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.

Clarifai, whose visual recognition software can instantly sort through a travel website's millions of hotel photos, has raised $30 million in a Series B round. The Flatiron-district-based startup plans to use the money to further its development of low-cost and easy-to-use artificial intelligence applications. Silicon Valley stalwart Menlo Ventures led the round, with participation from existing investors, including Union Square Ventures, Lux Capital and Qualcomm Ventures. Founded in 2013, Clarifai has so far raised a total of $41 million. "We've launched new products that move us in this direction of personalizing AI and getting away from this one-size-fits-all approach," said Clarifai founder and CEO Matt Zeiler in an interview.

Today in AI: Machine learning heavyweights launch AI startup factory, D-Wave co-founder reveals ... Google's neural networks invent their own encryption MIT scientists are training AI to scare people. Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Machine learning enables computers to learn from large amounts of data without being explicitly programmed to do so. We can already see how machine learning gives rise to new intelligent applications, from self-driving cars to intelligent assistants on our smartphones. Increasingly, businesses recognize the importance of using machine learning to transform their data assets into business value. However, many companies are unsure how machine learning can be applied to solve problems in an enterprise context. As the world's most relevant enterprise data is part of SAP's system and business network, SAP aspires to make all its enterprise solutions intelligent and help customers to leverage their data.

Formerly known as the CNTK, Microsoft says the beta version of the Cognitive Toolkit is not only faster than previous incarnations, but it is also beats out competing deep learning toolkits – especially when crunching large datasets across multiple machines. On a more practical level for startups and hobbyists, Microsoft says the platform is flexible enough to run on a solo laptop -- just in case you don't have a server farm loaded with NVIDIA GPUs at your disposal. The public release also allows developers to bring their own Python or C code to the deep learning party. The Cognitive Toolkit is available now on GitHub, but Microsoft has also put together an expansive set of documentation, complete with tutorials and example models, on its own Cognitive Toolkit site.

Yoshua Bengio, one of the leading figures behind the rise of deep learning, is launching a Silicon Valley-style startup incubator dedicated to this enormously influential form of artificial intelligence. The incubator, Element AI, will help build companies from AI research that emerges from the University of Montreal, where Bengio is a professor, and nearby McGill University, and he says this is just part of his efforts to develop an "AI ecosystem" in Montreal. Bengio says the Canadian city offers "the biggest concentration in the world" of academic researchers exploring deep learning, the breed of AI that now plays such an important role inside the likes of Google, Facebook, and Microsoft. "Element AI will help entrepreneurs get started in that high-growth area, with a team of experts--and my help--to steer those companies in the right direction," he says. According to Bengio, about 100 researchers are exploring deep learning at the University of Montreal and about 50 others are doing similar work at McGill.