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[slides] @Dyn's Cloud #APM and #NPM at @CloudExpo #AI #ML #Monitoring

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With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA. Join Cloud Expo / @ThingsExpo conference chair Roger Strukhoff (@IoT2040), June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets. Accordingly, attendees at the upcoming 20th Cloud Expo / @ThingsExpo June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track. The upcoming 20th International @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA announces that its Call For Papers for speaking opportunities is open.


Cloud 3.0: The Rise of Big Compute

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Furthermore, the existing category leaders driving billions of dollars of compute heavy workload revenue in the legacy on-premise high performance computing (HPC) market are facing the innovator's dilemma needing to reinvent their entire business to provide effective Big Compute solutions in the space – providing a unique opportunity for the most innovative companies to become category leaders. Just like Big Data removed constraints on data and transformed major enterprise software categories, Big Compute eliminates constraints on compute hardware and provides the ability to scale computational workloads seamlessly on workload-optimized infrastructure configurations without sacrificing performance. A comprehensive Big Compute stack now enables frictionless scaling, application-centric compute hardware specialization, and performance-optimized workloads in a seamless way for both software developers and end-users. Specifically, Big Compute transforms a broad set of full-stack software services on top of specialty hardware into a software-defined layer, which enables programmatic high performance computing capabilities at your fingertips, or more likely, as back-end function evaluations part of software you touch every day.


Using Machine Learning Algorithms to Improve Your Business Workflows

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For example, when you apply machine learning algorithms to a sales workflow process, the technology is constantly learning from its mistakes and reprogramming itself to improve performance. The next generation of productivity software and machine learning might also include more intelligent document creation tools and processes. There's also the prospect of machine learning that complements traditional customer relationship management and collaboration platforms, helping users better capture and interact with customer data and internal content and saving them the time of searching for content across platforms. Applying machine learning to customer service enables organizations to offer a layer of proactive self-help tools that can provide customers with options to resolve their issues without having to call into the actual customer service department.


GE Expands Predix Platform to Advance Industrial Internet Opportunities for Customers

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The Digital Hydro Plant complements GE's Digital Wind Farm, Digital Power Plant for Gas and Digital Power Plant for Steam, enhancing power generation reliability, efficiency, cybersecurity and profitability – targeted to reduce maintenance costs by up to 10%, increase plant availability by as much as 1% and boost revenues by up to 3%. ACQUISITIONS OF BIT STEW SYSTEMS, WISE.IO ACCELERATE DIGITAL INDUSTRIAL TRANSFORMATION GE Digital announced it has acquired Bit Stew Systems to bring its data intelligence capabilities to Predix and other industrial solutions. Wise.io's deep machine learning expertise – combined with GE Digital's existing data science talent and massive portfolio of industrial assets – will advance GE's Digital Twin capabilities and solidify its role as a leader in industrial machine learning. This news follow GE's recent acquisition of ServiceMax, a leader in cloud-based field service management solutions, which enables GE Digital customers to immediately gain more productivity from their assets and find greater efficiency in their field service processes.


NVIDIA Tesla P100 Available on Google Cloud Platform NVIDIA Blog

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NVIDIA Tesla P100 GPUs and Tesla K80 GPUs will be available on Google Cloud Platform, starting early next year. On Google Cloud Platform, Tesla P100 GPUs will be available to Google Compute Engine and Google Cloud Machine Learning users around the world. The Tesla K80 GPU accelerator delivers exceptional performance, with increased throughput that allows researchers to advance their scientific discoveries and developers to boost their web services. Learn more about NVIDIA GPU cloud computing and read Google's announcement.


NVIDIA Tesla P100 Available on Google Cloud Platform NVIDIA Blog

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NVIDIA Tesla P100 GPUs and Tesla K80 GPUs will be available on Google Cloud Platform, starting early next year. On Google Cloud Platform, Tesla P100 GPUs will be available to Google Compute Engine and Google Cloud Machine Learning users around the world. The Tesla K80 GPU accelerator delivers exceptional performance, with increased throughput that allows researchers to advance their scientific discoveries and developers to boost their web services. Learn more about NVIDIA GPU cloud computing and read Google's announcement.


PROS Holdings' (PRO) CEO Andres Reiner on Q3 2016 Results - Earnings Call Transcript

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Before we begin, we must caution you that some of today's remarks, including our guidance, our strategy, our competitive position, future business prospects, revenue, bookings, market opportunities, as well as statements made during the question-and-answer session, contain forward-looking statements. The growing excitement around algorithms, artificial intelligence and machine learning highlights the power for data-science to drive modern commerce. Real-time dynamic pricing, quoting and offers are essential to creating personalized and friction as customer experiences expected in modern commerce and data-science is the key to unlocking it. To simplify their customer experience, the company waned pricing that we both personalized for customer and prescriptive for their sales reps. With our deep industry experience, improving data-science made our cloud based price guidance edition a right fit.


Top Ten Intel Software Developer Stories October

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Machine learning is changing the balance of labor between the decision-making role of humans, and the number-crunching roles of computers. The High Performance Computing (HPC) Center Lunch and Learn seminars are opportunities for students and professional developers to meet with HPC industry experts. Take the difficulty out of managing IoT development by using IoT cloud services from Microsoft Azure* with Intel IoT Technology. Intel Developer Zone experts, Intel Software Innovators, and Intel Black Belt Software Developers contribute hundreds of helpful articles and blog posts every month.


Hewlett Packard Enterprise Powers Machine Learning Apps, Revs Vertica Database

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Haven OnDemand runs on Microsoft Azure, but it's REST-based APIs can be invoked in any services-enabled environment, including Amazon Web Services or hybrid and private clouds. The availability of machine learning services on Amazon, Azure, Google and IBM clouds is clearly a threat to Haven OnDemand. On the in-database front, Vertica 8.0 gains R-based machine learning algorithms that will enable data scientists to model against vast data sets relying on the power of Vertica's massively parallel processing (and thus avoiding moving data to analytic servers or relying on sampling techniques). Vertica was already certified to run on Amazon Web Services, but the 8.0 release adds support for deployment on Microsoft Azure.


Microsoft Eyes AI Supercomputer on Azure

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The infrastructure portion of the effort focuses on combining the processing engines like GPUs and FPGAs designed to improve network connectivity as ways to boost AI performance running on Microsoft's Azure Cloud. Microsoft's AI initiative seeks to "democratize" AI technology through a focus on agents, applications, services and infrastructure. The emerging cloud platform would use an "FPGA fabric" tied to GPU processing to speed applications like machine translation and Bing search queries. Along with the cloud infrastructure push, Microsoft's AI effort also includes a group focusing on furthering Bing search and Cortana development along with robotics and what the company referred to as "ambient computing."