Rocker Chris Cornell, who gained fame as the lead singer of the bands Soundgarden and later Audioslave, has died at age 52, according to his representative. Cornell, who had been on tour, died Wednesday night in Detroit, Brian Bumbery said in a statement to The Associated Press. Bumbery called the death "sudden and unexpected" and said his wife and family were shocked by it. The statement said the family would be working closely with the medical examiner to determine the cause and asked for privacy. With his powerful, nearly four-octave vocal range, Cornell was one of the leading voices of the 1990s grunge movement with Soundgarden, which emerged as one of the biggest bands out of Seattle's emerging music scene, joining the likes of Nirvana, Pearl Jam and Alice in Chains.

When Tesla bought a decommissioned car factory in Fremont, California, Elon Musk transformed the old-fashioned, unionized plant into a much-vaunted "factory of the future", where giant robots named after X-Men shape and fold sheets of metal inside a gleaming white mecca of advanced manufacturing. The appetite for Musk's electric cars, and his promise to disrupt the carbon-reliant automobile industry, has helped Tesla's value exceed that of both Ford and, briefly, General Motors (GM). But some of the human workers who share the factory with their robotic counterparts complain of grueling work pressure they attribute to Musk's aggressive production goals, and sometimes life-changing injuries. Ambulances have been called more than 100 times since 2014 for workers experiencing fainting spells, dizziness, seizures, abnormal breathing and chest pains, according to incident reports obtained by the Guardian. Hundreds more were called for injuries and other medical issues. In a phone interview about the conditions at the factory, which employs some 10,000 workers, the Tesla CEO conceded his workers had been "having a hard time, working long hours, and on hard jobs", but said he cared deeply about their health and wellbeing.

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.

Intel, Salesforce, eBay, Sony, SAP, McKinsey & Company, Zalando and Cogitai are joining the Partnership on AI, a collection of companies and non-profits that have committed to sharing best practices and communicating openly about the benefits and risks of artificial intelligence research. The new members will be working alongside existing partners that include Facebook, Amazon, Google, IBM, Microsoft and Apple. Collectively, the partners will be hosting a series of AI Grand Challenges to incentivize researchers to contribute to key roadblocks in the field and to address some of the social and societal ramifications of artificial intelligence research. The group is also announcing a best paper award for the greatest contribution to "AI, People, and Society," to aid in addressing a similar goal. In addition to the paper awards and challenges, the Partnership on AI will also be establishing topic and sector-specific work groups to make good on the group's promise to generate a list of best practices for researchers. The success of these projects depends on being able to build a community around the partnership, independent from larger partners.

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.