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Our Inevitable Future: A Conversation With Kevin Kelly About VR, Digital Socialism, And His New Book

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If you're a virtual reality enthusiast, you probably read Kevin Kelly's April Wired cover story on Magic Leap, "The World's Most Secretive Startup." Kelly is one of the few people who've seen the much-hyped mixed reality technology being produced by the Fort Lauderdale company and was suitably impressed by it. "While Magic Leap has yet to achieve the immersion of The Void," he wrote (referring to the Utah-based immersive experience company), "it is still, by far, the most impressive on the visual front -- the best at creating the illusion that virtual objects truly exist." As the co-founder of Wired, publisher of the Cool Tools website, and former publisher and editor of The Whole Earth Review, Kelly has always been prescient about these things. In his new book, The Inevitable: Understanding 12 Technological Forces That Will Shape Our Future, he compellingly outlines a set of behaviors and trends that will change the way we live. We recently spoke with Kelly about the themes of the book, and of course, the latest developments in VR. There Is Only R: The first question I have to ask: what do you think of the Pokemon Go phenomenon? Given what you've written about the VR and AR, what's your take on it? Kevin Kelly: I think it's just wonderfully thrilling to see -- I think perhaps the only unexpected thing about it is its apparent suddenness.


Scotiabank pumps funds into disruptive tech venture at OofT Rotman School of Management

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The gift of 1.75 million will create the Scotiabank Disruptive Technologies Venture at the Rotman School of Management and support programs and initiatives including: "Successful businesses in the digital economy are creating new products and services, and reimagining how existing ones are delivered. This requires a new generation of talent that has the knowledge to understand the possibilities of a digital world and the skills to seize them," says Tiff Macklem, Dean, Rotman School of Management. "This investment by Scotiabank will help us scale up our very successful experiential learning programs in technology-based entrepreneurship and design thinking." "Consumers expect the same frictionless experience whether they're paying for a coffee, booking a hotel room, ordering a taxi or signing up for a credit card," says Brian Porter, President and Chief Executive Officer, Scotiabank. "As we work to deliver the best experience to our customers, we recognize the tremendous value of working closely with post-secondary institutions and their students. It also provides students hands-on experience to prepare them for job opportunities in the digital world. Scotiabank's partnership with Rotman is an important piece of our digital strategy, and we are optimistic that it will produce great results."


When Bots Go Bad: Common UX Mistakes In Chatbot Design

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Bots will one day sweet-talk their way into our good graces, but that day is not today. Judging from recent debacles such as Microsoft's Tay and the fembots of Ashley Madison, AI-assisted chatbots still have a long way to go before gaining genuine and socially acceptable conversational skills. Just visit YouTube and you'll realize that giving bots an eerily human-like appearance is much easier than granting them the gift of gab. That means you'll have to wait just a bit longer before a real-life version of either Jarvis (The Avengers) or Samantha (Hers) will arrive to stir your intellect or your emotions. Nonetheless, chatbots have certainly made huge strides since they were first used decades ago.


Pinterest Is Using Machine Learning To Help You Find What You'll Pin Next

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With 100 million users active on its platform every month, Pinterest is increasingly relying on machine learning to help guide the company to new online discoveries. People come to Pinterest to explore, save, and share images and posts from around the internet. Finding content they like naturally keeps them engrossed in the platform: The company says 30% of engagement and 25% of in-Pinterest purchases are driven by the platform's recommendations of related content. To get those recommendations right, the company relies on cutting-edge, data-driven techniques and lots of experimentation. "A lot of what I"m doing here is trying to shape what direction we go in approaching the discovery problem," says Pinterest's lead discovery science engineer Mohammad Shahangian.


Pinnability: Machine learning in the home feed

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The home feed, a collection of Pins from the people, boards and interests followed, as well as recommendations including Picked for You, is the most heavily user-engaged part of the service, and contributes a large fraction of total repins. The more people Pin, the better Pinterest can get for each person, which puts us in a unique position to serve up inspiration as a discovery engine on an ongoing basis. The home feed is a key way to discover new content, which is valuable to the Pinner, but poses a challenging question. Given the ever increasing number of Pins from various sources, how can we surface the most personalized and relevant Pins? Pinnability is the collective name of the machine learning models we developed to help Pinners find the best content in their home feed.


Next In Tech

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Think back to when you were a child. You were in a data-rich environment, but only starting to make sense of it all. You barely knew the names for things, much less how one thing related to another. By this point, most of your experiences fit into webs of different but familiar contexts. You understand your co-workers' roles, their strengths and weaknesses, where they come from, what their families are like, who they work best with.


EFIS 2016: Execs Embrace 'Rise of the Machines' for Data Management, Trading

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Shannon Walker, chief operating officer of the chief data office at Deutsche Bank, described how the bank is building a data science platform mainly focused on organizational complexity and making sense of what functions are consuming data, in what locations, and for what purposes. Meanwhile, BNP Paribas is using machine learning "in a systematic and statistical way.... digging up a trading system's...


Mircosoft surpasses IBM's Watson in speech recognition

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This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers. To learn more and subscribe, please click here. A team of Microsoft researchers has achieved the lowest error rate for speech recognition on record at 6.3%, overtaking prior record holder IBM Watson's 6.9%. The news brings the company one step closer to getting computers to understand speech as well as a person, and helps in its efforts to provide conversation as a service through tech like Cortana, Skype Translator, and other language-related cognitive services. Voice is going to emerge as a dominant computing interface.


Machine Learning is the solution to the big data problem whose root cause is the Internet of Things

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Yes, the title is a precious mess. But "Big Data" was always defined as a problem statement. For some, it represented the challenge of acquiring data from new sources. For others, it meant the herculean task of building a scalable infrastructure that could manage all the data. For a brave few, it meant the arcane art (or presumptive science) of extracting value from data using advanced data analysis techniques and tools.


How to Use Machine Learning to Further Retail Analytic Capacity - insideBIGDATA

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Kerry leads three important functions at Rubikloud: people, sales, and technology disruption. Rubikloud helps retailers monetize their data to power personalized campaigns through the use of advanced machine learning techniques, effectively bridging the gap between marketing automation and retail management consultants. In his role, Kerry works to manage and maintain a thriving company culture that recruits the best and brightest in the industry, while also maintaining relationships with global retailers and investors. He is passionate about machine learning and big data, and enjoys providing enterprise retailers with the tools and knowledge needed to enhance their overall business goals. If you're only using big data to target consumers based on demographics or purchase history, you're making a mistake that will cost your company a significant amount of revenue.