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How telecom providers are embracing cognitive app development

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As an example, mobile network operators are increasing their investment in big data analytics and machine learning technologies as they transform into digital application developers and cognitive service providers. With a long history of handling huge datasets, and with their path now led by the IT ecosystem, mobile operators will devote more than $50 billion to big data analytics and machine learning technologies through 2021, according to the latest global market study by ABI Research. Machine learning can deliver benefits across telecom provider operations with financially-oriented applications - including fraud mitigation and revenue assurance - which currently make the most compelling use cases. Predictive machine learning applications for network performance optimization and real-time management will introduce more automation and efficient resource utilization.


Microsoft's AI and Speech Breakthroughs Eclipsed by New IBM Watson Platform -- Redmondmag.com

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The milestone was enabled with the new Microsoft Cognitive Toolkit, the software that enables those speech recognition advances (as well as image recognition and search relevance). In addition to helping the researchers hit the 5.9 WER, the new Microsoft Cognitive Toolkit 2.0 helped the researchers enable what the company is calling "reinforcement learning." The company released the new Watson Data Platform (WDP), a cloud-based analytics development platform that allows programming teams including data scientists and engineers to build, iterate and deploy machine-learning applications. WDP runs on IBM's Bluemix cloud platform, integrates with Apache Spark, works with the IBM Watson Analytics service and will underpin the new IBM Data Science Experience (DSX), which is a "cloud-based, self-service social workspace that enables data scientists to consolidate their use of and collaborate across multiple open source tools such as Python, R and Spark," said IBM Big Data Evangelist James Kobielus in a blog post outlining last month's announcements at the company's World of Watson conference in Las Vegas.


Top Ten Intel Software Developer Stories October

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Machine learning is changing the balance of labor between the decision-making role of humans, and the number-crunching roles of computers. The High Performance Computing (HPC) Center Lunch and Learn seminars are opportunities for students and professional developers to meet with HPC industry experts. Take the difficulty out of managing IoT development by using IoT cloud services from Microsoft Azure* with Intel IoT Technology. Intel Developer Zone experts, Intel Software Innovators, and Intel Black Belt Software Developers contribute hundreds of helpful articles and blog posts every month.


The AI disruption wave

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Machine learning (ML) has achieved remarkable breakthroughs, which have, in turn, driven performance improvements across AI components. However, it is still early days, and there are still several challenges: Most breakthroughs are in "narrow" applications and use supervised methods that require big labeled data sets (which are often expensive to create), most algorithms (still) achieve (just) sub-human performance, training requires considerable computing resources and most approaches are based on heuristics with lack of theoretical frameworks. New image recognition techniques powered by deep learning have enabled startups like Netra to improve visual intelligence and search, enhancing overall user experience. Talla is aiming to revolutionize enterprise knowledge management, starting with a seemingly simple conversational agent that will eventually become a full-fledged proactive knowledge agent.Wade & Wendy has created a two-sided conversational agent for recruiting that aims to reduce the overall recruiting time while improving the level of satisfaction on both sides of the table.


Hewlett Packard Enterprise Powers Machine Learning Apps, Revs Vertica Database

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Haven OnDemand runs on Microsoft Azure, but it's REST-based APIs can be invoked in any services-enabled environment, including Amazon Web Services or hybrid and private clouds. The availability of machine learning services on Amazon, Azure, Google and IBM clouds is clearly a threat to Haven OnDemand. On the in-database front, Vertica 8.0 gains R-based machine learning algorithms that will enable data scientists to model against vast data sets relying on the power of Vertica's massively parallel processing (and thus avoiding moving data to analytic servers or relying on sampling techniques). Vertica was already certified to run on Amazon Web Services, but the 8.0 release adds support for deployment on Microsoft Azure.


Using Artificial Intelligence to Set Information Free

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Just as a social graph represents the interconnection of relationships in an online social network, the knowledge graph will represent the interconnection of all the data and communications within your company. Whenever someone in a meeting volunteers to tackle an action item, AI software will record and track those commitments, and automatically connect the ultimate completion of that item back to the original meeting from whence it sprang. In the absence of data, internal politics and unconscious bias can play a major role, resulting in performance management that is biased and inaccurate. This article was originally published on June 14, 2016, with the title, "Using Artificial Intelligence to Humanize Management and Set Information Free."