critical factors often come to mind: noise isolation and transparency. Active Noise Cancellation (ANC) blocks all external noise, allowing you to hear only the audio from your device. Transparency mode lets some ambient sound through while still playing your music. Apple and Sony have excelled in these technologies, but no current audio gear can focus on a single external sound source.

Imagine wanting to hear only one person’s voice in a crowded room. Researchers at the University of Washington have developed an AI-driven headphone kit that allows you to focus on a specific person’s speech. This technology, called “Target Speech Hearing,” uses a brief visual cue—looking at the person for three to five seconds—to isolate their voice. Remarkably, it works even if you’re moving around and not directly facing the speaker.