Morgan Stanley upgraded Xilinx (NASDAQ: XLNX) from Equalweight to Overweight with a price target of $67.00 (from $46.00). Analyst Joseph Moore thinks machine learning could change the way investors look at the stock. He also anticipates revenue share gains. Moore explained, "A year ago, the focus of some Xilinx bulls was the high strategic value of the company's franchise in the context of a consolidating industry; the stock has modestly underperformed the substantial semiconductor rally since then, as M&A activity has focused on other subsectors. And yet, the fundamental outlook for the company has improved, we think, for 3 reasons: 1) as machine learning continues to evolve, we see the market for'inference' moving away from microprocessors and towards specialty solutions, including Xilinx FPGAs (as well as graphics and other specialty chips); 2) potential for share gains is improving as we have seen the company stretch its lead over Intel/Altera in the two most recent manufacturing nodes; and 3) we generally see the overall growth in FPGAs modestly improving, as base stations fade in importance and new technologies start to penetrate autos, factories and data centers."

Autonomous machines shining lasers at ants -- and spraying water at bewildered cats -- for the amusement of cackling grandchildren. Hobbyists are just getting started with deep-learning technologies that give them cheap, off-the-shelf capabilities that put Ronald Reagan's Star Wars program to shame. In the latest edition of the AI Podcast, NVIDIA engineer Bob Bond and Make: Magazine Executive Editor Mike Senese explain to host Michael Copeland how they've taken the once esoteric technology of deep learning and put it to work on offbeat projects that can be tackled on budgets of a few hundred bucks. "One of the big things that's happening -- and it's happening in real time right now -- is the technology is finally hitting a point where we, as consumers, have access to this type of capability," Senese says.

Palantir CEO Alex Karp Says Going Public Is'A Possibility' Big data is ubiquitous because it can provide valuable insight that is unavailable without it. Analyzing big data sets can pose problems, however. For starters, big data is big, sometimes too big to be handled effectively by commonly used analysis tools. Researchers at MIT's Computer Science and Artificial Intelligence Laboratory and the University of Haifa in Israel have developed a solution to this problem that turns big data into manageable data. Data analysis tools such as low-rank approximation, singular-value decomposition, principal-component analysis, and nonnegative matrix factorization are commonly used to reduce the number of variables in a dataset.

We do enterprise solutions, mobility and cloud," explained Santosh Ahuja, Director of Architecture at Impiger Technologies, in this SYS-CON.tv Featured on-site presentation and ongoing on-demand webcast exposure to a captive audience of industry decision-makers Showcase exhibition during our new extended dedicated expo hours Breakout Session Priority scheduling for Sponsors that have been guaranteed a 35 minute technical session Online targeted advertising in SYS-CON's i-Technology Publications Capitalize on our Comprehensive Marketing efforts leading up to the show with print mailings, e-newsletters and extensive online media coverage Unprecedented Marketing Coverage: Editorial Coverage on ITweetup to over 100,000 plus followers, press releases sent on major wire services to over 500 industry analysts Online targeted advertising in SYS-CON's i-Technology Publications All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, June 6-8, 2017, at the Javits Center in New York City, NY and October 31 - November 2, 2017, Santa Clara Convention Center, CA. Learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation.

'Event[0]' Is a Fresh Take on the AI Story 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.

'Event[0]' Is a Fresh Take on the AI Story 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.

AI is more present in our daily lives than many people realize. The world is on the cusp of an AI revolution. Companies around the world are already using the technology to help do everything from parse medical records to teach cars to drive themselves. At home, digital assistants like Amazon's Alexa, Apple's Siri and Google Now, have put a conversational gloss on the burgeoning tech. In 2017, AI is likely to not only get smarter (natch) but also more humanlike.

What is interesting is how little, year on year, this list changes. Transport investment, skills schemes and relatively fiddly tax incentives feature time and again. I used to be one of those officials: I worked in HM Treasury for three years in the "Productivity Unit". Our job was to study potential investments and problematic regulation to try and spot reforms that would improve the economic output per worker. It is not surprising the Treasury is obsessed by productivity.