Modern artificial intelligence systems rely on moving large amounts of data between memory and processors, a design that limits speed and increases energy use. The human brain works differently: it combines memory and computation within synapses, allowing fast, efficient learning and perception. Replicating this approach in hardware is a central goal of neuromorphic computing, especially for tasks like vision, where most real-world information is gathered and processed.
Most smartphones, portable computers and other devices on the market today are powered by lithium-ion (Li-ion) batteries. While these rechargeable batteries perform remarkably well, they are based on lithium, which is not as abundant as other materials and is not evenly distributed across different countries worldwide.
The rapid expansion of soft robots and smart electronic devices is driving demand for materials that can not only move and adapt, but also complete their missions without leaving behind unwanted traces. As these technologies are increasingly explored for health care, environmental monitoring, infrastructure inspection, and security applications, robots and devices are expected to operate in places where human access is limited—such as narrow pipes, sealed spaces, underground facilities, and hazardous environments.
Metamaterials—the term may sound esoteric to the layman. In science and engineering, however, this is an interesting field of research that has developed at a highly dynamic pace, particularly since the 1990s.
Rising fuel prices triggered by the Middle East war are driving a sharp increase in carpooling, with a ride-sharing platform reporting a surge in new users seeking cheaper ways to travel.
Faculty in the Cockrell School of Engineering have developed a rare printer as part of a larger project to speed up production and lower costs of manufacturing semiconductors critical to modern electronics.
Battery electrolytes aren't just one chemical, but a complex mixture of salts, solvents, and additives interacting and reacting with each other. Artificial intelligence has made great headway in helping select ideal materials to go into that chemical soup. But a team from the University of Chicago Pritzker School of Molecular Engineering (UChicago PME) is using AI to generate the entire formulation, balancing the complicated tradeoffs and interactions that go into the electrolytes that make batteries possible.
By stacking transistors on top of one another, rather than laying them side by side on a flat chip, many electronic engineers are hopeful that vast amounts of computing power could be packed into tiny spaces, all while cutting energy use. So far, however, the ability to build these monolithic 3D integrated circuits has proven stubbornly difficult, largely because the fabrication processes required can damage the layers already in place.
New research by Brown University computer scientists may be a key step in bringing volumetric video—video that can be viewed from virtually any perspective in a 3D scene—to computers and smart televisions.
What happens to language when a growing amount of text published in the press, online and on social media is written by machines? This question is not just important for the profession of journalism—it also has an impact on the richness of the language we all use to comprehend, describe and discuss reality itself.
The transition to renewable energy is not just about installing more solar panels and wind turbines. Without smarter market rules, the energy transition could become unnecessarily expensive and deepen inequality. That is the conclusion of new research by Dongchen He, who examined how electricity markets and subsidy policies should adapt as renewable energy becomes dominant.
From the shallow shores of Lake Wahlberg to the salty depths of the ocean, University of Florida researchers are dropping robots in the water and training them to communicate more efficiently in murky conditions.
By electrochemically introducing phosphonate ester groups into conductive polymer films, researchers at Science Tokyo have addressed a fundamental trade-off between electronic charge transport and ion transport, overcoming a key performance limitation in organic electrochemical transistors (OECTs).
Operating large language model (LLM) services like ChatGPT requires a server infrastructure on the scale of tens of thousands of units. However, constructing actual equipment every time a new AI semiconductor or system architecture needs to be verified incurs massive costs and time.
As the global transition toward carbon neutrality accelerates, "water electrolysis"—a technology that splits water electrically to produce clean hydrogen—is drawing significant attention. However, a major limitation has been the decline in efficiency caused by bubbles formed during the electrolysis process that block the pathways.
Artificial intelligence chatbots need to work on their social judgment, recent events suggest. At one end of the spectrum, they're facing lawsuits for recommending dangerous actions. At the other end, the models can be so nice they're considered sycophantic.
Researchers from Kyushu University and DENSO IT Laboratory, Inc. have developed a new method to improve the accuracy of indirect Time-of-Flight (I-ToF) cameras. The technology considers the practical limitations of real-world sensors during the design process.
Modern power systems are rapidly evolving into highly digitized smart grids, increasing their complexity at an unprecedented pace. Renewables, batteries, electric vehicles, power electronics, sensors and real-time control systems are all expanding rapidly, and this is making electricity grids significantly harder to simulate, optimize, secure and operate.
SUTD researchers have developed a reinforcement-learning-based safety system that teaches a stair-traversing service robot to brace itself mid-fall, addressing one of the biggest barriers to deploying autonomous robots on staircases.
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