On average, when an AP sportswriter covers a game, she produces eight different versions of the same story. Aside from writing the main print story, they have to write story summaries, separate ledes for both teams, convert the story to broadcast format, and more. "It's a manual labor nightmare," Jim Kennedy, the AP's senior vice president for strategy and enterprise development, told me in his New York office. Collectively, AP journalists spend about 800 hours a week converting print stories to broadcast format. As a result, the AP is experimenting with machine learning in an attempt to automate some of those processes.

As an IBM developerWorks information architect, I gave a presentation last week about cognitive computing to entrepreneurs and staffers at tekMountain, a co-working and tech incubator in Wilmington, North Carolina where I work as a tech mentor. The title is a bit tongue and cheek, but I really tried to position the Watson application development demo I gave as the "applied" part of a series that we launched in the area last year on artificial intelligence. At a previous "Exploring Artificial Intelligence" TechTalk, my buddies Mike Orr (IBM Watson University program chair) and Julian Keith (UNC Wilmington Psychology Chair and brain guy), began a series of conversations about artificial intelligence that quickly blossomed into several different AI events with different AI focuses at different venues. An upcoming talk in this very popular series (for example) is titled "Is artificial intelligence going to do my job better than me?" As a software development enthusiast who sometimes teaches kids and others how to start coding, I naturally conceived of a hands-on version of Watson services as a way to take the conversation further.

In the next five years, every important decision, whether it's business or personal, will be made with the assistance of IBM Watson. Watson, the company's artificial intelligence-fueled system, is working in fields like health care, finance, entertainment and retail, connecting businesses more easily with their customers, making sense of big data and helping doctors find treatments for cancer patients. The Watson system is set to transform how businesses function and how people live their lives. "Our goal is augmenting intelligence," Rometty said. "It is man and machine. This is all about extending your expertise. It doesn't matter what you do. IBM's conference this week, which the company said drew 17,000 attendees, explored how companies, including retailers, educators, human resources departments and financial institutions, amon others, can use Watson. "The challenge IBM has right now is to define the marketplace," said Jeff Kagan, an independent industry analyst, who attended the conference. "Ten years from now, will IBM be the leader?

Chatbots could become much more useful for knowledge workers if IBM Corp. and Slack Inc. have their way. Against the backdrop of its annual World of Watson summit in Las Vegas this week, Big Blue has struck a partnership with the communications startup to develop new artificial intelligence capabilities for Slack's messaging platform. Their first priority is to integrate the Watson Conversation service that launched at the event yesterday into Slackbot, the default personal assistant included in Slack rooms. It offers explainers about the tool's various features and can be configured to answer common questions such as inquiries about a chat channel's purpose. IBM and Slack say that Watson's natural language processing capabilities will increase the accuracy of the bot's responses while improving its efficiency at generating replies.

If you are a software developer who wants to learn how machine learning models work and how to apply them effectively, this book is for you. Familiarity with machine learning fundamentals and Python will be helpful, but is not essential. This book examines machine learning models including logistic regression, decision trees, and support vector machines, and applies them to common problems such as categorizing documents and classifying images. It begins with the fundamentals of machine learning, introducing you to the supervised-unsupervised spectrum, the uses of training and test data, and evaluating models. You will learn how to use generalized linear models in regression problems, as well as solve problems with text and categorical features. You will be acquainted with the use of logistic regression, regularization, and the various loss functions that are used by generalized linear models.

Check out our Workology Podcast powered by Blogging4jobs. Click here to check out all our episodes. What Does Artificial Intelligence Mean in Human Resources and Recruiting? One of the most talked about trends in HR and recruiting the second half of 2016 has been about AI and artificial intelligence. Artificial intelligence is defined as "an ideal "intelligent" machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal."

Jerry Kaplan has been working on artificial intelligence since the 1950s. He explains to Leo the difference between general artificial intelligence, machine learning, and automation. He also explains why he thinks the idea of the Singularity is nonsense, that the real thing the Turing Test describes is trickery rather than intelligence, and that much of the current hype over the development of AI is just that: hype. He does think that the current growth of machine learning can and will transform the economy - many jobs will be replaced through automation, but many other opportunities will be created.

As technologist Joi Ito, director of the MIT Media Lab and a board member at the The New York Times and at Sony, recently predicted, "This is the year artificial intelligence becomes more than just a computer science problem." This week, the White House issued a formal position paper with 23 recommendations on artificial intelligence. Let me cut to the chase: they don't think superhuman A.I. is imminent. While you're relaxing in the good news, take in the pleasant surprise that the National Science and Technology Council (NSTC) and the Office of Science and Technology Policy (OSTP), which advises the President in policy and budget development, coordinated efforts to deliver this cohesive position paper. The outcome is a chunky, committee-clarified read, but for all that, it cuts to the chase on big issues in nontechnical language.

Big global banks are now turning their businesses to artificial intelligence technology to stay competitive in this digital era. This technology has major benefits, both for the banks and as well as their customers. Here are the core AI banking features, which can be delivered by Centurysoft. Voice-assisted banking enables customers to use banking services with voice commands apart from a touch screen or press button. The Natural Language Processing technology can process queries to answer the questions, finding information, and connecting the users with various banking services.

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