The deep learning field has been dominated by “large models” requiring massive computational resources and energy, leading to unsustainable environmental and economic challenges. To address this, ...

Recent survey delivers the first systematic benchmark of TSP solvers spanning end-to-end deep learners, hybrid methods and ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Researchers developed a fully integrated photonic processor that can perform all the key computations of a deep neural network on a photonic chip, using light. This advance could improve the speed and ...

Crop nutrition and quality formation are complex processes influenced by genotype, environment, and management practices.

A new technical paper titled “StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign” was published by Intel. “In this paper, we propose StruM, a novel structured ...

The deep neural network models that power today’s most demanding machine-learning applications are pushing the limits of traditional electronic computing hardware, according to scientists working on a ...