Results


AI will fundamentally change how we manage content

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Perhaps it's not a coincidence that just this month, Box announced a partnership with Google to bring AI via image recognition technology to the cloud content management firm. Last week, M-Files, a hybrid content management solution, announced it was acquiring Apprento, a Canadian startup that uses natural language processing (NLP) and natural language understanding (NLU) to provide semantically based intelligent summaries. "In Apprento's case, we were first attracted to their practical experience with applying natural language processing (NLP) and natural language understanding (NLU) to practical business needs. All of these moves suggest that we could be in the midst of an industry shift that Levie and Patel alluded to, as content management firms try to use intelligence to make sense of the increasingly large amount of content moving into the enterprise.


Artificial Intelligence and the Role of Workers

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Already, robotic process automation (rules-based software) is rapidly advancing from handling traditional applications for repetitive tasks to handling continuously changing tasks. And, in fact, AI will gradually replace humans in some functions like customer service, personal assistants and document processing. Indeed, they're even thinner on the ground than they were in 2008 when, answering a similar question, CEOs indicated people with technological skills are more plentiful today than ever before. But one thing's clear: business leaders in all industries and functions must move rapidly to drive value from AI.


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Steve recognises the "disruptive and pervasive" impact AI is already having on business: "AI is enabling companies to achieve improved operational efficiency, develop new and improved products and services, and most significantly entirely new business models. Universities are particularly well suited for interdisciplinary approaches that include multiple technical disciplines as well as the liberal arts, humanities, arts, and social sciences. "Data sharing agreements with appropriate protections for sensitive confidential information enable university data science researchers to develop practical algorithms using real-world data. Municipal, state, and national governments are working to improve accessibility and the democratization of data.


Tractica Launches Artificial Intelligence Advisory Service

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BOULDER, Colo.--(BUSINESS WIRE)--Today Tractica announced the launch of its new Artificial Intelligence Advisory Service, a subscription-based market research and analysis suite that provides independent and objective market intelligence and strategy insights for companies engaged in the rapidly evolving artificial intelligence (AI) market. As part of the service, Tractica's global industry analyst team provides strategic and quantitative analysis focused on the market opportunity for AI technologies in enterprise, consumer, and government markets. Research reports include an in-depth examination of AI business models, use cases, technology issues, and key industry players in addition to detailed market sizing, segmentation, and forecasts. Tractica's Artificial Intelligence Advisory Service examines use cases and business models for the application of artificial intelligence technologies in enterprise, consumer, and government markets.


Business Case Drive Enhancements to Video Analytics

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The video analytics industry is typically split into two distinct camps: (1) systems designed around rules and user-specified rules or models and (2) autonomous systems designed around machine learning. Supervised learning systems require heavy training and feedback to achieve the desired output, where unsupervised learning systems train themselves from the input data and require minimal human input. The video analytic solutions we saw in the market a decade ago seem rudimentary compared to today's offerings; partly due to the technology catching up with early promises and partly due to the industry's understanding and level-setting of expectations from the initial splash of analytics hyped as a panacea and the future of security. However, some of the extreme claims such as its ability to replace trained human operators, eliminate the need for well-designed camera placement, completely eliminate false positives, and determine a person's intent ahead of an action have proven to be more hype than reality for many end users.


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The applications of AI are moving beyond predictive analytics and machine learning, as more innovative use-cases for anticipating the needs of customers, employees and partners emerge. This growth is being accelerated by billion dollar investments that technology companies are making in order to commercialise applications of AI. Secondly, since it is still an evolving area, there is a shortage of the skills required to design, build and integrate systems with AI capabilities. These changes can naturally create uncertainty amongst the workforce, so AI technology implementations require far greater organisational change management than traditional IT projects.