See the forest, see the trees. Here lies the challenge in both performing and presenting an analysis. As data scientists, analysts, and machine learning engineers faced with fulfilling business objectives, we find ourselves bridging the gap between The Two Cultures: sciences and humanities. After spending countless hours at the terminal devising a creative and elegant solution to a difficult problem, the insights and business applications are obvious in our minds. But how do you distill them into something you can communicate? Presenting my work is one of the surprising challenges I faced in my recent transition from academia to life as a data analyst at a market research and strategy firm.

During the recent Consumer Goods Forum global summit here in Cape Town, I had the opportunity to briefly chat with Vivienne about some of the issues confronting the digital disruption of this industry sector. [The original transcript has been edited for clarity and space.] Named one of 10 Women to Watch in Tech in 2013 by Inc. Magazine, Vivienne Ming is a theoretical neuroscientist, technologist and entrepreneur. She co-founded Socos, where machine learning and cognitive neuroscience combine to maximize students' life outcomes. Vivienne is a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, where she pursues her research in neuroprosthetics. In her free time, Vivienne has developed a predictive model of diabetes to better manage the glucose levels of her diabetic son and systems to predict manic episodes in bipolar suffers. She sits on the boards of StartOut, The Palm Center, Emozia, and the Bay Area Rainbow Daycamp, and is an advisor to Credit Suisse, Cornerstone Capital, and BayesImpact. Dr. Ming also speaks frequently on issues of LGBT inclusion and gender in technology. Every once in a while I have the opportunity to discuss wide-ranging topics with an intellect that stimulates, is passionate and really cares about the bigger picture. Those opportunities are more rare than one would think. Although set in a somewhat unexpected venue (the elite innards of consumer capitalism) her observations on the inescapable disruption that the new wave of modern technologies are prescient and thoughtful. Ed: In a continent where there is a large focus on putting people to work, how do you see the challenges and disruptions resulting from AI, robotics, IoT, VR and other technologies playing out? These technologies, as did other disruptive technologies before them, tend to replace human workers with machine processes. Vivienne: There is almost no domain in which artificial intelligence (AI), machine learning and automation will not have a profound and positive impact. Medicine, farming, transportation, etc. will all benefit. There will be a huge impact on human potential, and human work will change. I think this is inevitable, that we are well on the way to this AI-enabled future.

By Max Chafkin Y Combinator, the startup accelerator and investment firm that helped produce Airbnb, Dropbox, and Instacart, is embarking on a creation project arguably more ambitious than any company. "We want to build cities," wrote Y Combinator partner Adora Cheung and President Sam Altman in an announcement slated for release Monday. YC Research, Y Combinator's nonprofit arm, plans to solicit proposals for research into new construction methods, power sources, driverless cars, even notions of zoning and property rights. Among other things, the project aims to develop ways to reduce housing expenses by 90 percent and to develop a city code of laws simple enough to fit on 100 pages of text. Eventually the plan is to actually produce a prototype city.

Artificial Intelligence (AI) is gathering pace as one of the biggest ICT trends of our time – and the topic of "robot journalism" provides important insight on how AI is being applied to industry. How is natural language generation (NLG) being used to explain big data in narrative form that broader audiences can easily understand? What insights are being found by machines producing 2,000 articles per second? How are some of the world's biggest media agencies currently using vendors that provide these solutions to build their reach, engagement, and businesses? Will "robots" (or automated content) soon render journalists obsolete?

There are some things even Stephen Hawking can't figure out. On "Larry King Now," the world-famous astrophysicist told Larry King that he wonders why anything -- and everything -- even exists in the first place. "Why do the universe and all the laws of nature exist? "In one sense, they are, because otherwise we wouldn't be here to ask the question. But is there a deeper reason?" That's a little different from the answer Hawking gave in 2012 when New Scientist asked him what he thought about most during the day. Hawking said he's learned a lot about women since, and even asked King about his eight marriages to seven women. "Is that the triumph of hope over experience?" "You make a good point, Stephen," King said, noting his most recent marriage had lasted 19 years. "I think the answer is yes." Hawking was interviewed from the Canary Islands, where he was being honored at the Starmus Festival. During the interview, Hawking also warned that mankind could eventually be threatened by artificial intelligence. "I don't think that advances in artificial intelligence will necessarily be benign," he said. "Once machines reach the critical stage of being able to evolve themselves, we cannot predict whether their goals will be the same as ours." During an interview with King in 2010, Hawking said that two of mankind's biggest dangers were greed and stupidity. Not much has changed in the intervening years. "We certainly have not become less greedy or less stupid," Hawking said. "Six years ago, I was warning about pollution and overcrowding.

Tony Jebara is a Professor of Computer Science at Columbia University and Director of Machine Learning Research at Netflix. His research intersects computer science and statistics to develop new frameworks for learning from data with applications in social networks, spatio-temporal data, vision and text. At the Deep Learning Summit in Boston, on April 2016, Tony presented'Double-Cover Inference in Deep Belief Networks'. I caught up with him to hear more about his work at Netflix and his thoughts on the recent advancements in deep learning. Tell us more about your work as Director of Machine Learning Research at Netflix.

Y Combinator, the startup accelerator and investment firm that helped produce Airbnb, Dropbox, and Instacart, is embarking on a creation project arguably more ambitious than any company. "We want to build cities," wrote Y Combinator partner Adora Cheung and President Sam Altman in an announcement slated for release Monday. YC Research, Y Combinator's nonprofit arm, plans to solicit proposals for research into new construction methods, power sources, driverless cars, even notions of zoning and property rights. Among other things, the project aims to develop ways to reduce housing expenses by 90 percent and to develop a city code of laws simple enough to fit on 100 pages of text. Eventually the plan is to actually produce a prototype city.

Artificial Intelligence has touched each and every sector. We all know about Facebook suggesting friends or Siri managing our calendars. Even the stocks are traded by computers. There are cars which can park on their own. From education to military to even manufacturing there is hardly a field where artificial intelligence does not pay a role.

When American novelist David Foster Wallace delivered the commencement address at Kenyon College in 2005, he urged the graduating class to "exercise some control over how and what you think." If you don't at least try to regulate your thoughts and behaviors, Wallace cautioned, you will go through life "dead, unconscious, a slave to your head." Wallace himself long suffered with unwanted negative thoughts and crippling self-doubt--and took his own life three years after that speech. But can our mind become a "terrible master," as Wallace described? Kessler, the former commissioner of the U.S. Food and Drug Administration, has considered that question for the past two decades, studying how substances such as food, alcohol and tobacco can hijack our brain chemistry and compel us to act against our own best intentions--bingeing on brownies, booze or cigarettes.

Want to learn to talk like you're from Kansas? It's an app that uses machine learning to teach the pronunciation of a Midwestern accent. "We chose a Midwestern accent because we talked to a lot of speech therapists and they said this is the most commonly understood accent that people should learn," Elsa founder Vu Van told VentureBeat. Using machine learning, Van plans to extend Elsa to other accents. The same app that Van used to reduce her native Vietnamese accent could help an American moving to Vietnam learn a local Vietnamese accent.