Machine Learning

BlueData Introduces New Innovations for AI and Machine Learning in Hybrid or Multi-Cloud Deployments

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BlueData, provider of the leading Big-Data-as-a-Service (BDaaS) software platform, today announced the new summer release for BlueData EPIC. This release builds upon BlueData's innovations in running large-scale distributed analytics and machine learning (ML) workloads on Docker containers, with new functionality to deliver even greater agility and cost savings for enterprise Big Data and AI initiatives. 

Last spring, BlueData introduced support for hybrid cloud environments - leveraging the inherent infrastructure portability and flexibility of Docker containers. This past fall, BlueData delivered a major new release that added deep learning (DL), GPU acceleration, and multi-cloud support to the container-based BlueData EPIC platform. And last month, BlueData announced a new turnkey solution to accelerate AI and ML / DL deployments in the enterprise.

 

Protecting Your Organization's Cloud

As organizations move to the cloud, the next evolution of Network Access Control takes shape to meet business demands.
 

What are the chances that your organization has moved some of its data, systems, programs and applications to the cloud? Quite high. According to a Synergy Research survey of IT professionals, spending on private cloud and cloud-enabled solutions grew by 16% between the second quarters of 2015 to 2017. During that same period, traditional, non-cloud data center hardware and software dropped 18%. It is easy to understand why these days, cyber security threats are coming in through many new channels and vulnerabilities that are not part of the traditional IT infrastructure such as, mobile devices and cloud-based applications. The following prevalent trends in the enterprise highlight why it is essential to monitor your network with a Cloud Network Access Control (Cloud-Based NAC). 

Company Networks Go Global

Organizations are becoming perimeter-less. Traditional IT perimeters have been torn down by the adoption of BYOD, IoT devices, telecommuting and cloud computing. Therefore, one can no longer look at the network as a defined infrastructure within a physical firewall. The network is essentially global without boundaries. According to a Gallop News Service poll from 2015, 37% of U.S. workers had telecommuted for work, and this was up by 30% from the last decade but four times greater than the 9% found in 1995. Perimeter-less companies require continuous risk-monitoring and risk-assessment that can match the ever increasing mobile and cloud-based reality and this can be performed best via the cloud. 

Tens of Thousands of Customers Flocking to AWS for Machine Learning Services

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Today, Amazon Web Services, Inc. (AWS) shared that tens of thousands of customers are using AWS machine learning services, with active users increasing more than 250 percent in the last year, spurred by the broad adoption of Amazon SageMaker since AWS re: Invent 2017. Amazon SageMaker is a fully managed service that removes the heavy lifting, complexity, and guesswork from each step of the machine learning process, empowering everyday developers and scientists to use machine learning much more expansively and successfully. AWS has meaningfully more reference customers for machine learning than any other provider, and much of it has to do with AWS's unmatched array of services that enable a full stack machine learning experience. With AWS machine learning services, customers are building a wide variety of intelligent applications and solutions with the help of AWS's P2 and P3 graphical processing unit (GPU) instances, deep learning Amazon Machine Images (AMIs) that embed all the major frameworks, Amazon SageMaker, AWS DeepLens-a device that has helped thousands of customers gain hands on experience with machine learning, and services at the top layer of the stack such as Amazon Rekognition, Amazon Polly, Amazon Lex, and Amazon Comprehend.

Today, AWS also announced the general availability of two new machine learning services, which are part of AWS's machine learning portfolio, Amazon Transcribe and Amazon Translate. Amazon Transcribe provides grammatically correct transcriptions of audio files to allow audio data to be analyzed, indexed, and searched. Amazon Translate is a deep learning powered machine translation service that provides natural sounding language translation in both real-time and batch scenarios. These services further extend the language capabilities already provided on AWS with Amazon Lex for conversational interfaces, Amazon Polly for Text-to-Speech, and Amazon Comprehend for processing natural language to discover insights and contextual relationships in text.

OpenStack 'Queens' Release Expands Support for GPUs and Containers to Meet Edge, NFV and Machine Learning Workload Demands

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The OpenStack community today released Queens, the 17th version of the most widely deployed open source cloud infrastructure software. A packed release resulting from a six-month development cycle, Queens offers advancements benefiting not only enterprises with mission-critical workloads but also organizations investing in emerging use cases like containers, NFV, edge computing and machine learning. The software now powers 60 public cloud data centers and thousands of private clouds at a scale of more than six million physical cores.  

Enterprise adoption of cloud continues to expand, and by next year, 60 percent of enterprise workloads will run in the cloud, according to 451 Research's Voice of the Enterprise: Cloud Transformation, Workloads and Key Projects survey. 451 Research also reports that enterprise adoption of OpenStack is expanding in parallel, with enterprises in nearly all verticals and regions now running mission-critical workloads on OpenStack software. To support these workloads, the Queens release includes robust, enterprise-oriented features, most notably the multi-attach feature in Cinder.  

National Football League Selects AWS as Official Cloud and Machine Learning Provider for Next Gen Stats

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Today, Amazon Web Services, Inc. (AWS), announced that the National Football League (NFL) has selected AWS's machine learning and data analytics services to boost the accuracy, speed, and insights provided by its Next Gen Stats platform, the NFL's player-tracking system. In choosing AWS to power Next Gen Stats, the NFL aims to develop new ways of visualizing the action on the field, uncovering deeper insights into the action on the field, and expanding the fan experience by offering a broader range of advanced statistics. In addition, AWS will become an Official Technology Provider of the NFL.

Through the use of radio-frequency identification (RFID) tags in player equipment and the football, Next Gen Stats captures a variety of real-time location, speed, and acceleration data. The data is analyzed on AWS and used to contextualize movement on the field for fans to see on NFL Media properties, game broadcasts, third-party digital platforms, and in-venue displays. The data is also leveraged by NFL clubs post game as part of their football operations on a weekly basis. The system creates a variety of unique player and team stats for every game such as a receiver's ability to get open and an offensive line's ability to protect the quarterback. By leveraging AWS's broad range of cloud-based machine learning capabilities, the NFL is looking to take its game-day stats to the next level so that fans and NFL Clubs can benefit from deeper insights.

ZeroStack Showcases Machine Learning-Driven Cloud at Cloud Expo Asia

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ZeroStack, Inc., creators of the self-driving on-premises cloud, today announced that it will be demonstrating its Intelligent Cloud Platform at Cloud Expo Asia. Supported by Value Added Distributor, M5 Technologies and Alliance Partner Netweb, ZeroStack is participating at this major technology event in support of its regional channel program. ZeroStack will also be participating in Structure Research's VIP Event as part of the Expo. ZeroStack's ease of deployment, security features, SaaS portal, and self-healing capabilities were all cited as standouts against competitive offerings in a recent Frost & Sullivan report, and the company is seeing strong traction in South Asia through its partner ecosystem in Singapore.

FireEye Expands Cybersecurity Threat Detection with Major New Releases

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FireEye, Inc., the intelligence-led security company, today announced major new software releases and next-generation hardware, adding new and expanded capabilities to extend FireEye's cybersecurity threat detection while reducing costs and increasing flexibility.

To address the issue of post-breach attacks and insider threats, FireEye unveiled FireEye Network SmartVision - a new capability that leverages a machine-learning framework to detect suspicious lateral threat movements (East-West traffic) and data exfiltration. This capability is designed to provide customers with greater detection and expanded visibility across their perimeter and now network core and servers.

FireEye Network (NX) deployments can now burst network traffic to FireEye's MVX Smart Grid during periods of high-content scanning activity, to address overload and gaps in protection that might otherwise occur. Other new software capabilities include significant updates to alert handling, event change visualization, expanded logging, and overall usability improvements.

These new software releases complement the launch of fifth-generation FireEye hardware, expanding customer capability to address increasingly sophisticated threats, while reducing costs and increasing deployment flexibility. FireEye also introduced FireEye File Content Security (FX), a new virtual offering that extends FireEye protection further into hybrid IT environments.

Box Brings Intelligence to Cloud Content Management

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Box, Inc., a leader in cloud content management, today announced that it is bringing advanced image recognition capabilities to enterprise content through an integration with Google Cloud Vision. Available today in private beta, the integration represents one of Box's first use cases of advanced machine learning to help enterprises improve workflows and drive efficiencies through more accurate discovery and deeper insights into unstructured content stored in Box.

"Organizations today have no way to extract insights from the massive amounts of unstructured data that are essential to their business, missing a huge opportunity to drive innovation, efficiency, and cost savings," said Aaron Levie, cofounder and CEO, Box. "By combining the machine learning capabilities of Google Cloud with the critical data businesses manage and secure in Box, we are enabling our customers - for the first time - to unlock tremendous new value from their content, digitize manual workflows, and accelerate business processes."

LiveAction Advances Network Visibility at the Edge and the Cloud with Latest Release of LiveNX Platform

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LiveAction, a provider of IT network performance management, visualization and analytics software, today announced the latest release of the LiveNX platform. The newest features further boost the performance of SD-WANs, offer increased viewability into the network endpoints of all types, and include machine learning and automation, among other enhancements. LiveNX enables network engineers and IT operations to increase productivity and improve online user experiences by making it easier to monitor, manage, and troubleshoot network performance issues.

The LiveNX platform maximizes a company's investments in IT network management by ensuring users consistently have optimal online experiences without interruptions or delays. LiveNX performs network diagnostics, monitors service delivery to ensure service level agreements (SLA) are met, automates device discovery to make it easier for users to access the network, and issues proactive alerts to potential problems. It visualizes the entire network and presents a comprehensive view of performance through a dynamic dashboard. LiveNX also integrates with the Cisco Digital Network Architecture (DNA) as well as other multi-vendor environments.

IBM Revamps Computer Network Unit Around Watson Artificial Intelligence

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International Business Machines Corp. is revamping its Global Technology Services division, which helps customers run their computer networks, to rely more heavily on artificial intelligence. The new AI-capability will help IBM's customers minimize disruptions such as server outages or switching malfunctions by predicting problems before they occur and automatically taking corrective action, such as brokering additional cloud capacity or rerouting network traffic around bottlenecks, Bart van den Daele, general manager of IBM Global Technology Services in Europe, said in an interview.

The product offering, powered by IBM's Watson cognitive computing platform, will enable the company to maintain its market share in IT network infrastructure management, Van Daele said. New York-based IBM has been struggling to pivot from reliance on older products like computers and operating system software and into higher-growth areas like AI and the cloud...