How to explain machine learning in plain English

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Machine learning is already pervasive: Most people probably don't realize it. "Whether or not you know it, odds are that machine learning powers applications that you use every day," says Bill Brock, VP of engineering at Very. "Machine learning has revolutionized countless industries; it's the underlying technology for many apps in your smartphone, from virtual assistants like Siri to predicting traffic patterns with Google Maps." Perhaps you care more about the accuracy of that traffic prediction or the voice assistant's response than what's under the hood – and understandably so. But as machine learning use cases continue to increase, you will find yourself needing to explain at least the basics of the technology to folks outside of IT, whether it's to get buy-in, to showcase the work of your team, or simply to build better communication and understanding between departments. Your understanding of ML could also bolster the long-term results of your artificial intelligence strategy.


AI skills: 5 ways to build talent internally

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As artificial intelligence use cases expand inside all types of businesses and industries, you can expect another sequel to a timeless IT hiring story: The Skills Shortage, AI edition – coming soon to a team near you. As Pat Calhoun, CEO of Espressive, told us recently: "Most organizations want to embrace AI as part of their digital transformation but do not have the developers, AI experts, and linguists to develop their own or to even train the engines of pre-built solutions to deliver on the promise." As new technologies emerge and especially as their adoption begins to spike, there's commonly a gap between an organization's goals and the technical skills necessary to achieve those goals. So while AI might sound exotic and fancy, you don't actually need a newfangled playbook to bridge the gap. "Despite its evocative title, AI is remarkably similar to other fields in information technology, in that success comes through continuous learning, training, and great processes," says Zachary Jarvinen, head of technology strategy for AI and analytics at OpenText.


"Above the Trend Line" – Your Industry Rumor Central for 12/24/2019 - insideBIGDATA

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Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, industry partnerships, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. Our intent is to provide you a one-stop source of late-breaking news to help you keep abreast of this fast-paced ecosystem. We're working hard on your behalf with our extensive vendor network to give you all the latest happenings. Be sure to Tweet Above the Trend Line articles using the hashtag: #abovethetrendline.


9 Artificial Intelligence Trends You Should Keep An Eye On In 2019

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Artificial Intelligence has become a hot topic in tech circles. It has not only changed our lives, but it has also disrupted every industry you can think of. Despite all this, people have different perception about it. Some might consider it as a bad thing because they are told that it will take your job away from you in near future. On the other hand, AI advocates continue to think of AI as an enabler which will reduce your burden and make your life easy by automating things.


AI in 2019: 8 trends to watch

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December means holiday parties, New Year's resolutions, and a blizzard of technology industry predictions. You'll see a ton of AI-related calls as we approach 2019. The artificial intelligence hype machine is already roaring. The potential impacts of AI are wide-ranging – as are the related forecasts, on everything from how AI will change college admissions to the role it will play in international relations and politics. We decided to focus on the trends that matter most urgently to IT leaders – you don't need another "AI is taking over the world" story; you need concrete insights for your team and business.