Deep neural networks have a huge advantage: They replace “feature engineering”—a difficult and arduous part of the classic machine learning cycle—with an end-to-end process that automatically learns ...

Neural Architecture Search (NAS) is an emerging area focused on automating the design of neural network architectures. The overarching goal of NAS research is to discover optimal network architectures ...

Announced at the annual Qualcomm Snapdragon Tech Summit on Tuesday, the companies said that the collaboration will focus on the development of Vertex AI Neural Architecture Search (NAS), a managed ...

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...

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This book explores the interdisciplinary project that brings the long tradition of humanistic inquiry in architecture together with cutting-edge research in artificial intelligence. The main goal of ...

Deep learning researchers have been dancing around a looming performance wall in recent months, as huge neural networks push the limits in terms of computation and power consumption. But now a company ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

This book explores the interdisciplinary project that brings the long tradition of humanistic inquiry in architecture together with cutting-edge research in artificial intelligence. The main goal of ...