Hardware

Edge computing is an emerging IT architecture that enables the processing of data locally by smartphones, autonomous vehicles, local servers, and other IoT devices instead of sending it to be processed at a centralized large data center. This approach could allow artificial intelligence (AI) models and other computational systems to... Read more

A team led by engineers at the University of California San Diego has developed a new brain-inspired hardware platform that could help computer hardware keep pace with the explosive growth of artificial intelligence. By combining memory and computation on the same chip—and allowing its components to interact collectively like neurons... Read more

Australian researchers have built an ultra-compact artificial intelligence (AI) chip that is able to make calculations using the power of light, at the speed of light. The nano photonic chip prototype, which harnesses the power of light particles (photons) is built completely in-house at the Sydney Nano Hub at the... Read more

Most materials we use in everyday life expand slightly when heated and return to their original size when cooled. In addition to such thermal properties, materials can also have electrical properties or magnetic properties, and traditionally we have used these characteristics separately. However, some materials allow multiple properties to coexist... Read more

Around the world, scientists are exploring an unexpected solution to the growing data crisis: storing digital information in synthetic DNA. The idea is simple but powerful—DNA is one of the most compact, durable information systems on Earth. But one issue has held the field back. Once data is written into... Read more

A research team led by Professor Taesung Kim from the School of Mechanical Engineering at Sungkyunkwan University has developed a technology that precisely controls the internal structure of semiconductors using heat, much like stamping out "bungeoppang" (fish-shaped pastry) in a mold. The team report that this approach improves the performance... Read more

A miniaturized radar chip, developed by researchers at Science Tokyo, advances Integrated Sensing and Communication for Beyond 5G and 6G systems. Measuring just 0.24 mm2 and consuming only 9.8 mW, the compact, low-power device generates high-speed, highly linear chirps by embedding linearization directly into the hardware, overcoming traditional speed-versus-accuracy limits... Read more

Over the past few decades, electronics engineers have been trying to develop new neuromorphic hardware, systems that mirror the organization of neurons in the human brain. These systems could run artificial intelligence (AI) models, particularly artificial neural networks (ANNs) more reliably and efficiently than existing devices.... Read more

A new study has demonstrated how networks of spiking nanolasers could emulate a key principle of brain function: to imagine things that we cannot directly perceive by sampling from internal models of the world. The study, led by scientists from the University of Bern in collaboration with Thales Research &... Read more

Bees navigate their surroundings with astonishing precision. Their brains are now inspiring the design of tiny, low-power chips that could one day guide miniature robots and sensors.... Read more

The use of artificial intelligence (AI) systems, such as the models underpinning the functioning of ChatGPT and various other online platforms, has grown exponentially over the past few years. Current hardware and electronic devices, however, might not be best suited for running these systems, which are computationally intensive and can... Read more

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