English
Arabic
Chinese (Simplified)
Dutch
Esperanto
French
German
Greek
Italian
Japanese
Korean
Portuguese
Russian
Spanish
UrduA framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a study led by engineers at the University of California San Diego. In the paper, which was published May 30 in Nature Machine Intelligence, researchers present HypOp, a framework that uses unsupervised learning and hypergraph neural networks.
Tag: chip design
‘Surprising’ hidden activity of semiconductor material spotted by researchers
Using advanced imaging techniques, an international team led by Penn State researchers found that the material that a semiconductor chip device is built on, called the substrate, responds to changes in electricity much like the semiconductor on top of it.
A new neuromorphic chip for AI on the edge, at a small fraction of the energy and size of today’s compute platforms
An international team of researchers has designed and built a chip that runs computations directly in memory and can run a wide variety of AI applications–all at a fraction of the energy consumed by computing platforms for general-purpose AI computing. The NeuRRAM neuromorphic chip brings AI a step closer to running on a broad range of edge devices, disconnected from the cloud, where they can perform sophisticated cognitive tasks anywhere and anytime without relying on a network connection to a centralized server.
Pushing the Boundaries of Moore’s Law: How Can Extreme UV Light Produce Tiny Microchips?
Some analysts say that the end of Moore’s Law is near, but Patrick Naulleau, the director of Berkeley Lab’s Center for X-Ray Optics (CXRO), says that it could be decades before the modern chip runs out of room for improvement, thanks to advances in materials and instrumentation enabled by the CXRO.