Under, behind and inside many of the apps we use every day, a revolution is underway. It's a revolution that started decades ago but today is empowering companies to deliver better, smarter services with greater ease and on broader scales than ever before. At Singularity University's inaugural Global Summit, Neil Jacobstein, chair of Artificial Intelligence and Robotics, provided a primer showing how artificial intelligence literally transforms everything it touches. First of all, it's critical to define the scope of artificial intelligence (AI), which can be categorized into four areas: techniques in pattern recognition, software agency (that is, software that acts like real users), an exponential technology that is accelerating other exponential technologies, and a vision of a future superhuman intelligence (that fortunately hasn't happened yet). Anyone who has seen a science fiction film is likely familiar with this last area, but it's the other three areas where AI is making huge strides at a revolutionary pace.

Summary: Next time you bring up Artificial Intelligence and your non-data scientist friends all say "Watson" here's some perspective you can offer. Their understanding of AI and Watson is very likely to be inaccurate. Here's what you need to know to set them straight. When conversation with my non-data scientist friends turns to AI it's almost inevitable that at least one will remark on the wonders of Watson. To many of the uninformed, Watson is synonymous with AI and clearly it's already here.

Investors believe it is'inevitable' that artificial intelligence will destroy millions of jobs and that governments are unprepared for such an impact, according to a new survey. Artificial intelligence (AI), or the process by which computers or robots take on tasks that need human intelligence, is one of the key themes of this week's Web Summit in Lisbon. The poll among 224 venture capitalists attending the conference showed 53 percent believed AI would destroy millions of jobs and 93 percent saw governments as unprepared for this. The poll among 224 venture capitalists attending the Web summit in Lisbon found 53 percent believed AI would destroy millions of jobs and 93 percent saw governments as unprepared for this. The survey also found that 83 percent of the investors canvassed expect Britain's exit from the European Union to damage Europe's economy and 77 percent believe it will damage British startups.

With confidence I can say that we would have never planted Red Tree without Second Baptist's support,

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They say great data is 95% of the problem in machine learning. We saw first hand at Udacity that this is the case, with the amazing reception from the machine learning community when we open sourced over 250GB of driving data. But, finding interesting data is really hard, and actively holds the industry back from progress. In trying to learn more about this problem I searched far and wide, and cataloged just a sliver of the datasets I found. In the hope that others might find this catalog useful, here's 20 weird and wonderful datasets you could (perhaps) use in machine learning.

Human resources departments rarely, if ever, are thought of as cutting edge when it comes to the use of technology. A closer look, however, shows the implementation of new technologies, including solutions powered by Artificial Intelligence (AI), in almost every aspect of the talent function. According to a recent Towers Watson HR Service Delivery and Technology Survey, HR professionals are overhauling structure to improve quality and efficiency with 33% of the group spending significantly more on technology in the last year. HR's investment in new technology has also spurred the creation of new data sources. Data around employee productivity, wellness, manager effectiveness, and a host of other activities is quickly dwarfing the traditional data set that HR has traditionally been using.

The results of Tuesday's US election shocked many--including pollsters and campaign insiders. As a result, many have begun questioning the data and methods behind predictions, wondering what went wrong. But not everyone got it wrong: An AI tool created by an Indian startup in Mumbai in 2004 has correctly predicted the last three US elections, including this one. By collecting and analyzing 20 million social media data points, MogIA, developed by Sanjiv Rai, has used sentiment to determine political outcomes. And social media has proven to have a powerful impact on candidates' popularity.

Wipro Cited as a Leader in Service Providers for Next-generation Oracle Application Projects by Leading Independent Research and Advisory Firm Business Wire India Wipro Ltd. (NYSE: WIT, BSE: 507685, NSE: WIPRO), a leading global information technology, consulting and business process services company today announced that Wipro has been cited as a "Leader" by technology global research and advisory firm Forrester Research Inc. in its report, 'The Forrester Wave(TM): Services Providers for Next-Generation Oracle Application Projects, Q3 2016'. Forrester evaluated 13 service providers across three categories of current offering, strategy and market presence. Forrester wrote, "Wipro is a proven provider making big investments in the shift to cloud. It has a long track record of delivering Oracle services ... [Wipro] was recognized by Oracle with a co-innovation award at Oracle's Collaborate conference in 2016." According to the Forrester report: "Wipro wants to be the partner of choice for tomorrow's digital businesses; it has invested in its own artificial intelligence tool, [Wipro HOLMES Artificial Intelligence Platform(TM)], and in next-generation Oracle technologies. Wipro has recently started to invest in digital experience and customer journey mapping capabilities, including its acquisition of Designit and associated studios."

With Google, Microsoft and Facebook all pushing artificial intelligence, AI is becoming the next battleground for agencies, perpetually on the hunt for new service lines. AI basically gives machines the ability to think like humans. A simple example: You can have a one-on-one conversation with another person, but AI can talk to 500 people at the same time and make decisions based on real-time data to learn what's going on in each conversation, explained Dave Meeker, vp of Isobar's U.S. operations. In the context of advertising and marketing, AI theoretically means more personalized and interactive consumer experience, including targeted programmatic ad buys, identification of site visitors' decision-making patterns, conversational commerce like bots, as well as smarter search and recommendation engines on websites, according to six agency executives interviewed for this article. At the moment, with the help of AI developed by big tech companies, agencies are able to serve cognitive ads and integrate voice-activated assistants in their campaigns.