A new study from the University at Albany shows that artificial intelligence systems may organize information in far more ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

PPA constraints need to be paired with real workloads, but they also need to be flexible to account for future changes.

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Microsoft has revealed it has collaborated with Ciena to define a blueprint for what it calls a zero-trust tiered optical network architecture. In a white paper explaining the nature of the ...

A new technical paper titled “MultiVic: A Time-Predictable RISC-V Multi-Core Processor Optimized for Neural Network Inference” was published by researchers at FZI Research Center for Information ...

[NeurIPS 2019] This is the code repo of our novel passport-based DNN ownership verification schemes, i.e. we embed passport layer into various deep learning architectures (e.g. AlexNet, ResNet) for ...

Abstract: This article presents the development, implementation, and validation of a loss-optimized and circuit parameter-sensitive triple-phase-shift (TPS) modulation scheme for a dual-active-bridge ...

Cisco has embarked on a plan to modernise its campus, branch and industrial networks for the artificial intelligence (AI) era. Cisco believes the new products can simplify operations, scale for ...