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5 things to know about getting started with AI/ML

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Alan Gibson, VP EMEA at Alteryx explains that these technologies have real business-altering potential and that's why Gartner's Enter the Age of Analytics report predicts that by 2023, AI and deep-learning techniques will be the two most common approaches for new applications of data science. But despite the promise, few companies have been able to successfully implement and deploy this technology as part of their overall data and analytics strategy--according to Gartner, 46 percent of CIOs have developed plans to deploy AI but just 4 percent have made the concept a reality. The truth is that it will take years before many organisations realise the true potential of AI and ML, but it is never too early to lay the groundwork now for an AI-driven future. In fact, if an organisation is not already thinking about what an AI strategy looks like, its competition is likely one step ahead. There's no time to waste, so here are five important points to consider when getting started with AI and ML.


6 Emerging Applications for AI in Healthcare

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What is the future of artificial intelligence (AI) in healthcare? It's a big question that almost every medical professional has had cause to ask recently, and the answer is even bigger. In fact, at this moment, the answer is something along the lines of, "We don't exactly know yet, but it's going to be monumental." There are, of course, current applications for AI being used and developed today that we can look at to inform our prediction of how AI will be used in healthcare in the future, and that's exactly what we're going to cover here. By the end of this article, we will have an answer to our question.


ML and BI Are Coming Together, Gartner Says

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The convergence of machine learning and business intelligence is upon us, as BI tool makers increasingly are exposing ML capabilities to users, and users are performing ML activities in their BI tools. That's according to the latest Gartner report on analytics and BI tools, which was released this week. In its February 11 Magic Quadrant for Analytics and Business Intelligence (ABI) Platforms, the storied Stamford, Connecticut analyst firm did its best to quantify and qualify the trends in the sector. While BI and ML have largely existed on parallel tracks, with BI seeking to report what happened and ML seeking to predict what will happen, Gartner sees the two disciplines converging, at least as far as the toolsets are concerned. Not all ML work will occur within BI tools, of course.


AI to replace 69% of manager's workload by 2024: Gartner

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Mumbai: Artificial Intelligence (AI) and emerging technologies such as virtual personal assistants and chatbots will replace almost 69 per cent of the manager's workload by 2024, according to a prediction by research and advisory firm Gartner on Thursday. "The role of manager will see a complete overhaul in the next four years," Helen Poitevin, Research Vice-President at Gartner, said in a statement. "Currently, managers often need to spend time filling in forms, updating information and approving workflows. By using AI to automate these tasks, they can spend less time managing transactions and can invest more time on learning, performance management and goal setting," Poitevin said. AI and emerging technologies will undeniably change the role of the manager and will allow employees to extend their degree of responsibility and influence, without taking on management tasks.


Increased automation to open more doors to disabled people, says Gartner

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The Gartner report, 'Predicts 2020: AI and the Future of Work', predicted that 69% of routine work by managers will be replaced by AI and emerging automation technologies by 2024. That proportion of managerial admin is expected to be offloaded to technologies such as chatbots and virtual personal assistants. This shift in reliance on technology is expected to empower employees more, giving them more responsibility and scope for influence without needing to take on management tasks. Matt Weston, Managing Director of Robert Half UK, examines the future of the workplace as automation and artificial intelligence shift the landscape. "The role of manager will see a complete overhaul in the next four years," said Helen Poitevin, research vice president at Gartner.


Internet of Things: Smart cities pick up the pace

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Our cities are becoming more connected by the day. Around the world, cities are using the Internet of Things (IoT), fifth generation mobile networks and artificial intelligence technologies to cut traffic congestion, improve public safety and protect the environment. IoT devices monitor sewers, air quality and rubbish. Smart street lamps save energy by tracking pedestrian volumes, while sensors on roads and bridges monitor vibration and humidity for damage. In 2019, the IoT network had 14.2bn devices, according to Gartner, a research company.


What can machine learning do for testing? - Software Testing News

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With the move to DevOps and high-paced development, there is a greater and more frequent need to specify test environments to ensure that systems are working efficiently; yet the ability of enterprise to model and manage capacity accurately is immature. Performance testers are theoretically well-placed to help but they may be naturally cautious about modelling capacity since testing functions can run up significant annual costs in capacity usage alone. You'll have heard plenty about AI (artificial intelligence) and ML (machine learning) of late, and with good reason – delicate, complex and downright costly technology and tools are rapidly maturing into usable toolsets in a wide range of verticals. Analyst firms predict huge markets for AI and ML, indeed the number of enterprises implementing artificial intelligence (AI) grew 270 percent in the past four years and tripled in the past year, according to industry analyst Gartner's 2019 CIO Survey. Results showed that organisations across all industries use AI in a variety of applications but on the downside struggle with acute talent shortages.


AI in manufacturing is stalled by lack of data infrastructure and internal buy-in

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According to Gartner, artificial intelligence is still in the early phases of the hype cycle. Among the 37 types of AI on its chart, only speech recognition and GPU accelerators have reached the plateau of productivity. Despite the fact that many AI technologies are too new for mainstream adoption, manufacturing leaders are already stuck in a rut with these projects, according to a new survey from Plutoshift. Plutoshift found that manufacturing professionals are having trouble with almost every aspect of AI projects from defining realistic outcomes and collecting data to getting internal buy-in. The Gartner Hype Cycle for Artificial Intelligence 2019 examines the stream of innovations and trends in the AI sector and scopes AI plans.


Report predicts 69% of managers' routine work will be completely automated by 2024

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Will AI render managers obsolete by 2024? Perhaps not entirely, but a new report from Gartner predicts that with innovation and the responsible adoption of AI tech, the tedium of managers' paper flow will be greatly reduced by an estimated 69%. "The role of manager will see a complete overhaul in the next four years," said Helen Poitevin, research vice president at Gartner, in a release. "Currently, managers spend time filling in forms, updating information and approving workflows. By using AI to automate these tasks, they can spend less time managing transactions and can invest more time on learning, performance management and goal setting." SEE: Prescriptive analytics: An insider's guide (free PDF) AI will influence the office, but the level at which it does, will be based on new tech advances, organizational readiness to exploit, and worker attitudes, the report, "Predicts 2020: AI and the Future of Work," found.


The boss machine is here -- AI is all set to eliminate middle managment in 8 years

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The massive pace at which companies are adopting automation and artificial intelligence may lead to elimination of middle management roles over the next decade. Smart machines will soon become co-workers -- changing the modus operandi of how employees work. According to Gartner, "People managers will focus on people-related activities that require intuition, empathy and interpersonal skills." A recent McKinsey report also said that nearly half of the activities undertaken by the workers could be automated -- including managing expertise. A lot of offices have already replaced secretaries with virtual assistants.