8 AI Highlights of 2018: Jobs, Research, Skills, Events, More - InformationWeek

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Data Management // AI/Machine Learning
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Jessica Davis
Jessica Davis
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8 AI Highlights of 2018: Jobs, Research, Skills, Events, More

Things happen fast in artificial intelligence and machine learning. Here are some of the highlights of 2018.
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Artificial intelligence technology has grown more powerful and sophisticated as new advances build on old ones, and the pace just keeps accelerating. Experts point to the difference between how long it took AI to beat a game like chess to how long it took AI to beat humans at Go -- years versus days. Now, as 2018 comes to a close and technology's pace continues to accelerate. We are living in a world where if you aren't already doing some kind of agent based technology now, you are probably behind the curve, according to Gartner analyst Janelle Hill, speaking about the adoption of AI in the enterprise at the most recent Gartner Symposium.

But chatbots are just the entry-level technology for many enterprises. There are loads of other advances and innovations on the way, enabled by artificial intelligence and the technologies that comprise it -- machine learning, deep learning, natural language processing, computer vision, and more.  

Enterprises have a long way to go to fully leverage these technologies to enable their businesses. It's one thing to have a vision, a plan, or a pilot. It's another thing entirely to put that into practice in a way that makes a meaningful impact on the business, by either improving operations, increasing sales, creating new markets, or some other way.

Advances in technology and the demand for artificial intelligence in businesses and other organizations are driving changes in other places, too. For instance, the high demand for more technology professionals that specialize in AI, machine learning, natural language processing (NLP) and related technologies is continuing and accelerating. Some organizations, recognizing the challenge have changed the way they look at their teams. Maybe they are splitting that data science unicorn job into a team of several workers, each with a specialized expertise -- a statistician, a developer, a business expert. Perhaps they have set their data scientists to work enabling more self-service options for analytics users, bringing the ability to find the business value to the masses.

At the same time, universities and other educational institutions have risen to the challenge to graduate more experts in artificial intelligence disciplines such as machine learning and deep learning. Universities may be expanding the courses they already have available to teach the skills needed. Other universities may be adding these disciplines for the first time. Recognizing the strong job market for these professionals, students are enrolling in these courses.

In this environment, the acceleration of AI innovation is captured in a series of data points and milestones collected from 2017 (as the most recent year that information has been published so far in 2018) and from 2018. The results are published in a paper by Stanford University, The AI Index 2018 Annual Report and compiled by a team of experts from organizations including MIT, Stanford, Harvard, OpenAI, and McKinsey Global Institute, among others. Here are a few of the data points these experts highlighted.

Jessica Davis has spent a career covering the intersection of business and technology at titles including IDG's Infoworld, Ziff Davis Enterprise's eWeek and Channel Insider, and Penton Technology's MSPmentor. She's passionate about the practical use of business intelligence, ... View Full Bio

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