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.

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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.

LAGUNA BEACH, Calif.--International Business Machines Corp.'s Watson artificial-intelligence technology is on track to be used in some form by a billion people by the end of next year, Chief Executive Virginia Rometty said Wednesday. Ms. Rometty, speaking at The Wall Street Journal's WSJDLive 2016 technology conference, pointed to the company's new deal with General Motors Co. to pair Watson with GM's OnStar system in cars as an example of how IBM is extending Watson's reach. She said such partnerships will have put...

Deep Learning is becoming the next big area for companies and universities to explore. Deep Learning libraries are growing and their adoption is expanding. With Google's open sourcing of TensorFlow, there is a massive rise in deep learning adoption. I have started using it for it's very interesting Image Recognition capabilities which can be used out of the box with their ImageRecognition example. Google has released a new TensorFlow library - Image Recognition, Slim. TF-Slim is a lightweight library for defining, training and evaluating complex models in TensorFlow, which should speed up adoption and ease of use.

Almost a quarter century ago, a book was written about how organizations would focus on share of customer as opposed to share of market, building a personalized collaboration driven by big data. With advanced analytics, banking may finally getting close to realizing this vision. In 1993, a then revolutionary book, "The One to One Future: Building Relationships One Customer at a Time" was published, proposing the idea that as technology makes it affordable to track individual customers, marketing shifts from finding customers for products to finding products for customers. According to the authors, Don Peppers and Martha Rogers, Ph.D., a company could use technology to gather information about, and to communicate directly with, individuals to form a commercial bond. The book became a bestseller, and was on every marketer's bookshelf … almost a quarter century ago.

Artificial intelligence and robots aren't coming for your job anytime soon, the U.S. White House's chief economic adviser says. Some technology experts worry about the economic impact of A.I.-powered computers and robots, but Jason Furman, chairman of the White House Council of Economic Advisers, predicts that A.I. will grow the economy instead of taking jobs away. While some jobs may disappear, A.I. will create new jobs and consumer demand for new products and services, he said Wednesday at the Nvidia GPU Technology Conference in Washington, D.C. While technology critics believe "the robots are going to take all our jobs away from us," A.I. won't change the basic rules of economics, Furman said. A.I. will create some economic challenges, just as other technologies have, he said.

It took less than 5 mins for me to activate and transfer money from my China Merchant's Bank account to a friend. Using facial recognition, the smartphone app directed me to tilt my head, blink my eyes and hold my face still to authenticate the transfer. Facial recognition is gaining traction at a startling pace in China. Real-world applications already range from verifying Uber drivers to identifying people seeking to withdraw cash from an ATM without a debt card. Chinese startups in this space have attracted serious funding: Face was most recently valued at $1B.