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The Digitalisation World Video magazine contains the latest Zoom interviews with experts in the industry.
Learn how ITOps teams can apply machine learning and advanced analytics to manage the ever increasing volume of operational data across complex, hybrid environments. AIOps use cases including event noise reduction predictive alerting and probable cause analysis enable ITOps to optimize the performance and health of infrastructure and applications while supporting business innovation.
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Almost 5,000 knowledge workers and business decision makers share their insight on how RPA is changing business operations and employees’ working lives.
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Densify is launching machine learning capabilities that will automatically optimise use of containers. This technology will enable companies to be more efficient, limit wasted cloud spend, improve application uptime and scalability, and reduce performance risk. With Densify, organisations can ensure their containers are being deployed to their full potential.
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Alfresco Software has unveiled the immediate availability of a new Intelligence Services for its cloud-first Digital Business Platform. The Intelligence Services that seamlessly leverages Amazon Web Service uses AI (Artificial Intelligence) and ML (Machine Learning) to provide enterprises with a highly-scalable method for intelligently extracting important content often locked away in multiple documents, scanned images, videos and photographs.
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Organisations will need to overcome challenges to scale the technology.
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Collaboration speeds up critical functions such as image recognition and inferencing at the edge.
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Hear LinkedIn’s senior SRE, Todd Palino, share how the company continually improves the state of its infrastructure, so that the developers who are rolling out applications have a framework that they can do it within, and they can do it safely. LinkedIn currently generates over 50 terabytes a day of unique metrics on applications. No human is going to look at 50 terabytes a day of data and get anything useful out of it, so LinkedIn relies on systems give them some useful signal out of all that noise. By moving down the road of machine learning, LinkedIn can now do anomaly detection using machine learning models.
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