A new law in Illinois will regulate the use of artificial intelligence in job interviews. The Artificial Intelligence Video Interview Act, House Bill 2557, requires companies to notify the applicant when the system is being used, explain how the AI works, get permission from the applicant, limit distribution of the video to people involved with the process and to destroy the video after 30 days. Matthew Jedreski, counsel at Davis Wright Tremaine LLP in Seattle, is a litigator and employment attorney who updates clients on local and state employment laws. Jedreski said AI video interviews apply psychometrics, which is the science of measuring attitude and personality traits. "It's reading data and then analyzing it to determine whether it can draw conclusions about the person being interviewed," Jedreski said.

Game theory is one of the most relevant aspects in modern multi-agent artificial intelligent(AI) systems. To some extent, the recent evolution of AI has triggered a renaissance in the field of game theory fostering innovation across all sorts of new areas. One of those areas is the field of asymmetric games that describe settings in which different players can follow different strategies. Last year, Alphabet's subsidiary DeepMind published a super innovative way to tackle asymmetric game problems. DeepMind's breakthrough can have profound implications in modern multi-agent, AI systems that are often modeled as asymmetric games.

Maria Bartiromo has been covering business news for 30 years, and she's got her eye on the next big wave: artificial intelligence. The Fox Business Network anchor, who recently re-signed with the network for a multiyear deal, is releasing an hour-long investigative documentary about artificial intelligence. The segment, which has been in the works for a year now, includes interviews with chief executive officers of major companies including IBM IBM, -0.76% and Ford. Fox News parent company Fox Corp FOXA, 0.72% was previously owned by MarketWatch parent News Corp NWS, -0.21%. Artificial intelligence isn't just making demands to Siri on Apple's iPhones, AAPL, -1.46% or telling your Google GOOG, -0.71% email inbox to identify spam.

Asked what is the biggest misconception about AI, Yoshua Bengio answered without hesitation "AI is not magic." Winner of the 2018 Turing Award (with the other "fathers of the deep learning revolution," Geoffrey Hinton and Yann LeCun), Bengio spoke at the EmTech MIT event about the "amazing progress in AI" while stressing the importance of understanding its current limitations and recognizing that "we are still very far from human-level AI in many ways." Deep learning has moved us a step closer to human-level AI by allowing machines to acquire intuitive knowledge, according to Bengio. Classical AI was missing this "learning component," and deep learning develops intuitive knowledge "by acquiring that knowledge from data, from interacting with the environment, from learning. That's why current AI is working so much better than the old AI."

Last month data scientists, analysts, executives, engineers, developers, and AI researchers from a wide range of industries flew in the city of seven hills, San Francisco, California. Each one of over 1000 attendees was super pumped to share and learn emerging trends that are transforming data and businesses. I was one of them and I would like to share some key takeaways with the data science community around the globe. In my opinion, at Strata Data Conferences one could see a perfect intersection of cutting-edge science and evolving business models. The conference featured more than 300 speakers, 10 keynotes, 10 tutorials, and 150 technical sessions.

Asked what is the biggest misconception about AI, Yoshua Bengio answered without hesitation "AI is not magic." Winner of the 2018 Turing Award (with the other "fathers of the deep learning revolution," Geoffrey Hinton and Yann LeCun), Bengio spoke at the EmTech MIT event about the "amazing progress in AI" while stressing the importance of understanding its current limitations and recognizing that "we are still very far from human-level AI in many ways." Deep learning has moved us a step closer to human-level AI by allowing machines to acquire intuitive knowledge, according to Bengio. Classical AI was missing this "learning component," and deep learning develops intuitive knowledge "by acquiring that knowledge from data, from interacting with the environment, from learning. That's why current AI is working so much better than the old AI."

I recently caught up with Terry Deem, Product Marketing Manager for Data Science, Machine Learning and Intel Distribution for Python, and David Liu, Software Technical Consultant Engineer for the Intel Distribution for Python*, both from Intel, to discuss the Intel Distribution for Python (IDP): targeted classes of developers, use with commonly used Python packages for data science, benchmark comparisons, the solution's use in scientific computing, and a look to the future with respect to IPD. This Q&A is a follow-up to a previous sponsored post, "Supercharge Data Science Applications with the Intel Distribution for Python." Terry specializes in developer tools and the developer community. Terry has covered a wide variety of tools for Intel from the highly popular XDK to the industry-standard Media Server Studio. He currently covers Intel's machine learning tool such as Intel Data Analytics Acceleration Library (Intel DAAL), Intel Math Kernel Library for Deep Neural Networks (Intel MKL-DNN) and Intel Distribution for Python.

When I left a "regular" job some time ago to become an entrepreneur and adviser to multiple companies, a senior leader in the company observed encouragingly: "Instead of one company-many employees, work is moving to one employee-many companies. You are going to be a part of this future of work." As if to prove his point, the very next day I settled down at my "hot desk" in the spanking new WeWork that had opened in my city and contributed my bit to its ever-expanding valuation. Coworking spaces are mushrooming all around us in every city of the world. JLL estimates that coworking space in India rose three-fold to 3.4 million sq.

The human brain is a funny thing. Certain memories can stick with us forever: the birth of a child, a car crash, an election day. But we only store some details--the color of the hospital delivery room or the smell of the polling station--while others fade, such as the face of the nurse when that child was born, or what we were wearing during that accident. For Google CEO Sundar Pichai, the day he watched AI rise out of a lab is one he'll remember forever. "This was 2012, in a room with a small team, and there were just a few of us," he tells me. An engineer named Jeff Dean, a legendary programmer at Google who helped build its search engine, had been working on a new project and wanted Pichai to have a look. "Anytime Jeff wants to update you on something, you just get excited by it," he says. Pichai doesn't recall exactly which building he was in when Dean presented his work, though odd details of that day have stuck with him. He remembers standing, rather than sitting, and someone joking about an HR snafu that had designated the newly hired Geoffrey Hinton--the "Father of Deep Learning," an AI researcher for four decades, and, later, a Turing Award winner--as an intern. The future CEO of Google was an SVP at the time, running Chrome and Apps, and he hadn't been thinking about AI.

Today's artificial intelligence systems, including the artificial neural networks broadly inspired by the neurons and connections of the nervous system, perform wonderfully at tasks with known constraints. They also tend to require a lot of computational power and vast quantities of training data. That all serves to make them great at playing chess or Go, at detecting if there's a car in an image, at differentiating between depictions of cats and dogs. "But they are rather pathetic at composing music or writing short stories," said Konrad Kording, a computational neuroscientist at the University of Pennsylvania. "They have great trouble reasoning meaningfully in the world."