Brian Dipert

Algolux Wins Top AI Award For ADAS and Autonomous Vehicles at Tech.AD Europe 2020 Conference

Montreal, QC – April 22, 2020 – Algolux, the automotive industry’s leading provider of robust and scalable perception solutions, has won the top award at the 2020 Tech.AD Europe Conference. Algolux’s Eos Embedded Perception Software was recognized as the Most Innovative Use of Artificial Intelligence and Machine Learning in the Development of Autonomous Vehicles and […]

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DarwinAI Makes AI Applications More Efficient and Less of a ‘Black Box’ — with Its Own AI

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. As a student pursuing a doctorate in systems design engineering at the University of Waterloo, Alexander Wong didn’t have enough money for the hardware he needed to run his experiments in computer vision. So he invented a

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Speeding Up Deep Learning Inference Using TensorRT

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This is an updated version of How to Speed Up Deep Learning Inference Using TensorRT. This version starts from a PyTorch model instead of the ONNX model, upgrades the sample application to use TensorRT 7, and replaces the

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Upcoming Webinar Discusses Deep Neural Network Quantization Trade-offs and Optimizations

On Thursday, May 7, 2020 at 10 am Pacific Time, Alliance Member company Hailo will present the free webinar “Quantization of Neural Networks – High Accuracy at Low Precision”. From the event page: Quantization is a key component of efficient deployment of deep neural networks. 8-bit quantization holds the promise of 4x reduction in model

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Automotive Lighting: From “Vision” to “Driving Assistance”

Outlines: Automotive lighting market is expected to reach US$38.8 billion by 2024, with 4,9% CAGR between 2018 and 2024. Evolution of lighting technologies enables new functionalities. ADAS vehicles: sensors integration is becoming mandatory. LiDAR integration: OEM s have several requirements at different levels. “Autonomous vehicle technologies have a direct impact on traditional vehicles market and

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Data is Indeed the New Oil, But Not for the Reason You Expect

This blog post was originally published by Bitfury. It is reprinted here with the permission of Bitfury. Discussions about the future of artificial intelligence (AI) often focus on the incredible value that can be gleaned from data. The idea that “data is the new oil” was first attributed to mathematician Clive Humby in 2006, followed

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Intel and Udacity Launch New Edge AI Program to Train 1 Million Developers

What’s New: Today, Intel and Udacity announced the new Intel® Edge AI for IoT Developers Nanodegree Program to train the developer community in deep learning and computer vision, which will accelerate the development and deployment of artificial intelligence (AI) models at the edge by leveraging the Intel® Distribution of OpenVINO™ toolkit. Students who successfully complete the nanodegree program, estimated to take about three

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NVIDIA VRSS, a Zero-Effort Way to Improve Your VR Image Quality

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The Virtual Reality (VR) industry is in the midst of a new hardware cycle – higher resolution headsets and better optics being the key focus points for the device manufacturers. Similarly on the software front, there has been

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Object Recognition: 3 Things You Need to Know

This article was originally published at MathWorks’ website. It is reprinted here with the permission of MathWorks. What Is Object Recognition? Object recognition is a computer vision technique for identifying objects in images or videos. Object recognition is a key output of deep learning and machine learning algorithms. When humans look at a photograph or

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Intel Joins Georgia Tech in DARPA Program to Mitigate Machine Learning Deception Attacks

What’s New: Intel and the Georgia Institute of Technology (Georgia Tech) announced today that they have been selected to lead a Guaranteeing Artificial Intelligence (AI) Robustness against Deception (GARD) program team for the Defense Advanced Research Projects Agency (DARPA). Intel is the prime contractor in this four-year, multimillion-dollar joint effort to improve cybersecurity defenses against deception

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