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How to Achieve #DigitalTransformation @ExpoDX @DellEMC #AI #IoT #IIoT #FinTech #SmartCities

#artificialintelligence

Industry after industry is under siege as companies embrace digital transformation (DX) to disrupt existing business models and disintermediate their competitor's customer relationships. But what do we mean by "Digital Transformation"? Digital Transformation The coupling of granular, real-time data (e.g., smartphones, connected devices, smart appliances, wearables, mobile commerce, video surveillance) with modern technologies (e.g., cloud native apps, Big Data architectures, hyper-converged technologies, artificial intelligence, blockchain) to enhance products, processes, and business-decision making with customer, product and operational insights. The digital transformation starts by understanding the organization's business initiatives, and then prioritizing which initiatives are top candidates for enhancement through digital transformation. "Begin with an end in mind" to quote Stephen Covey.


A 20-Year Community Roadmap for Artificial Intelligence Research in the US

arXiv.org Artificial Intelligence

Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.


Sidewalk Labs spins out Replica to help city planners create 'virtual populations' with big data

#artificialintelligence

Google sibling Sidewalk Labs has confirmed the latest project spinout from its incubator. Replica, originally known as Model Lab, is touted as a "next-generation urban planning tool" and began life as a Sidewalk Labs project in April, 2018. In truth, Replica Inc. has actually been an independent entity since March, and a June corporate filing describing its business somewhat enigmatically as "quality fish reproductions" was spotted by Redtail a few months back. Now it seems Replica is willing to go on the record about its new life as a standalone company and has also revealed a fresh tranche of funding. But first -- what exactly does Replica do?


The Easy Way Big Data Can Be Accessed with Data-as-a-Service

@machinelearnbot

Primed to make a huge entrance in 2015, Data-as-a-Service (DaaS) empowers companies with real-time data to overcome tough challenges with data. DaaS is allowing companies to generate real-time insights and revenue from Big Data. Companies commonly report feeling overwhelmed solely by the mere size of big data, not to mention the processes necessary to use the data. This no longer has to be a reality. With DaaS using big data is no longer a couple month long process.