Hardware

The ubiquity of smart devices—not just phones and watches, but lights, refrigerators, doorbells and more, all constantly recording and transmitting data—is creating massive volumes of digital information that drain energy and slow data transmission speeds. With the rising use of artificial intelligence in industries ranging from health care and finance... Read more

A new chip aims to dramatically reduce energy consumption while accelerating the processing of large amounts of data.... Read more

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method that aligns memristor hardware's noisy updates with neural network training, slashing energy use by nearly six orders of magnitude versus GPUs while boosting accuracy on vision tasks. The study validates EaPU on 180 nm... Read more

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive optical networks, in particular, enable large-scale parallel computation through the use of passive structured phase masks and the propagation of light. However, one major challenge remains: systems trained in model-based simulations often fail to perform... Read more

Until now, AI services based on large language models (LLMs) have mostly relied on expensive data center GPUs. This has resulted in high operational costs and created a significant barrier to entry for utilizing AI technology. A research team at KAIST has developed a technology that reduces reliance on expensive... Read more

An ultrathin ferroelectric capacitor, designed by researchers from Japan, demonstrates strong electric polarization despite being just 30 nm thick including top and bottom electrodes—making it suitable for high-density electronics. Using a scandium-doped aluminum nitride film as the ferroelectric layer, the team achieved high remanent polarization even at reduced thicknesses. This... Read more

Scientists in China have unveiled a new AI chip called LightGen that is 100 times faster and 100 times more energy efficient than NVIDIA chips, the leading supplier of AI chips worldwide. Instead of using electricity to move information, this new optical chip relies on light to perform complex generative... Read more

A cross-institutional team led by researchers from the Department of Electrical and Electronic Engineering (EEE), under the Faculty of Engineering at The University of Hong Kong (HKU), have achieved a major breakthrough in the field of artificial intelligence (AI) hardware by developing a new type of analog-to-digital converter (ADC) that... Read more

A collaborative team has achieved the first monolithic 3D chip built in a U.S. foundry, delivering the densest 3D chip wiring and order-of-magnitude speed gains.... Read more

MIT researchers have developed a new fabrication method that could enable the production of more energy efficient electronics by stacking multiple functional components on top of one existing circuit.... Read more

Artificial intelligence and machine learning could become dramatically more efficient, thanks to a new type of computer component developed by researchers at the University of California, Santa Barbara and Tohoku University, in collaboration with the Taiwan Semiconductor Manufacturing Company (TSMC).... Read more

Holding a conversation in a crowded room often leads to the frustrating "cocktail party problem," or the challenge of separating the voices of conversation partners from a hubbub. It's a mentally taxing situation that can be exacerbated by hearing impairment.... Read more

The expansion of data centers to power the AI boom has more people wondering: what exactly is in a data center?... Read more

Developing chips that simulate how the brain works has great promise for AI, robotics, and other fields. But making them so that they're scalable while providing repeatable results has proven tricky. Now, a Yale-led team of researchers has put forth a solution. The results are published in Nature Communications.... Read more

Addressing the staggering power and energy demands of artificial intelligence, engineers at the University of Houston have developed a revolutionary new thin-film material that promises to make AI devices significantly faster while dramatically cutting energy consumption.... Read more