Intel Corporation INTC is gearing up to become a major provider of solutions for the Artificial Intelligence (AI) market, which is anticipated to be worth $5.05 billion by 2020 as per MarketsAndMarkets.com. The company recently announced a plethora of products, technologies and investments, which will augment its presence in the AI market. Additionally, Intel expects the next generation Xeon Phi processors to deliver up to four times better performance than the previous generation for deep learning. Code-named Knights Mill, the co-processor will be available in 2017. Acquisitions to Expand Footprint Apart from Nervana, the Movidius acquisition also expands Intel's AI product portfolio.

The difficulty in dealing with insider threats is that it hinges on detecting anomalous user behavior instead of finding and patching vulnerabilities in software. But unfortunately, drawing the line between safe and malicious behavior is not an exact science, and traditional approaches such as setting static rules and alerts either churn out too many false positives and impede organisational workflows, or leave too many holes to be exploited by hackers.

Last tuesday, at the annual meeting of the French Economic Association, I was having lunch with Alfred, and while we were chatting about modeling issues (econometric models against machine learning prediction), he asked me what boosting was. Since I could not be very specific, we've been looking at wikipedia webpage. One should admit that it is not very informative. But at least, there is the idea that'weak learners' can be used to provide a good predictor. Now, to be honest, I guess I understand the concept. But I still can't reproduce what I got with standard'boosting' packages.

The Internet media is trending now with numerous mentions of "big data", "machine learning" and "artificial intelligence" all together destined to revolutionize pharmaceutical and biotech industries and the way drugs are discovered. These new technologies are believed to make drug discovery cheaper, faster, and more productive. First, let's review briefly some of the basic concepts in the heart of new technologies. The term "big data" by itself is more of a marketing nature. It describes an abstract concept of having large volumes of data obtained from various channels in multiple formats, which needs to be arranged in such a way, that it can be possible to quickly access, search, update, and analyze it to output useful information.

Intel CEO Brian Krzanich speaks at the company's AI day. We all know processors are the brains of a computer. But the booming field of artificial intelligence takes the metaphor to a whole new level -- and Intel wants to make sure it's propelling the change, not being left behind. Despite Intel's financial might and technological prowess, the company stumbled with the last big overhaul of the computing industry, the arrival of smartphones, tablets and mobile devices. The company's high-profile "Intel Inside" publicity campaign failed to extend beyond its PC stronghold.

Last week I mentioned to one of my U.S.-based colleagues that I would be out of office for three days at the Irish National Digital Week (NDW16), taking the opportunity because the event was being held in Skibbereen, just a few kilometres down the road from my home office. He asked, "Surely an event of that type would be held in Dublin?" And I replied, "Well there's a story here that needs to be told; one that will have profound implications for business in Ireland and probably internationally". Skibbereen is a small market town in the South West of Ireland. The population is approximately 2000, although there's perhaps several times that number in the immediate hinterland.

Robots will need to teach themselves. The common, and recurring, view of the latest breakthroughs in artificial intelligence research is that sentient and intelligent machines are just on the horizon. Machines understand verbal commands, distinguish pictures, drive cars and play games better than we do. How much longer can it be before they walk among us? The new White House report on artificial intelligence takes an appropriately skeptical view of that dream.

A country's dexterity with artificial intelligence technology might be the next strong source of national pride and international power. Knowing it would lay the foundation for the future of medicine, IBM captured the world's imagination in 2011 with Watson, a supercomputer that not only won Jeopardy!, but beat trivia superstar Ken Jennings in the process. The novel cognitive computing technology was quickly adapted to "read" the thousands of medical research papers published weekly in order to diagnose cancer patients more accurately than human doctors seemingly could. It's a banner technology for IBM, a company that remains no slouch in its 105 years of operation Now five years after Watson's debut, Japanese researchers at Kyoto University and Fujitsu are collaborating to build their own computing technology that's fairly characterized as a response to Watson. Skipping the game shows and going straight to medical applications, the Japanese system aims to close the gap in understanding how our genes determine our health by accounting for a patient's genetic code in its computer-generated diagnoses.

Hinton was only technically an intern at Google. He arrived that summer for what he describes as a trial run -- he was hesitant to leave Toronto, where he has lived with his family for most of the past quarter-century -- and the short-term stint didn't have any other obvious job title. But in the manner of an intern, Hinton still seems chuffed to find himself quite where he is. On a recent morning at Google's headquarters in Mountain View, the first thing he did was enumerate the riches of one of many well-stocked "micro-kitchens." His job is to rove among one of the company's most highly valued teams, seeding the work underway with ideas.