In the ever-evolving world of artificial intelligence, deep neural networks (DNNs) have revolutionized data processing, offering unparalleled accuracy across various ...

Google unveils Ironwood, its most powerful TPU, for the age of inference, and Axion Arm VMs promising up to 2× better ...

The authors point out that quantum computers are still plagued by high gate error rates, low qubit counts, and extremely slow ...

The LHCb collaboration developed an inclusive deep-learning flavour tagger for neutral B-mesons, improving tagging power by ...

As the 2025 Atlantic hurricane season winds down, early evaluations of model performance reveal a shift in forecasting reliability that may redefine meteorology. Google DeepMind's Weather ...

A team at Carnegie Mellon University is helping kids understand artificial intelligence with a soft, squishy, LED-lit neural ...

"The papers and data we've presented at the November IEEE conference show how Verseon's advances in AI produce superior results in life-science applications," said Verseon's Head of AI Ed Ratner. "Our ...

Abstract: Hardware-aware Neural Architecture Search (HW-NAS) has garnered significant research interest due to its ability to automate the design of neural networks for various hardware platforms.

Abstract: Spiking Neural Networks (SNNs) have emerged as a compelling alternative to traditional Artificial Neural Networks (ANNs) due to their energy efficiency and biological plausibility. However, ...

The human visual system provides us with a rich and meaningful percept of the world, transforming retinal signals into visuo-semantic representations. For a model of these representations, here we ...

Traditional medical imaging follows a linear workflow: capture → transmit → store → analyze → report. This often involves large imaging files (e.g., DICOM for CT or MRI scans), reliance on PACS ...

Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a ...