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, ...

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 ...

Agnik, the global leader of the vehicle analytics market, announced today that it is going to offer a wide range of Deep Machine Learning-based solutions for powering its new and existing products in ...

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 ...

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

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 ...

A research team has developed an AI-based approach to streamline the evaluation of maize haploid fertility restoration, a key bottleneck in double haploid (DH) breeding.