Blog Posts

This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. Quantized neural networks (QNNs) are regularly used to improve network efficiency in deep learning. Though there has been much research into different quantization schemes, the number of bits required and the best quantization scheme is still unknown. […]

This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. We are pleased to announce the open source release of HE-Transformer, a homomorphic encryption (HE) backend to nGraph, Intel’s neural network compiler. HE allows computation on encrypted data. This capability, when applied to machine learning, allows data

This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. Deep Learning (DL) computational performance is critical for scientists and engineers applying deep learning techniques to many challenges in healthcare, commerce, autonomous driving, and other domains. This is why in March, we released an early version of

This blog post was originally published at videantis' website. It is reprinted here with the permission of videantis. Since AlexNet in 2012, deep learning (DL) has taken the world of image processing by storm. Working on vision applications for automotive, smartphones, data centers, augmented reality, or using image processing in any shape or form? Then

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. Autonomous vehicles promise to reduce traffic accidents by replacing unpredictable human drivers with artificial intelligence. But how do manufacturers ensure these new drivers are truly safe? To help answer that, NVIDIA has released the Self-Driving Safety Report.

This blog post was originally published at Intel's website. It is reprinted here with the permission of Intel. Artificial intelligence and the Internet of Things are helping companies make the factory of the future a reality by harnessing the power of machine vision, connected devices, and real-time insights. Designing and implementing smart factories requires the

This blog post was originally published at videantis' website. It is reprinted here with the permission of videantis. It seems like it was only yesterday that Robert Stead from Sense Media organized his first AutoSens conference, but time flies when you’re having fun, and last week it was already the fifth AutoSens show that took

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. The hit 1982 TV series Knight Rider, starring David Hasselhoff and a futuristic crime-fighting Pontiac Firebird, was prophetic. The self-driving, talking car also offers a Hollywood lesson in image and language recognition. If scripted today, Hasselhoff’s AI

This blog post was originally published at Camio's website. It is reprinted here with the permission of Camio. Assembling realistic and relevant training data is critical to the quality of AI classifiers. But finding and collecting all that real-life data is hard — especially when the training data is specialized for specific camera scenes and private to

This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. Self-driving cars and trucks are the talk of the town, but trains could be first out of the station as a fully autonomous form of transportation. That’s because — unlike passenger vehicles or long-haul trucks — a