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Using Machine Learning with Health Data: The Challenges and Pitfalls

In this contributed article, Elad Ferber, CTO and Co-founder of Spry Health, points out that when considering health data, the level of required customization for machine learning algorithms is very high for 3 reasons: the inherent complexity of the human body, the accessibility and relevance of data sources, and integration into the existing healthcare system.

Case Study: More Efficient Numerical Simulation in Astrophysics

Novosibirsk State University is one of the major research and educational centers in Russia and one of the largest universities in Siberia. When researchers at the University were looking to develop and optimize a software tool for numerical simulation of magnetohydrodynamics (MHD) problems with hydrogen ionization —part of an astrophysical objects simulation (AstroPhi) project—they needed to optimize the tool’s performance on Intel® Xeon Phi™ processor-based hardware.

Neural Machine Translation Evolving at Breakneck Speed

In this special guest feature, Sirena Rubinoff, Content Manager at Morningside Translations, discusses how Neural Machine Translation (NMT), although still relatively new, is quickly transforming into a robust platform for translations. Hardware advances will further contribute to neural networks overall, and NMT in particular.

Logical Glue Develops Machine Learning White Box Insights for Financial Services and Insurance Markets

Logical Glue, the cloud-based software company that helps the financial services and insurance industry reduce risk and increase profits with insightful and faster data-driven decisions, has closed a major private investment from UK entrepreneur Tom Singh. The investment will allow Logical Glue to expand its cloud-based machine learning and statistical modelling platform, further developing its patented “white box” decision-making engine and data visualization tools.

Machine Learning Comes to Tour de France

Amaury Sport Organisation (A.S.O.), organizers of the Tour de France, and Dimension Data, the Official Technology Partner of the Tour de France, announced the introduction of machine learning technologies at this year’s Tour de France to give cycling fans across the globe an unprecedented experience of this year’s event. The race begins in Düsseldorf on Saturday and finishes at the Champs-Élysées in Paris on 23 July.

Ayasdi Unveils Framework to Simplify and Speed Development of Intelligent Applications across the Enterprise

Ayasdi, a leader in machine intelligence software and a pioneer in enterprise-class intelligent applications, announced the release of Ayasdi Envision, a new framework to accelerate the creation of intelligent applications. Built on Ayasdi’s enterprise-class AI platform, the offering is the first of its kind to enable organizations to quickly create and consume intelligent applications that are purpose-built to solve a broad array of real-world business problems.

Building a Machine Learning Platform at Quora

In this MLconf SF 2016 talk “Building a Machine Learning Platform at Quora,” Nikhil Garg, Engineering Manager at Quora, discusses the core ideas behind his company’s machine learning platform, as well as some of the specific systems, tools, and abstractions that have enabled the company to scale their approach to machine learning.

How Enterprises Can Finally Capitalize on Machine Learning

In this special guest feature, Dr. Michael Zeller, SVP, AI Strategy & Innovation at Software AG, discusses how enterprises have reached a pivotal moment for operationalizing machine learning. For a while now artificial intelligence has been over hyped, its benefits over promised and, in the end, it always under-delivered. Now the hype is back stronger than ever. For AI to not fade away again, however, it needs to be made actionable.

Go for Big Data

Many of the hottest modern infrastructure projects are powered by the Go programming language, including Kubernetes, Docker, Consul, etcd, and many more. Go is turning into a go to language for devops, web servers, and microservices. One route to providing robust, performant, and scalable data processing within Go is to utilize the Intel® Data Analytics Acceleration Library (Intel® DAAL) within Go programs.

OpenVX – The Standard for Computer Vision

OpenVX is an API enabling software developers to add hardware accelerated computer vision capabilities to their programs. Coupled with the current upswing in the use of deep learning technologies, computer vision applications with OpenVX are becoming very important. OpenVX is an integral part of Intel Computer Vision SDK. This comprehensive toolkit is for developing and deploying vision-oriented solutions on platforms from Intel, including autonomous vehicles, digital surveillance cameras, robotics, and mixed-reality headsets.