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SaaS-Ready platform is the force multiplier for overwhelmed and understaffed IT and Security operations Ayehu today launched its next generation automation and orchestration platform for IT and Security operations. The new platform is Software-as-a-Service (SaaS)-ready for hybrid deployments and is powered by artificial intelligence (AI) and machine learning driven decision support, for fully enhanced and optimized automated workflows. Today’s IT and Security operations teams are overwhelmed by the increasing influx of alerts, incidents, and requests. This state of affairs combined with a growing shortage of skilled, talented IT and security professionals, has created the need for intelligence-backed, automated solutions.
“We’ve received overwhelmingly positive initial feedback from our partners and customers who have previewed our new platform and are excited to now make it generally available,” said Gabby Nizri, Co-founder & CEO of Ayehu. “We developed it because we wanted to make it even easier for our customers to incorporate and use automation as a game changer in their business.  The SaaS-ready, multi-tenant platform is now able to deliver efficiencies across hybrid environments. This sets the stage for CIOs around the world to start the journey to enable the Self Driving Enterprise.”
The platform includes an architecture redesign to support managed service providers (MSP) and businesses with hybrid deployments across on-premise, private and public cloud environments such as AWS and Azure. It also enriches product security in areas such as message encryption across internal and external networks and presents a brand new user interface. Key features include:
  • AI Powered – Machine learning delivers decision support via prompts to optimize workflows and dynamically creates rule-based recommendations, insights, and correlations
  • SaaS Ready – Ideal for hybrid deployments, supports multi-tenant, communication encryption, OAuth2 authentication, and internal security improvements
  • High Availability and Scalability – Ayehu easily scales to support organizations with a high volume of incidents and safe guards against a single-point-of-failure
  • Workflow Version Control – Ayehu is the first IT automation and orchestration platform to provide version control on workflows, allowing users to rollback changes and review, compare or revert workflows
  • Tagging and Labeling – Ayehu users can associate workflows with keywords through tags to quickly search and return commonly used workflows
  • User Interface Enhancements – The new angular 2.0 web-based interface, offering easy and user-friendly workflow designer and template navigation, as well as white labeling options for OEM partnerships
Ayehu acts as a force multiplier, driving efficiency through a simple and powerful IT automation and orchestration platform powered by AI. The next generation automation platform helps enterprises save time on manual and repetitive tasks, accelerate mean time to resolution (MTTR), and maintain greater control over IT infrastructure. IT and security operations teams can fully- or semi-automate the manual response of an experienced IT or security operator/analyst, including complex tasks across multiple, disparate systems. Ayehu’s response time is instant and automatic, executing pre-configured instructions without any programming required, helping to resolve virtually any alert, incident or crisis. For more information and to request a live, personalized demonstration of the next generation platform, visithttps://ayehu.com/nextgen

About Ayehu

Named by Gartner as a Cool Vendor, Ayehu’s Intelligent IT automation and orchestration platform is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe. For more information, please visitwww.ayehu.com and the company blog.  Follow Ayehu on Twitter and LinkedIn.

 Source: https://ayehu.com/ayehu-launches-next-generation-automation-orchestration-platform-powered-artificial-intelligence/

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Post written by Gabby Nizri, Co-Founder and CEO at Ayehu Inc.

Since the industrial revolution, business leaders have been leveraging technology to augment human workers with the goal of maximizing efficiency and productivity while simultaneously cutting costs. Now, thanks to the recent tidal wave of intelligent technology advancement, we have suddenly found ourselves staring down the barrel of a workplace that looks quite different than the one we have become used to.
What do automation, machine learning and artificial intelligence (AI) mean for tomorrow’s workforce? Will AI eliminate the need for human workers altogether? The reality isn’t quite so cut and dry. In fact, the future of work will likely be a hybrid that involves both human and machine intelligence working in conjunction toward the same shared goals. Let’s explore this in a little more detail. Redefining The Way We Work The basic concept behind automation hasn’t changed all that much over the past century or so. When menial tasks can be shifted from human employees to robots, work can be completed faster and without the risk of human error. This dramatically improves efficiency levels, which means a better bottom line for an organization as a whole. And because the output of quality of work increases, service levels also receive a boost, so in theory, everybody wins. However, automation powered by artificial intelligence has taken this basic concept and brought it to an entirely new level. Now, it’s not just about programming a machine to perform simple tasks; rather, it’s about relying on technology that is intuitive enough to adapt and improve without the need for human input. Take chatbots, for example. This technology is capable of using the data gathered over time from incoming customer inquiries to continuously develop a robust catalog of answers. In other words, the more it’s used, the smarter it becomes. A New Realm Of Possibilities Automation will inevitably lead to redundancy in certain roles. It’s only logical to assume that if software robots are capable of performing the majority of a lower-skilled employee’s tasks, it’s a much more economical business decision to shift those duties to technology, subsequently making certain roles obsolete. This doesn’t necessarily mean, however, that we’re doomed to a future of humanless offices. The truth is that while automation may eliminate some jobs, it also creates new roles and opportunities for human workers to pursue. It’s also important to point out that as far as intelligent automation has come, there are still certain areas where the human touch cannot be replaced or replicated. For instance, a chatbot can be programmed to perform basic customer support, but it is not capable of managing complex situations. Likewise, intelligent automation can be highly effective in identifying ideal candidates for a job opening, but the actual hiring process is still a human-centric function.
Humans And Machines: A Match Made In Heaven Ideally, the best way to approach the adoption of artificial intelligence in the workplace is to view it from a more holistic perspective. Rather than machines and humans working independently, the two should be working in tandem toward the greater good of an organization. For example, process automation can be leveraged to handle the majority of the mundane, repetitive IT tasks while seamlessly transferring more complex issues to human workers. AI can also be highly effective in helping business leaders make smarter, more data-driven decisions. Machines handle the data mining process, identifying, extracting and organizing the most relevant information available. Executives can then use this information to more accurately project and plan for the future. This facilitates greater innovation, which means those enterprises who adopt AI will lead the charge in their respective fields.
A New Definition Of Work
As artificial intelligence continues to evolve and improve, the very definition of what we consider to be mundane or routine will also continue to change. With smarter technology, more and more tasks will be shifted to machines. In fact, according to a recent report from Gartner, smart machines and robots could take over the tasks performed by highly trained professionals in such fields as IT, medicine and law by 2022. But that doesn’t necessarily mean certain unemployment for those individuals working on the front lines. To the contrary, according to one study conducted by ServiceNow, 79% of executives surveyed say they expect an increase in the adoption of automation to lead to the creation of new jobs. Furthermore, an incredible 94% agreed that when repetitive tasks are automated, the demand for jobs that call for soft skills like communication, collaboration and creative problem-solving will grow. Ultimately, it’s the way human workers approach this technology that will determine what tomorrow will bring. For those who choose to embrace artificial intelligence and all of the opportunities it presents, the future certainly looks bright.
Source: https://www.forbes.com/sites/forbestechcouncil/2017/08/17/shaping-the-future-of-work-a-collaboration-of-humans-and-ai/#5e0798e547b7
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SAN JOSE, CA (PRWEB) AUGUST 16, 2017: Intelli-Vision, a pioneer and leader in AI/Deep Learning video analytics software for Smart Cameras, today announced that the latest version of its license plate recognition (ANPR) and detection software, which uses a combination of AI, CNN (convolutional neural network) and Deep Learning, has achieved accuracy numbers as high as 99% in real-world customer environments. More information can be found here “We have been continuously improving our LPR/ANPR technology for a number of years, as part of our AI and deep learning-based video analytics software,” said Vaidhi Nathan, IntelliVision’s CEO. “We are now achieving accuracy of up to 99% in countries as diverse as the U.S., Mexico, Germany and India and not just in the lab.” IntelliVision’s License Plate Recognizer (LPR/ANPR) has performed and matured over many years of application, taking into account variables such as movement and high speeds which are natural to the environment of vehicle monitoring. Using still images or video feeds, the product can recognize and capture information located on license plates and automatically log this information for future inspection. Real-time searching can also be performed on each plate detected, comparing the information gathered with a stored database of license plates. IntelliVision’s License Plate Recognizer is part of a portfolio of products for Smart City, Smart Auto and Intelligent Transportation Systems (ITS). IntelliVision products are in over 3 million cameras worldwide, including 15,000 cameras at 3,000 intersections in the United States, taking the place of under-street induction loops.

About IntelliVision  IntelliVision is a market leader in AI and Deep Learning video analytics software for Smart Cameras, providing video analytics solutions for several markets including Smart Home/IoT, Smart Security, Smart Retail, Smart Business, Smart City, big data analytics and video search. IntelliVision technology has been recognized as the Brains Behind the Eyes™ for many applications deploying and using cameras to analyze video content, extract metadata, send out real-time alerts and provide intelligence to other home, business and security systems. IntelliVision provides the largest suite of video analytic products in the market today. Its products are used by Fortune 500 companies, the US Government and many leading brands. IntelliVision is headquartered in San Jose, California with offices in Asia and Europe.

For more information, visit: http://www.intelli-vision.com Email: info(at)intelli-vision(dot)com Phone: 408-754-1690


Source: http://www.prweb.com/releases/2017/08/prweb14606123.htm

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Anik Bose (BGV General Partner) and Niranjan Venkatesan (BGV intern and Kellogg MBA student) share their perspective on innovation and value creation in computer vision. Computer vision is defined as tasks that include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions. In layman’s terms, computer vision is an arm of artificial intelligence (A.I.) that focuses on enabling machines to “understand” images by processing and analyzing them on a pixel-by-pixel basis, rather than relying on human-controlled categorization data, such as keywords and descriptions. Getting computers to recognize objects just like human beings do remains elusive; 100% accuracy and reliability is almost impossible. As a reference point, the human eye delivers 91% recognition. New technologies such as deep learning are evolving that promise to increase accuracy and reliability dramatically, but these technologies need more research before they can become mainstream. These technologies are modeled on a neural network and will allow the conversion of an image to text or speech. Deep learning will also enable the conversion of text or speech to image or video and the two together can enable tagging, searching, and indexing of a video or image just like text. Some of these new software technologies can deliver a recognition accuracy of 95%. Intellivision, a BGV portfolio company, is able to deliver 98% accuracy for specific vertical applications. Early M&A activity in the computer vision space by larger companies is a lead indicator of the large market potential. The most prominent acquisition being Intel’s recent $15bn acquisition of Mobile eye. Adoption Challenges While the computer vision market forecasts are significant, we believe there are several adoption challenges that must be addressed for the market opportunity to be realized. Key adoption factors include image data privacy concerns, lack of data accuracy, quality and ubiquity, automotive regulations, evolving industry standards and dependence on analytic platforms and applications. These factors, along with operational challenges such as costs, increases in video/image data driven by higher security needs, inability to maintain and fit legacy systems to the new requirements and the difficulties associated with scaling pilots in addition to high bandwidth requirements for hardware, are all rate limiting factors influencing the timing and size of the actual market opportunity. The Venture Investment Opportunity We believe that the computer vision technology stack can be broken down into three layers: a) hardware – This includes cameras, sensors, chipsets and video cards; b) solution frameworks – This includes image-processing algorithms, analytics/deep learning algorithms; c) application – This includes facial recognition, AR/VR and 3D imaging applications. This stack must be applied to proprietary data needed to train the algorithms required to solve specific customer problems. Access to such data will be the long-term differentiator for the winning companies, sometimes more important than the technology stack itself. We believe that there are six specific areas where innovative startups can play a strong role in value creation. These are:
  • Robotics Vision – Driven by demands for the following: safety, quality, reliability, and ease of use, cost efficiencies, benefits of 3D over 2D technology, rapid deployment, and penetration of smart camera in retrofit robotic systems. Key early adopter industries will be automotive and food processing. 6dbytes is an innovative robotics software orchestration company that is targeting the food-processing industry.
  • Visual inspection/Machine Vision – Manufacturers prefer machine vision for visual inspections for their high speed and repeatability of measurements. This accuracy, along with the ability to safely and reliably identify flows and defects in products without disrupting or delaying processes, will create strong demand for computer vision. Key early adopter segments are likely to be the electronics and automotive industries. Drishti is another innovative startup that aims to revolutionize the manufacturing assembly line by digitizing human actions based on technology that can enable non-intrusive and real time observation.
  • Augmented Reality – Applications such as improved logistics in a warehouse, remote monitoring, trouble-shooting and hands free access to contextual information are expected to drive the adoption of AR. Retail and transportation are expected to be early adopter segments. Augment is a startup seeking to transform the retail shopping experience with AR. They are one of the first companies targeting the enterprise B2B space with an end- to-end AR platform.
  • Video Analytics – Intelligent video surveillance to respond to rising threats along with increased demand for business intelligence and adoption of cloud and analytics are also creating the need for computer vision technology. Early adopter markets are likely to be public safety and defense. Intellivision is an innovative BGV portfolio company that provides intelligent video analytics and smart camera solutions for retail, smart home and IOT markets.
  • 3D Imaging – The automotive and construction sectors are progressively adopting 3D imaging solutions for designing, previewing and rectifying the final version of the end products. Fast-paced adoption is expected in healthcare as well for surgical applications and diagnosis.
  • Image/Facial Recognition – Applications will increasingly value code recognition, digital image processing, object recognition, pattern recognition and optical character recognition.   Media and entertainment is expected to be a lead early adopter segment. Finally, facial recognition will be driven by applications such as law enforcement, surveillance, mobile device authentication as well as targeted advertising in retail.
In conclusion, we believe that the analysis of content via computer vision and artificial intelligence is no longer a concept being discussed only in academia. It is an area where we expect to see significant startup innovations that will empower and disrupt existing industries over the next ten years.
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