Let me also mention some of the advances in my main area of expertise: Recommender Systems. Of course, Deep Learning has also impacted this area. While I would still not recommend DL as the default approach to recommender systems, it is interesting to see how it is already being used in practice, and in large scale, by products like Youtube. That said, there has been engaging research in the area that is not related to Deep Learning. The best paper award in this year's ACM Recsys went to "Local Item-Item Models For Top-N Recommendation," an interesting extension to Sparse Linear Methods (i.e.

The ability of artificial intelligence to look for patterns in vast volumes of data - including large collections of unstructured data, which are commonly found in the healthcare sector - is presenting new potential ways for bolstering the security of patient information, says AI expert Navin Budhiraja of outsourcing vendor Infosys. "The nature [of healthcare data], how rapidly new [challenges] are appearing and how large and complex those systems are becoming, are making the security problems very, very hard," he says in an interview with Information Security Media Group. "So, how do you look at very large amounts of data - not necessarily knowing what you're looking for - and still actually try to find interesting patterns in there around who's accessing what; is their behavior expected or anomalous, and so on? I think the traditional ways of doing security, like where you have an anti-virus system or a particular way your firewall is configured because those are the best practice, are no longer applicable because of this complex IT environment," he says. "And those are exactly the kinds of challenges AI is very good at."

One of the best parts of writing the Afternoon Edition each day is that I get to explore all kinds of interesting topics. Two of those recent topics continue to be all over the news, and they are the issues of robots and automation, and artificial intelligence and the "Singularity." These topics do materially affect markets, although their effect may not be as acute as, say, a monthly employment report. And speaking of which, we got a new monthly employment report this morning, as February saw 235,000 new non-farm payroll jobs created. That's good economic news; however, I wonder how many more jobs would have been created if there weren't as many advancements in the field of automation.

Sign up for our newsletter to not miss out on tomorrow's game-changers for your industry. At Mobile World Congress this year, I got to moderate the most interesting panel of the whole show. Okay, I may be a bit biased as I created the idea of the panel The unreal reality: what is real when AI, VR and AR are mainstream? We kept circling back to human kind's seemingly inherent distrust of Artificial Intelligence (AI). But I think my colleague Manoj P M had a great point: "People think AI will be a replacement for humans, but actually it won't," he said.

Genevera I. Allen (left) is a professor in the Departments of Statistics, and the Electrical and Computer Engineering, at Rice University. Corinne Cath (right) is a doctoral student at the Alan Turing Institute, the national institute for data science in UK. Below are extracts of recent interviews that are most relevant to our audience. Links to full interviews are provided. Genevera, what do you think of the shift from "Statistics" to "Statistical Learning and Data Science" in the statistics community (The "Data vs Math" Question?)

In an economy where value is generated by digital efficiency, I believe that every organization should strive for digital flow. For an introduction to digital flow, see Digital Transformation Isn't A Goal. It's A Journey.There are three central forces of flow: Design Thinking, Platform Thinking, and Open Thinking. This article focuses on Design Thinking. Digital technology is complex, but users should never know it.

The Drum caught up with Gareth Mackown, partner and European mobile leader at IBM Global Business Services, at the Mobile World Congress this week in Barcelona to ask him about how mobile solutions are becoming more vital for not only an enterprise's customers, but also employees. "Today, organizations are really being defined by the experiences they create," Mackown said in an interview. "Often, you think of that in terms of customers, but more and more we're seeing employee experience being a really defining factor." IBM partnered with Apple to transform employee experiences through mobility, he said, and it's just getting started. Internet of Things (IoT) technology, cognitive computing and analytics will make those mobile solutions "even more critical" for people working in all kinds of different fields.

Most press coverage of AWS's recent outage has explained the event as having been caused by a "typo" that one of its engineers made when updating a billing subsystem. The'typo' spin on this story may be the media's way of dramatizing the blunder and making it easy to explain. Certainly, Amazon's own post-mortem noted that "one of the inputs to the command was entered incorrectly {read'typo'} and a larger set of servers was removed than intended." I believe that Amazon is trying to shift the blame from how they have designed, protected and audited their systems – a systemic process that affects all of their operations – and have instead chosen to portray this as a one-off event that happened just within one small subsystem bcause someone didn't follow the approved playbook. Google's advice to make it hard for errors to happen follows the practice of all leading safety organizations.

Readers of The Right Stuff long knew that founder "Mike Enoch" had two main interests: technology and white supremacy. Posts on the neo-Nazi site have included discussion of "a new blogging platform built on node.js," while other less techie content has alluded to the "chimpout" in Ferguson, putting Jews in ovens, and Trump's "top-tier troll" of Jews on Holocaust Remembrance Day. In January, Enoch was outed as Mike Peinovich, a Manhattan-based software engineer. His unmasking highlighted a lingering question about the racist far-right movement that rose to prominence with Donald Trump's election: What support might the so-called alt-right have among techies? Ever since I began investigating the extremist groups lining up behind Trump last spring, several of their leaders have made big claims to me about an alt-right following in Silicon Valley and across the broader tech industry. "The average alt-right-ist is probably a 28-year old tech-savvy guy working in IT," white nationalist Richard Spencer insisted when I interviewed him a few weeks before the election.

Dr. Ayanna Howard (1972 –) has some impressive credentials. She is a noted expert in the area of Artificial Intelligence. She is often referred to as an "old school Blerd" (Black Nerd). Her motivation to pursue a career in the sciences was fueled by watching TV shows such as, The Bionic Woman, Star Trek, and Wonder Woman" as a child. Howard has worked as a roboticist and Motorola Foundation Professor at Georgia Tech's Institute for Robotics and Intelligent Machines.