See the heat: An infrared imaging system that outputs in color

Researchers achieved that by combining mercury telluride colloidal quantum dots, which absorb infrared light, and a ...

Bringing complex field physics to the tabletop: A photonic stage for non-Abelian gauge fields

For most theories in physics, the order of operations has little impact on the result. When setting a dial to a certain ...
CIE – Components in Electronics

Mercury Systems advances AI/ML electronic warfare in space

Artificial intelligence (AI) and machine learning (ML) are moving from terrestrial data centres into space-qualified ...

Nvidia is putting its Vera CPUs to work alongside AI agents to speed up chip design

Nvidia is creating a kind of continuous feedback loop, where its current generation Vera CPUs speed up the development of ...
Microwaves & RF

Wideband, Direct-RF SoC FPGAs Boost DSP Capabilities at the Edge

Altera’s latest devices address growing demands for bandwidth, flexibility, and real-time processing across aerospace, ...
eLife

A stable cryogenic fluorescence microscope for correlative super-resolution light and electron microscopy

In this useful Tools & Resources article, the authors describe a new cryogenic light microscopy design and characterize its temperature and spatial stability. This compelling system avoids the ...
Electronic Design

AMD Moves from HBM to LPDDR5X with New Memory-on-Package SoC

The differences between AMD’s new LPDDR5X memory-on-package (MoP) architecture and HBM. How hyperscalers are aggressively stockpiling AI chips, leading to HBM shortages and rising costs. How AMD’s MoP ...
IEEE

LUT-Based Convolutional Tsetlin Machine Accelerator with Dynamic Clause Scaling for Resources Constrained FPGAs

Abstract: The rapid growth of machine learning (ML) workloads, particularly in computer vision applications, has significantly increased computational and energy demands in modern electronic systems, ...
IEEE

Real-Time Classification of Vehicles Using Machine Learning Algorithm on the Extensive Dataset

Vehicle classification (VC) is a prominent research domain within image processing and machine learning (ML) for identifying vehicle volumes and traffic rule violations. In developed countries, nearly ...