May 31, 2018   |   Yulia Tell, Jiao Wang

Data Analytics and AI are Just What the Doctor Ordered

The healthcare industry is ripe for adoption of multiple aspects of artificial intelligence (AI).  In a segment with an abundance of use cases to inform AI solutions, it’s easy to see how the healthcare industry can benefit from the insights provided by AI. And the stakes are high when patient outcomes can be impacted by…

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#Solutions #Technology

May 24, 2018   |   Yurong Chen, Daniel Cobb

Analyzing and Understanding Visual Data

Currently, more than 75% of all internet traffic is visual (video/images). Total traffic is exploding, projected to jump from 1.2 zettabytes per year in 2016, to 3.3 zettabytes in 2021, and visual data will comprise roughly 2.6 zettabytes of that. A major challenge for applications is how to process and understand this visual data, a…

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#Research #Technical Blog

May 23, 2018   |   Yinyin Liu, Harini Eavani, Zach Dwiel

Applying Deep Learning to Genomics Analysis

Synthetic Genomics, Incorporated (SGI) is a synthetic biology company that aims to bring genomic-driven solutions to market. They design and build biological systems and conduct interdisciplinary research by combining biology and engineering to address global sustainability problems SGI asked for Intel’s help to conduct a deep learning proof of concept that would automatically tag a…

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May 23, 2018   |   Yinyin Liu, Moshe Wasserblat

Introducing NLP Architect by Intel AI Lab

Many advances in Natural Language Processing (NLP) and Natural Language Understanding (NLU) in recent years have been driven by advancements in the field of deep learning with more powerful compute resources, greater access to useful data sets, and advances in neural network topologies and training paradigms. At Intel AI Lab, our team of NLP researchers…

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May 22, 2018   |   Hanlin Tang

Deep Learning for Remote Sensing

A remarkable aspect of deep learning is that its neural networks are powerful learning machines that generalize to different domains. For example, semantic segmentation model performs the underlying task of classifying pixels, whether those pixels are photons from a camera mounted on a self-driving car, radiodensities from X-ray tubes in a CT scanner, or seismic…

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May 16, 2018   |   Naveen Rao

Helping Developers Make AI Real

The pace of AI developer community growth and advancement is incredible. Kaggle added more than 600,000 new users in 2017, twice as many as in 2016[1]. The Scopus database now contains more than 200,000 papers indexed with the key term “artificial intelligence.”[2] Dozens of new AI submissions are posted to each week. Driven by…

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May 03, 2018   |   Elson Rodriguez

Our Friend the Object Store

This is your Tensorflow I/O operation: This is your Tensorflow I/O operation on S3: Any questions? … ...Oh wait, you have a ton of questions and doing this awesome thing interests you greatly? What’s going on here? Back in July 2017, Yong Tang added an S3 backend for Tensorflow’s Filesystem interface. This means almost anywhere…

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#Technology #Tutorial

May 02, 2018   |   Harsh Kumar

An End-to-End Video Analytics Solution for Surveillance and Securing High-Value Assets

Currently, corporations struggle to safeguard their workers from accidents and monitor remote operations such as oil fields, oil pipelines, transmission lines, transportation goods, machinery, plants, etc. for malfunctions. Often broken equipment, pipeline, or other nefarious activity goes unnoticed for a long period of time causing a great amount of loss. With computer vision and deep…

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May 01, 2018   |   Srinivasa Karlapalem

High-throughput Object Detection on Edge Platforms with FPGA

This article introduces software and deep neural network architecture (DNN) level optimizations and tweaks to achieve high throughput with deep learning based object detection applications and FPGAs on edge platforms. The ideas presented here could be generalized to speed up other compute-intensive applications on edge platforms as well. Contents Overview of Edge Platforms Introduction to…

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May 01, 2018   |   Andres Rodriguez, Wei Li, Jason Ye, Rinat Rappoport, Eden Segal, Koichi Yamada, Niharika Maheshwari, Rong Zhang, Etay Meiri, Amit Bleiweiss, Zhiyuan Huang

Amazing Inference Performance with Intel® Xeon® Scalable Processors

[bc playerid="4090876643001" videoid="5780439477001"] Over the past year, Intel has focused on optimizing popular deep learning frameworks and primitives for Intel® Xeon® processors.  Now, in addition to being a common platform for inference workloads, Intel Xeon Scalable processor (formerly codename Skylake-SP) is a competitive platform for both training and inference. Previously, deep learning training and inference…

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