…expect the arms race to continue Aug 27, 2018 Source Awesome, not awesome. #Awesome“In 2014, Flint began getting water from Flint River rather than the Detroit water system. Mistreatment of the new water supply, combined with old lead pipes, created contaminated water for residents…Records that could be used to figure out which houses might be affected by […]
Archives for August 2018
GitHub process automation: A bot to build pull requests authorized by core maintainers
We are maintaining multiple Open Source projects where we focus on CloudFormation templates. To ensure that the templates are of high quality, we leverage automated testing and pull requests. We could use the CodeBuild GitHub integration to execute yamllint, cfn-lint, and also aws cloudformation validate-template to make sure that a pull request is not breaking […]
Navigant Research Publishes Report on Key Issues with Autonomous Vehicle Data
The autonomous systems piloting self-driving cars will make decisions that have life-and-death consequences. There is little room for error in their ability to classify and track objects in a vehicle’s vicinity. That’s why in developing vehicle perception systems, curating high-quality training and validation datasets is critical. For example, seeing in training data how a pedestrian […]
If cancer-spotting algorithms are only trained on fair skinned people…
…the survival rate of dark skinned people will decrease. Aug 20, 2018 Source Awesome, not awesome. #Awesome“A team at DeepMind, based in London, created an algorithm… to enable a computer to analyse optical coherence tomography (OCT), a high resolution 3D scan of the back of the eye… [a]rtificial intelligence performed as well as two of the […]
What We Learned About Localization Accuracy of Vehicle Detection Models (Part 3)
Editor’s note: This is the third in a series of three posts outlining the findings of research our in-house computer vision team conducted regarding the accuracy of popular open-source object detection models for detecting vehicles, as measured by pixel level accuracy. Before diving in, be sure to check out part one and part two to […]
Our Findings on Localization Accuracy of Vehicle Detection Models (Part 2)
Editor’s note: This is the second in a series of three posts outlining the findings of research our in-house computer vision team conducted regarding the accuracy of popular open-source object detection models for detecting vehicles, as measured by pixel level accuracy. Before diving in, be sure to check out part 1 to understand the scope […]
Our Research on Localization Accuracy of Vehicle Detection Models (Part 1)
Editor’s note: This is the first in a series of three posts outlining the findings of research our in-house computer vision team conducted regarding the accuracy of popular open-source object detection models for detecting vehicles, as measured by pixel level accuracy. Why we conducted this research Autonomous driving technology requires accurate detection of traffic participants […]
Azure #HDInsight Interactive Query: simplifying big data analytics architecture
Fast Interactive BI, data security and end user adoption are three critical challenges for successful big data analytics implementations. Without right architecture and tools, many big data and analytics projects fail to catch on with common BI users and enterprise security architects. In this blog we will discuss architectural approaches that will help you architect […]
Advanced Analytics is coming into Azure Portal
We see Azure Monitor users are using both the Log Search page and the Analytics portal to accomplish their tasks. The Analytics portal offers advanced features, and we’re happy to announce it’s coming into Azure! This is another step on our journey to consolidate and unify all Log Analytics experiences under Azure Portal. What’s coming? […]
Azure #HDInsight Apache Phoenix now supports Zeppelin
The HDInsight team is excited to announce Apache Zeppelin Support for Apache Phoenix Phoenix in Azure HDInsight Apache Phoenix is an open source, massively parallel relational database layer built on HBase. Phoenix allows you to use SQL like queries over HBase. Phoenix uses JDBC drivers underneath to enable users to create, delete, alter SQL tables, […]
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