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Artificial brains could point the way to ultra-efficient supercomputers
Sandia National Labs cajole Intel's neurochips into solving partial differential equations New research from Sandia National ...
Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...
Researchers have developed a new computational approach that uncovers possible drugs for specific cellular targets for ...
Abstract: An active research topic in the array signal processing field is the direction of arrival (DOA) estimation, where establishing an efficient estimation of radio waves received from an antenna ...
Despite incredible progress, the capabilities of artificial intelligence are still limited when compared against real-world expectations. We build complex models, run neural networks, and test ...
MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...
anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...
The relentless advancement of artificial intelligence (AI) across sectors such as healthcare, the automotive industry, and social media necessitates the development of more efficient hardware ...
TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.
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