A number of web APIs enable developers to develop applications using IBM Watson, Watson Machine Learning infrastructure, and capabilities running on IBM Cloud Services to build analytical models and neural networks, deploy AI, and more. Watson Analytics is a natural language-based cognitive service from IBM Watson that can provide real-time analysis, machine learning, and artificial intelligence (AI) capabilities. Watson Analytics, which includes IBM Cloud Services, an IBM cloud-based service that runs on both desktop and mobile devices, is available in a range of languages including English, French, German, Spanish, English – as – a – Second – Language (EASL) and Mandarin Chinese (Mandarin), as well as English and French. Watson is an IBM supercomputer that combines the best of both worlds – a high-performance computing platform and artificial intelligence (AI) for the optimal performance of an answering machine. This expert guide(IBM Watson) is designed to help you better understand the design and maintenance considerations of your infrastructure machine that support your initiative.

If you work at IBM or a company equipped with their artificially intelligent employee retention software, your planned two-week's notice may already be old news. According to a recent panel discussion with IBM's CEO, Ginni Rometty, at a Work Talent and Human Resources Summit in New York, the company's'predictive attrition' software is now 95 percent accurate in determining when an employee is ready to quit. Using their predicative software, Rometty says that IBM has been able to preempt employees on the cusp of quitting, bolstering their retention rates, which has reportedly saved them $300 million. Human resources may need a new name as a host of new software has begun to disrupt jobs and efficiency. Among the many AI-powered tools being developed by IBM for human resources is'predictive attrition.'

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The question came via Facebook Messenger from a friend who was coming over for dinner. Under his message appeared two options: yes and no. With one touch of a fingertip, my answer appeared in a blue bubble as if I had typed y-e-s myself. That experience, a first for me, was so logical, natural, convenient, and simple that I hardly noticed it. An app had recognized my friend's message as a yes-no question and had presented me with ready-to-use replies. Nothing about the exchange shouted, "Hey! Only after I heard Paul Roetzer's Content Marketing World talk did I realize that my experience represented exactly that: artificial intelligence at work. In fact, artificial intelligence is at work all around us. And this "science of making machines smart" (Paul's favorite definition, which comes from Demis Hassabis, co-founder and CEO of Google DeepMind) is beginning to open possibilities for B2B marketers who want to increase efficiency, boost performance, and create a competitive advantage. If you take away only one thing from this post, let it be Paul's mantra: "Try it!" If you take away two things, let the second be "Don't wait!" This post covers highlights of Paul's CMWorld talk, Machine-Assisted Narrative: How to Transform and Scale Your B2B Content With Artificial Intelligence. As a marketer, you'll never have to understand artificial intelligence in depth. "You don't have to know how it works.

When people in an emergency situation call into their local 911 operations center, there might be another "brain" listening in on the call. The Association of Public-Safety Communications Officials (APCO) International, which has more than 29,000 members, tapped IBM to bring Watson into their software. APCO recently announced that APCO International's new guide card software called APCO IntelliCommä will use IBM Watson Speech-to-Text and Watson Analytics to improve the scripts used by 911 operators. The guide card system provides guidance to 911 operators on what to ask and say to gather needed information to access specific emergency call types. Essentially, the software helps operators "provide rapid and customized instructions so callers get the fast, consistent, and appropriate information they need and expect in an emergency," according to a press release.

In two previous posts, I covered the emerging industry of cloud-based machine learning solutions. First, I covered Microsoft's Azure Machine Learning and IBM's Watson Analytics. Microsoft's Azure ML provides a graphical drag-and-drop interface for connecting preprogrammed components of a data science pipeline together. The service is similar to KNIME and seemed targeted for users who knew just enough to know what to do, but not so much that they would want to code up fresh algorithms. One value added for Microsoft's product is a smooth integration for companies which already have their data stored in Microsoft's Azure compute cloud.

Managing business data is a big trend right now. Through a couple of clicks and a couple drags, anybody can explore it. Businesses have been collecting and analyzing data since the 1950s. Data is the prime factor for businesses in order to gather the information and related analysis to increase operational efficiency, reduce costs and serve their customers. You might be wondering, why one must care about Data Analysis, in particular?

Summary: IBM's Watson as it exists today is as close as we've come to a single integrated platform for AI. It contains all the capabilities for image and video, natural language speech and text input and output, and the most comprehensive knowledge recovery module yet combined together. If you want to exploit the advances we've made in AI you need to understand where Watson is today and where it's heading. Recently we wrote about how the'popular' Watson of Jeopardy fame still lingers in the memories of our non-data scientist colleagues and perhaps misleads them about the capabilities of AI. It's time we got in tune with the modern Watson, or more correctly IBM's Watson Group and its Watson platform and took a look at all there is to offer. There are three broad capabilities in today's AI and they are: Image and video processing: Largely driven by Convolutional Neural Nets (CNNs) this field has been getting most of the press with capabilities like facial and object recognition.

From winning Jeopardy in 2011 to helping write a sad song last year, IBM's Watson cognitive computing platform is all over popular culture. Press releases fly out about Watson producing a movie trailer, powering a Macy's shopping app, even controlling lights on an internet-connected dress--along with more serious applications like working on cancer treatments. It seems, from IBM's hype, that Watson can do everything. But Bernie Meyerson, IBM's chief innovation officer, wants to dial back the hype in some ways, calling Watson "just the first step on a very, very long road." Watson can be helpful in a lot of industries, such as medicine, which are awash in data, but it can't replace people, he says.