Deep Learning Infrastructure Challenges There are three significant obstacles for you to be aware of when designing a deep learning infrastructure: scalability, customizing for each workload, and ...

Google’s deep learning finds a critical path in AI chips The work marks a beginning in using machine learning techniques to optimize the architecture of chips.

With use cases like computer vision, natural language processing, predictive modeling, and much more, deep learning (DL) provides the kinds of far-reaching applications that change the way technology ...

Automated crack detection in civil infrastructure has emerged as a transformative tool in maintenance and safety assessment, utilising advanced deep learning techniques to identify and quantify ...

About Deep Instinct Deep Instinct takes a prevention-first approach to stopping ransomware and other malware using the world’s first and only purpose-built, deep learning cybersecurity framework.

AI is about to make the cloud a lot heavier. Cloud services and private networks for years had to handle relatively limited amounts of data. Now that artificial intelligence and deep learning are ...

MicroCloud Hologram Inc. Develops a Noise-Resistant Deep Quantum Neural Network (DQNN) Architecture to Optimize Training Efficiency for Quantum Learning Tasks ...

Get the details of the unique rack-scale architecture provided by NVIDIA and NetApp. Find out how the purpose-built infrastructure allows organizations to deploy deep-learning workloads and handle ...

The funding, from the Department of Homeland Security, will support the use of machine learning and AI to develop novel solutions to safeguard the critical infrastructure that powers our world.