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With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. Join Cloud Expo @ThingsExpo conference chair Roger Strukhoff (@IoT2040), October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, 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 21st Cloud Expo @ThingsExpo October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, 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 AI Era Ignited by GPU Deep Learning

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Soon, hundreds of billions of devices will be infused with intelligence. AI will revolutionize every industry. READ MORE 7. 7 The global ecosystem for NVIDIA GPU Deep Learning has scaled out rapidly. Breakthrough results triggered a race to adopt AI for consumer internet services: TRANSLATION RECOGNITION SEARCH RECOMMENDATIONS 8. 8 Cloud service providers, from Alibaba and Amazon to IBM and Microsoft, make the NVIDIA GPU deep learning platform available to companies large and small. Pinterest is Changing Online Retail with GPUs 12. 12 AI can solve problems that seemed well beyond our reach just a few years back.


Nvidia CEO's "Hyper-Moore's Law" Vision for Future Supercomputers

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Over the last year in particular, we have documented the merger between high performance computing and deep learning and its various shared hardware and software ties. This next year promises far more on both horizons and while GPU maker Nvidia might not have seen it coming to this extent when it was outfitting its first GPUs on the former top "Titan" supercomputer, the company sensed a mesh on the horizon when the first hyperscale deep learning shops were deploying CUDA and GPUs to train neural networks. All of this portends an exciting year ahead and for once, the mighty CPU is not the subject of the keenest interest. Instead, the action is unfolding around the CPU's role alongside accelerators; everything from Intel's approach to integrating the Nervana deep learning chips with Xeons, to Pascal and future Volta GPUs, and other novel architectures that have made waves. While Moore's Law for traditional CPU-based computing is on the decline, Jen-Hsun Huang, CEO of GPU maker, Nvidia told The Next Platform at SC16 that we are just on the precipice of a new Moore's Law-like curve of innovation--one that is driven by traditional CPUs with accelerator kickers, mixed precision capabilities, new distributed frameworks for managing both AI and supercomputing applications, and an unprecedented level of data for training.


IBM and Nvidia make deep learning easy for AI service creators with a new bundle

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On Monday, IBM announced that it collaborated with Nvidia to provide a complete package for customers wanting to jump right into the deep learning market without all the hassles of determining and setting up the perfect combination of hardware and software. The company also revealed that a cloud-based model is available as well that eliminates the need to install local hardware and software. To trace this project, we have to jump back to September when IBM launched a new series of "OpenPower" servers that rely on the company's Power8 processor. The launch was notable because this chip features integrated NVLink technology, a proprietary communications link created by Nvidia that directly connects the central processor to a Nvidia-based graphics processor, namely the Tesla P100 in this case. Server-focused x86 processors provided by Intel and AMD don't have this type of integrated connectivity between the CPU and GPU.


[session] #MachineLearning - It's All About the Data @CloudExpo #BigData

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Data is the fuel that drives the machine learning algorithmic engines and ultimately provides the business value. In his session at 20th Cloud Expo, Ed Featherston, director / senior enterprise architect at Collaborative Consulting, will discuss the key considerations around quality, volume, timeliness, and pedigree that must be dealt with in order to properly fuel that engine. Speaker Bio Ed Featherston is a director/senior enterprise architect at Collaborative Consulting. He brings 37 years of technology experience in designing, building, and implementing large complex solutions. He has significant expertise in systems integration, Internet/intranet, and cloud technologies, Ed has delivered projects in various industries, including financial services, pharmacy, government and retail.


Top 100 @CloudExpo Sponsors #Cloud #IoT #AI #BigData #MachineLearning

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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.


The Business Of HPC Is Evolving

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With most of the year finished and a new one coming up fast, and a slew of new compute and networking technologies ramping for the past year and more on the horizon for a very exciting 2017, now is the natural time to take stock of what has happened in the HPC business and what is expected to happen in the coming years. The theme of the SC16 supercomputing conference this year is that HPC matters, and of course, we have all known this since the first such machines were distinct from enterprise-class electronic computers back in the 1960s. HPC not only matters, but the growing consensus at the conference is that HPC will possibly be returning to its roots as a sector for innovation and specialization to solve very specific and computational intensive and complex problems. We could be seeing the waning of the Era of General Purpose HPC even as the simulation, modeling, analytics, and machine learning workloads that comprise modern HPC continue to evolve at a rapid pace. It takes money to make HPC happen, and HPC also makes money happen, and it is supposed to be a virtuous cycle where more innovation in HPC systems drives more innovation in product design and various kinds of simulation such as weather forecasting or particle physics or cosmology, just to name a few.


IBM and Nvidia team up to create deep learning hardware

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A new software toolkit available today called IBM PowerAI is designed to run on the recently announced IBM server built for artificial intelligence that features Nvidia NVLink technology optimized for IBM's Power Architecture. "PowerAI democratizes deep learning and other advanced analytic technologies by giving enterprise data scientists and research scientists alike an easy to deploy platform to rapidly advance their journey on AI," said Ken King, general manager of OpenPower at IBM, in a statement. IBM PowerAI is optimized for iIBM's highest-performing server in its OpenPower LC lineup, the IBM Power S822LC for High Performance Computing(HPC), which features Nvidia NVLink technology optimized for the Power architecture and Nvidia's graphics chips. Initial client uses for the new IBM Power S822LC for HPC servers include the Human Brain Project, a research project funded by the European Commission to advance understanding of the human brain.


The State of Enterprise Machine Learning

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First, the machine learning outputs – patient risk scores, propensity to buy scores, and fraud predictions – are substantially more valuable to each organization than the raw data. Practical applications include speech recognition, image recognition, or recommendation engines, where the best item to offer can be one of many. Machine learning produces output that can be difficult for humans to interpret compared to statistical techniques; which makes machine learning less useful when the goal of the analysis is attribution or analysis of variance. Before launching his consultancy in 2015, Thomas served as an analytics expert for The Boston Consulting Group; Director of Product Management for Revolution Analytics (Microsoft); Solution Architect for IBM Big Data (Netezza), SAS and PriceWaterhouseCoopers.


AI is from Venus, Machine Learning is from Mars - International Institute for Analytics

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Unlike AI which seeks to understand the world through conceptual models, machine learning has no such interest. The underlying hypothesis of machine learning as applied to log files is that correlation can serve as a proxy for causation. AI emulates human intelligence and is P. Machine learning simulates it and is NP. His first book, Crossing the Chasm, focuses on the challenges start-up companies transitioning from early adopting to mainstream customers.