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It’s Time to Redesign Medical Data

In the TEDMED talk below, Thomas Goetz looks at medical data, making a bold call to redesign it and get more insight from it. Your medical chart: it’s hard to access, impossible to read — and full of information that could make you healthier if you just knew how to use it.

Data Analytics, Machine Learning, and HPC in Today’s Changing Application Environment

In this video from the Intel HPC Developer Conference, Franz Kiraly from Imperial College London and the Alan Turing Institute describes why many companies and organizations are beginning to scope their potential for applying rigorous quantitative methodology and machine learning.

Performance Optimization of Deep Learning Frameworks on Modern Intel Architectures

In this video from the Intel HPC Developer Conference, Elmoustapha Ould-ahmed-vall from Intel describes how the company is doubling down to optimize Machine Learning frameworks for Intel Platforms. Using open source frameworks as a starting point, surprising speedups are possible using Intel technologies.

Making Data Mean More Through Storytelling

In this TEDx talk, Ben Wellington discusses how to use data to tell stories. In fact, he draws on some key lessons from fields well outside computer science and data analysis to make his observations about New York City fascinating.

Data Hacking: Data Science for Entrepreneurs

In the TEDx video presentation below, Kevin Novak, Senior Data Scientist at Uber, provides a description and history of Uber and how Uber’s data hacking made their explosion possible.

Driving High Frequency Trading and Compliance with In Memory Computing

In the video presentation below, courtesy of our friends over at GridGain, Eric Karpman shares how some of the world’s largest financial institutions use in-memory computing to address the challenges of high frequency trading.

Video: Why use Tables and Graphs for Knowledge Discovery System?

In this video from the 2016 HPC User Forum in Austin, John Feo from PNNL presents: Why use Tables and Graphs for Knowledge Discovery System? “GEMS software provides a scalable solution for graph queries over increasingly large data sets. As computing tools and expertise used in conducting scientific research continue to expand, so have the enormity and diversity of the data being collected. Developed at Pacific Northwest National Laboratory, the Graph Engine for Multithreaded Systems, or GEMS, is a multilayer software system for semantic graph databases. In their work, scientists from PNNL and NVIDIA Research examined how GEMS answered queries on science metadata and compared its scaling performance against generated benchmark data sets. They showed that GEMS could answer queries over science metadata in seconds and scaled well to larger quantities of data.”

Visualizing and Understanding Deep Neural Networks

In this presentation, Matthew Zeiler, Ph.D., Founder and CEO of Clarifai Inc, speaks about large convolutional neural networks. These networks have recently demonstrated impressive object recognition performance making real world applications possible.

Deep Learning at Google with Jeff Dean

In the Google TechTalk video presentation below, luminary Jeff Dean discusses the use of Deep Learning at Google – “Large-Scale Deep Learning for Intelligent Computer Systems.”

Solving the Data Integration Challenge with a Purpose-Built IIoT Application

In the video presentation below, Alex Clark, Chief Software Architect & Founder at BitStew, talks about Industrial Internet of Things (IIoT), its challenges, and opportunities.