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Understanding artificial intelligence and machine learning in digital business

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The problem of learning and decision-making is at the core of human and artificial thought, which is why scientists introduced machine learning (ML) into artificial intelligence (AI). AI is a platform or solution that appears to be intelligent and can often exceed the performance of humans. It is a broad description of any device that mimics human or intellectual functions, such as mechanical movement, reasoning or problem solving. ML is a widely used AI concept that teaches machines to detect different patterns and adapt to new circumstances and can be both experience- and explanation-based. For instance, in robotics, ML plays a vital role by optimizing machine-based decision-making, which eventually increases a machine's efficiency by enabling a more organized way of performing a particular task.


IBM Introduces New Software to Ease Adoption of AI, Machine Learning and Deep Learning - insideBIGDATA

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IBM announced new software to deliver faster time to insight for high performance data analytics (HPDA) workloads, such as Spark, Tensor Flow and Caffé, for AI, Machine Learning and Deep Learning. Based on the same software, which will be deployed for the Department of Energy's CORAL Supercomputer Project at both Oak Ridge and Lawrence Livermore, IBM will enable new solutions for any enterprise running HPDA workloads. New to this launch is Deep Learning Impact (DLI), a set of software tools to help users develop AI models with the leading open source deep learning frameworks, like TensorFlow and Caffe. The DLI tools are complementary to the PowerAI deep learning enterprise software distribution already available from IBM. Also new is web access and simplified user interfaces for IBM Spectrum LSF Suites, combining a powerful workload management platform with the flexibility of remote access.


AI and the enterprise: The view from Noodle.ai

ZDNet

Noodle.ai was founded in March 2016 by Stephen Pratt, who has an impressive track record in the tech industry: before launching the San Francisco-based AI startup he oversaw all worldwide Watson implementations for IBM Global Business Services; prior to that he was the founder and CEO of Infosys Consulting, a senior partner at Deloitte Consulting, and a technology and strategy consultant at Booz, Allen & Hamilton. Noodle.ai is firmly focused on the enterprise, and its mission is to bring business executives, process experts and AI technologies together to address complex business challenges and deliver enhanced outcomes. ZDNet talked to Stephen Pratt to learn more. ZDNet: How did your career path lead you to forming Noodle.ai? Stephen Pratt: I have a background in satellite communication and digital signal processing, and started my career doing spooky stuff for the government. Later I was a partner at Deloitte and did the first ever project using teams in India and the US combined, and it worked so well I thought it was the future of technology implementations.


Lenovo says AI crucial for enterprise as it announces new tech for training machine-learning systems

ZDNet

Lenovo has announced new hardware and software for firms building machine-learning systems, as the Chinese tech giant double down on AI. Lenovo expects firms will increasingly rely on AI systems to make rapid decisions based on the vast amount of data being generated, predicting will be 44 trillion gigabytes of data will exist by 2020. To serve the fast-growing market, Lenovo today announced new hardware and software for streamlining machine-learning on high-performance computer systems. The ThinkSystem SD530, a two-socket server in a 0.5U rack form factor, is now available with the latest NVIDIA GPU accelerators and Intel Xeon Scalable family CPUs. By including the option of adding NVIDIA's Tesla V100 GPU accelerator, Lenovo is giving businesses the ability to massively boost the performance of AI-related tasks.


HPE launches upgraded high-performance systems for AI applications

ZDNet

Hewlett Packard Enterprise (HPE) has announced the launch of upgraded high-density compute and storage systems to encourage adoption of high-performance computing (HPC) and artificial intelligence (AI) among enterprises. The HPE Apollo 2000 Gen10 is a multi-server platform for enterprises looking to support HPC and deep learning applications but have limited datacentre space. The platform supports Nvidia Tesla V100 GPU accelerators to enable deep learning training and inference for use cases such as real-time video analytics for public safety. Enterprises deploying the HPE Apollo 2000 Gen10 system can start small with a single 2U shared infrastructure and scale out up to 80 HPE ProLiant Gen10 servers in a 42U rack. "HPC and AI play an increasingly important role in digital transformation, enabling organisations to leverage modeling, simulation, and deep learning to drive business innovation in areas like financial trading, computer-aided design and engineering, video surveillance, and text analytics," HPE said in an announcement.


Why Intel is suddenly bullish on Artificial Intelligence - ET Telecom

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NEW YORK: There is no denying the fact that Artificial Intelligence (AI) is one phenomenon that has stood out among other emerging technologies. Sensing great possibilities, global chip giant Intel has now joined the AI bandwagon in a big way. AI is not new to the world of technology but the past five years have given AI believers a reason to cheer as its uses are increasing across industries - from health care to autonomous vehicles -- say AI experts at Intel. "AI capabilities are greatly supplementing humans to do great work in less time in sectors like healthcare, banking and finance, transport, energy and robotics, etc. It will be interesting to see how this whole AI thing evolves with time," Bob Rogers, Data Scientist, AI and Analytics, Data Center Group at Intel, told.


Artificial Intelligence is big on Intel's agenda: Here's why

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There is no denying the fact that Artificial Intelligence (AI) is one phenomenon that has stood out among other emerging technologies. Sensing great possibilities, global chip giant Intel has now joined the AI bandwagon in a big way. AI is not new to the world of technology but the past five years have given AI believers a reason to cheer as its uses are increasing across industries – from health care to autonomous vehicles – say AI experts at Intel. "AI capabilities are greatly supplementing humans to do great work in less time in sectors like healthcare, banking and finance, transport, energy and robotics, etc. It will be interesting to see how this whole AI thing evolves with time," Bob Rogers, Data Scientist, AI and Analytics, Data Center Group at Intel, told IANS here.


[session] Continuous Deep Learning for Visual Systems @CloudExpo @CalSci #AI #ML #DL #Cloud

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In his session at 21st Cloud Expo, James Henry, Co-CEO/CTO of Calgary Scientific Inc., will introduce you to the challenges, solutions and benefits of training AI systems to solve visual problems with an emphasis on improving AIs with continuous training in the field. He will explore applications in several industries and discuss technologies that allow the deployment of advanced visualization solutions to the cloud. Speaker Bio James Henry is Co-CEO/CTO of Calgary Scientific Inc., a company specializing in bringing real time interactive software to cloud and mobile platforms. He has 25 years of experience leading software teams in many industries including the oil and gas, healthcare, telecommunication, geolocation, construction and simulation industries. His current interest is in enabling people, data and AIs to interact in real time to solve complex problems.


[session] Machine Learning Intro for Anyone and Everyone @CloudExpo @BigDataTrunk #ML #AI #Cloud

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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.


An Industry of Innovation

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No longer is the technology stack enabling information sharing, the technology stack is now creating the information. Most of these scientific advancements leverage scientific computing methods in what is referred to as HPC or High Performance Computing. And in order to ensure that scaling is an option for the long term, CIOs are choosing to buy specialized hardware applied in specialized data centers or simply bypassing the data center all together and purchasing AI services via a cloud model. We believe that the future in high intensity computing for AI and HPC will be with on-demand services that are run in data centers designed and operated similarly to the same industrial data center factories that power today's most advanced Blockchain computing.