As the wide range of technologies that fall under the banner of "Big Data" begin to mature and become ubiquitous, the next stage of development of the analytics stack is machine learning. Beyond its role in making better sense of data, however, machine learning has an increasingly critical role to play in application security, particularly in areas like financial services. With increased security focus turning toward one of the prime sources for exploitation--commercial and homegrown code--the tooling around application security is getting smarter and bringing the rest of the monitoring stack up to speed through automation. For data-driven organizations, which include almost any Fortune 500 company, maintaining the security of their critical applications is equivalent to locking down some of their most valuable assets. With a wide set of applications spanning departments and even different clusters or infrastructure, this is no small task.

Intelligent machines won't be ruling the world anytime soon – but what happens when they turn you down for a loan, crash your car or discriminate against you because of your race or gender? On one level, the answer is simple: "It depends," says Bryant Walker Smith, a law professor at the University of South Carolina who specializes in the issues raised by autonomous vehicles. But that opens the door to a far more complex legal debate. "It seems to me that'My Robot Did It' is not an excuse," says Oren Etzioni, CEO of the Seattle-based Allen Institute for Artificial Intelligence, or AI2. The rapidly rising challenges that face America's legal system and policymakers were the focus of today's first-ever White House public workshop on artificial intelligence, presented at the University of Washington School of Law. For a full afternoon, Smith, Etzioni and other experts debated the options in an auditorium that was filled to capacity.

A partnership between the University of Michigan and IBM could spark the next wave of artificial intelligence (AI) interfaces -- and the test bed for the work will be an academic adviser for students driven by cognitive computing. The 4.5 million, multiyear partnership, dubbed Project Sapphire, combines IBM's resources with scientists and students at the University of Michigan's Artificial Intelligence Lab, according to a news release from the University of Michigan. Scientists will feed this new AI large volumes of recorded human interactions between students and academic advisers to give the system a conversational edge, allowing it to improve upon the scripted responses of previous AI. "Natural conversations bring in so many different aspects of human intelligence -- knowledge, context, goals and emotion, for instance. In many ways, to build a versatile conversational system is a grand challenge for artificial intelligence," said Satinder Singh Baveja, professor of computer science and engineering and director of U-M's AI Lab, in the news release.

Computer scientists have been captivated by the potential of artificial intelligence to create human like experiences with computers for decades. Although we are not at the point of true human intelligence, we have seen great advances in vision, speech, language understanding and knowledge recall that will produce better human computer experiences. This started with investments in speech recognition and natural language processing (NLP) for a variety of uses. Microsoft demonstrated this technology 15 years ago at CES and since then has continued to drive these innovations into products. Having computers mimic human behavior at scale has augmented our lives in useful ways.

China will speed up the development of its artificial intelligence (AI) sector and create a market worth more than 100 billion yuan (USD 15.26 billion) over the next three years, the National Development and Reform Commission said in a statement. By 2018, China shall build platforms for fundamental AI resources and innovation and make breakthroughs on basic core technology, the three-year implementation programme for "Internet Plus" artificial intelligence said. Under the plan, China will cultivate and develop emerging artificial intelligence industries, promote innovation in intelligent products and enhance the intelligence level of terminal products. The programme will involve key projects such as intelligent home appliances, smart automobiles, intelligent unmanned systems, intelligent wearable devices and robots. China will also offer some guarantee measures involving financial support, intellectual property protection, talents and international cooperation, state-run China Daily reported.

An article explores how Nvidia Corp. microchips, the kind that are used in video games and by social media networks for photo tagging, are being applied to medicine. They are being used to add machine learning to medical imaging. The idea is to use the technology to spot conditions such as cancer and Alzheimer's disease earlier and faster. But one potential consequence of advancements in this area is reduced dependence on radiologists. Luminex has raised its offer for Nanosphere to obtain its molecular diagnostics technology from 83 million to more than 100 million.

I gave a talk on Design Thinking for Data Scientists at the O'Reilly Strata Conference in February 2015. The talk was pretty much orthogonal to every other talk at the conference. But it was well received, so I thought I'd share the transcript with you (or your can watch the video). I'd be delighted to hear your thoughts and experiences around this topic of increasing the business impact of Data Scientists working in industry. This talk is primarily directed towards Data Scientists, especially early career Data Scientists, but its also highly relevant to those who manage Data Scientists. I'm using the term Data Scientist in a very broad sense, to mean anyone who is using data plus statistics plus programming to do something new, something that's never been done before in their organization. I'm going to talk about how and why Intuit is transforming it's Data Scientists into Design Thinking leaders.

As the third industrial revolution - led by software - continues to gather steam, world leaders are predicting our entrance into the fourth industrial revolution. Can you guess what is leading it? We all dreamed of the day when robots would effortlessly takeover our mundane chores like doing the dishes, but the truth is that AI can already do more than that. AI is already driving cars, making art, beating humans at Go...and will soon take over your job! Forget science fiction, AI is already here and it is so close to getting so much bigger that governments are starting to prepare for this Tsunami. The White House recently released a report that highlighted staggering numbers for the job market due to AI.

I asked Siri whether she believes in God. "I believe in the separation of spirit and silicon," she demurred. I asked the chatbot ELIZA the same question -- her thing is she's a therapist, so she'd rather focus on what I believe. I asked her if she was religious; she asked if I'd prefer if she weren't. "We aren't really talking about me, are we," she replied.

This IR Magazine interview explores how artificial intelligence, including machine learning and natural language processing, is affecting investor relations. Darrell Heaps, founder and CEO of Q4, a market intelligence and investor engagement firm based in Toronto, is joined by Adam Frederick, Q4's senior vice president, intelligence. Frederick also covered the topic in a recent webinar with Matt Danziger, director of IR at LinkedIn: http://www.irmagazine.com/events/ir-m... Look for part two of the video interview, in which Heaps and Frederick discuss the consumerization of IR teamwork.