Data Harmonization is an approach to Data Quality that is meant to improve the governance and usefulness of data across the enterprise. How does it do that? And how should a company go about implementing a Data Harmonization strategy? To answer these questions, DATAVERSITY spoke with Anil Kaul, co-founder and CEO of Absolutdata. Mr. Kaul was named one of the ten most influential Analytics Leaders in India. He has over two decades of experience in Data Analytics, market research, and management consulting.

This was the title of a very popular book published in 2012, featuring several job interview questions (brain teasers) asked by Google's hiring managers to candidates. They apparently dropped all these questions, as they found out that they were not good indicators of career success. Do you think you are smart enough to work for Google? I had one phone interview with Google long ago, and was rejected right away. The interviewer was just focused on very technical details, and spent all her time arguing about Lasso regression, and was clearly looking for a specialist, dismissing people with a broad range of skills and non-standard approach to solving tech problems.

Although artificial intelligence (AI) has experienced a number of "springs" and "winters" in its roughly 60-year history, it is safe to expect the current AI spring to be both lasting and fertile. Applications that seemed like science fiction a decade ago are becoming science fact at a pace that has surprised even many experts. The stage for the current AI revival was set in 2011 with the televised triumph of the IBM Watson computer system over former Jeopardy! This watershed moment has been followed rapid-fire by a sequence of striking breakthroughs, many involving the machine learning technique known as deep learning. Computer algorithms now beat humans at games of skill, master video games with no prior instruction, 3D-print original paintings in the style of Rembrandt, grade student papers, cook meals, vacuum floors, and drive cars.1 All of this has created considerable uncertainty about our future relationship with machines, the prospect of technological unemployment, and even the very fate of humanity. Regarding the latter topic, Elon Musk has described AI "our biggest existential threat." Stephen Hawking warned that "The development of full artificial intelligence could spell the end of the human race." In his widely discussed book Superintelligence, the philosopher Nick Bostrom discusses the possibility of a kind of technological "singularity" at which point the general cognitive abilities of computers exceed those of humans.2 Discussions of these issues are often muddied by the tacit assumption that, because computers outperform humans at various circumscribed tasks, they will soon be able to "outthink" us more generally. Continual rapid growth in computing power and AI breakthroughs notwithstanding, this premise is far from obvious.

Summary: Someone had to say it. In my opinion R is not the best way to learn data science and not the best way to practice it either. More and more large employers agree. Someone had to say it. I know this will be controversial and I welcome your comments but in my opinion R is not the best way to learn data science and not the best way to practice it either.

On May 11, 1997, a computer showed that it could outclass a human in that most human of pursuits: playing a game. The human was World Chess Champion Garry Kasparov, and the computer was IBM's Deep Blue, which had begun life at Carnegie Mellon University as a system called ChipTest. One of Deep Blue's creators, Murray Campbell, talked to us about the other things computers have learned to do as well as, or better than, humans, and what that means for our future. What follows is an edited version of that conversation. Is it true that you and Deep Blue joined IBM at the same time?

On May 11, 1997, a computer showed that it could outclass a human in that most human of pursuits: playing a game. The human was World Chess Champion Garry Kasparov, and the computer was IBM's Deep Blue, which had begun life at Carnegie Mellon University as a system called ChipTest. One of Deep Blue's creators, Murray Campbell, talked to us about the other things computers have learned to do as well as, or better than, humans, and what that means for our future. What follows is an edited version of that conversation. Is it true that you and Deep Blue joined IBM at the same time? A group of us, including myself, joined IBM from Carnegie-Mellon University in Pittsburgh in 1989, but we didn't come up with the name Deep Blue until about a year later.

AI is one of the buzzwords of the moment in the world of tech, with startups coming at the concept from all angles -- computer vision, machine learning, unstructured data inference and natural language processing being just a handful -- in a wider effort to create more intelligent machines. Now comes a new organization that hopes to find and foster the next wave of AI businesses and products, co-founded by the ex-CEO of Evernote, Phil Libin (pictured above), who has left his role as a managing director at General Catalyst to build it (but he tells me he'll stay on as an advisor). All Turtles, as the new company is called, is not your traditional startup incubator. In an interview with TechCrunch earlier, Libin (whose other co-founders are Jessica Collier (Product Design) and Jon Cifuentes (Research and Operations) described it as "startup studio", more akin to Netflix's push to develop original content than to 500 Startups. It will start out with locations in San Francisco, Tokyo and Paris.

Welcome to the Remark Holdings First Quarter Financial Results Conference Call. Today's conference is being recorded. At this time, I would like to turn the conference over to Becky Herrick of LHA. Thank you all for joining us today for the Remark Holdings first quarter 2017 financial results conference call. On the call today are Chairman and CEO, Shing Tao; and CFO, Doug Osrow. After the prepared remarks, we'll open the call for questions. A webcast replay of today's call will be available at www.remarkholdings.com. Some of the statements made today may be forward-looking statements. These statements involve risks, uncertainties and other factors that could cause actual results to differ materially from those expressed or implied by these forward-looking statements. Any forward-looking statements reflect Remark Holdings current views and Remark Holdings expressly disclaims any obligation to update or revise any forward-looking statements after the date hereof. This disclaimer is only a summary of Remark Holdings' statutory forward-looking statements disclaimer which is included in its filings with the SEC.

There are big discussions in the automotive industry right now, about whether autonomous electric vehicles – yes, the ones that can drive themselves – will come to dominate transportation, personal and public, in the next few years. But it is completely foreseeable, in my opinion. The future of transportation is the electric vehicle (EV) because of sustainability; it can be powered by wind and sun, requiring only 1/3 of the energy of a vehicle with a combustion engine. Looking ahead to 2020, there will be many more EVs. Looking further to 2030, we will see major advancements in the area of autonomous driving.

The question of whether a god exists is heating up in the 21st century. In 2014, the proportion of the US who didn't believe in God was 33 per cent while in the UK it was 39 per cent. Despite this growing disbelief in a higher being, in a new article for The Conversation, Robert Nelson, a Professor of Public Policy at the University of Maryland explores why he believes that God exists. The question of whether a god exists is heating up in the 21st century. In 2014, the proportion of the UK who said they didn't believe in God was 39 per cent, while it was 33 per cent of people in the US (stock image) In 1960 the Princeton physicist – and subsequent Nobel Prize winner – Eugene Wigner raised a fundamental question: Why did the natural world always – so far as we know – obey laws of mathematics?