While the number of headlines about machine learning might lead one to think that we just discovered something profoundly new, the reality is that the technology is nearly as old as computing. It's no coincidence that Alan Turing, one of the most influential computer scientists of all time, started his 1950 treatise on computing with the question "Can machines think?" From our science fiction to our research labs, we have long questioned whether the creation of artificial versions of ourselves will somehow help us uncover the origin of our own consciousness, and more broadly, our role on earth. Unfortunately, the learning curve on AI is really damn steep. By tracing a bit of history, we should hopefully be able to get to the bottom of wtf machine learning really is.

Watson, can you grow into a multibillion-dollar business and become the engine of IBM's resurgence? IBM is betting its future that the answer is yes. Its campaign to commercialize Watson, the company's version of artificial intelligence technology, stands out, even during the current A.I. frenzy in the tech industry. IBM has invested billions of dollars in its Watson business unit, created at the start of 2014, which now employs an estimated 10,000 workers. Its big-ticket marketing push includes clever television ads that feature Watson trading quips with famous people like Serena Williams and Bob Dylan.

In AI-Ready or Not, Weber Shandwick surveyed global consumers and senior ranking marketers on their attitudes toward and expectations for artificial intelligence (AI). The following provides the results of the consumer perspectives and what those implications mean for marketers. In its most basic definition, AI is intelligence exhibited by machines. It is frequently thought of as robotics, but encompasses a broader range of technologies, some of which are in wide use among the general population today.

Jason Tan is the co-founder and CEO of Sift Science. He's also held leadership and engineering roles at BuzzLabs, Optify and Zillow. Facebook recently fired the entire Trending Topics team of human editors amid accusations they were promoting specific agendas and biasing what news was deemed "important." Now the company is relying on machine learning algorithms to manage Trending Topics -- and finding that keeping the results free of hoaxes and fake news isn't always easy. The social media giant recently assured an audience at TechCrunch Disrupt that it was working on new technology that would help prevent untrue or satirical stories from being labeled as legitimate news we should follow.

The text is supported by a strong outline. The authors preserve much of the introductory material, but add the latest techniques and developments in data mining, thus making this a comprehensive resource for both beginners and practitioners. The focus is data-all aspects. The presentation is broad, encyclopedic, and comprehensive, with ample references for interested readers to pursue in-depth research on any technique. "This interesting and comprehensive introduction to data mining emphasizes the interest in multidimensional data mining--the integration of online analytical processing (OLAP) and data mining. Some chapters cover basic methods, and others focus on advanced techniques. The structure, along with the didactic presentation, makes the book suitable for both beginners and specialized readers."

Want to watch this again later? Need to report the video? This feature is not available right now. Although numeric data is easy to work with in Python, most knowledge created by humans is actually raw, unstructured text. By learning how to transform text into data that is usable by machine learning models, you drastically increase the amount of data that your models can learn from.

SAN FRANCISCO - 26 Oct 2016: IBM (NYSE: IBM) and Slack are partnering to bring Watson to Slack's global community of developers and enterprise users. Drawing on the power of Slack's digital workplace and the cognitive computing capabilities of Watson, developers will be able to create more offerings -- including bots and other conversational inferences -- that will transform the platform's user experience. Developers can easily access the range of Watson services -- such as Conversation, Sentiment Analysis or speech APIs -- and build powerful new tools for the platform with this enhanced cognitive functionality. As a first step, IBM and Slack intend to develop new and improved communications tools for users of the Slack platform, including an updated Slackbot to be powered by Watson and an IBM Watson-enabled bot for IT and network operations. IBM and Slack also plan to share learnings from the creation of these tools with developers as part of ongoing educational efforts, and the companies plan to offer specialized tutorial resources to accelerate how developers can tap into Watson: Slack Intends to Adopt Watson Conversation for Slackbot: To further strengthen the Slack user experience, Slack intends to adopt Watson Conversation as a technology that helps power its Slackbot -- the platform's popular customer service bot.

Anyone else wondering if some garage somewhere has the AI equivalent of Google or Microsoft. Really interesting, but that is more Rhen 8 months old.

The search to improve and eventually perfect artificial intelligence is driving the research labs of some of the most advanced and best-known American corporations. They are investing billions of dollars and many of their best scientific minds in pursuit of that goal. All that money and manpower has begun to pay off. In the past few years, artificial intelligence -- or A.I. -- has taken a big leap -- making important strides in areas like medicine and military technology. What was once in the realm of science fiction has become day-to-day reality. You'll find A.I. routinely in your smart phone, in your car, in your household appliances and it is on the verge of changing everything. On 60 Minutes Overtime, Charlie Rose explores the labs at Carnegie Mellon on the cutting edge of A.I. See robots learning to go where humans can'... It was, for decades, primitive technology. But it now has abilities we never expected. It can learn through experience -- much the way humans do -- and it won't be long before machines, like their human creators, begin thinking for themselves, creatively.

The increasing pace of digital is changing civilization as we know it, according Peter Sondergaard, senior vice president of Gartner Research, who spoke on Oct. 17 from the middle of a harsh spotlight on a darkened stage at the Gartner Symposium ITxpo 2016 in Orlando, Florida. The digital world around us is in a permanent state of upgrade," he warned. The dramatic words were followed by other speeches delivered by Daryl Plummer, vice president and Gartner fellow, and Hung LeHong, vice president and Gartner fellow. The speeches were no less dramatic, but rather less dark, taking their tone from another early passage in Sondergaard's speech: "CIOs are builders again." CIOs are building an infrastructure for an increasingly digital business, Sondergaard said, noting that Gartner is estimating that within three years more than half the value of most company's products will arise from their digital content. That digital content will be built on a digital platform and an infrastructure that is critical because, according to Sondergaard, "When you build it, it will bring the capability to reach customers and things more intelligently." Traditional core IT systems remain important to the organization, because the business must continue to operate while the digital transformation takes place. This traditional IT is Mode 1 in Gartner's Bimodal IT model, with Mode 2 as the dynamic, transformative digitalization mode. LeHong said, "You don't need two organizations for bimodal.