When I entered Stanford, I was considering becoming a doctor or neuroscientist. I really enjoyed the sciences in high school, but had never written a line of code. I took my first Computer Science course as a freshman without plans to pursue it further, but by the end of freshman year I wanted to major in it. I was less sure about a career in Computer Science though. I questioned if I would be good enough for the tech industry, or even like working in it. My first software engineering internship at Google after sophomore year answered my doubts.

This is not the first time Forrester has made an attention-grabbing prediction about technology leading to the disappearance of jobs. It also said that the same would happen in the business-to-business sales arena, and that current virtual assistant technology spelled the beginning of the end of those jobs as well. How should the retail industry feel about all this? Retail has been pretty progressive thus far in testing artificial intelligence and machine learning technologies in both virtual assistant form and physical robot form. While there may be some concern about what happens as these technologies are perfected and become affordable enough to be deployed throughout the retail ecosystem, the retail industry for now seems fairly enthused about the ways in which these technologies can help to better serve customers and make stores and operations more efficient.

Enter Microsoft Women Health Risk Assessment competition, develop machine learning solutions to accurately categorize young women for their particular health risk. Enter now - submissions due Sep 30. Microsoft is awarding up to 5,000 in cash prizes for the Women's Health Risk Assessment competition. They are calling for optimized machine learning solutions that allow a young woman (age 15-30 years old) to be accurately categorized for their particular health risk. Based on the category a patient falls within, healthcare providers can offer appropriate education and training programs to help reduce the patient's reproductive health risks.

Video Interview With Deep Learning Expert Honglak Lee Honglak Lee is Assistant Professor of Computer Science & Engineering at the University of Michigan. He received his Ph.D. from Computer Science Department at Stanford University in 2010, advised by Prof. Andrew Ng. His research interests span deep learning, unsupervised, semi-supervised, and supervised learning, transfer learning, graphical models, and optimization. He also works on application problems in computer vision, audio recognition, robot perception, and text processing. At the 2016 Deep Learning Summit in Boston, Honglak shared expertise on Deep Learning With Disentangled Representations.

D&S year 3 is underway, and we're seeking a Research Analyst for our "Reimagining Accountability" project (9/22 deadline), plus a Program Administrator (9/27 deadline). Data, Tech, Learning The Enabling Connected Learning initiative has been exploring student data collection/analysis and technological development, digging into the hype and fear around tech in education, the tangled issues of privacy, equity, and efficacy. Today we're sharing some of what we've learned so far, a bundle of primers -- The conversation around student data and "EdTech" can be contentious and complicated. We hope that the materials we're sharing can help the work of other researchers and educators tackling these issues. Why women are asking a major art and technology festival to #KissMyArs "Institutions like Ars Electronica have a tremendous opportunity to set a global example by highlighting diverse voices which run counter to the mainstream, and to open public dialogue around the problems, benefits, and tradeoffs new technology is bringing."

The field of Computer Vision has undergone such a drastic change during the course of my PhD that it's almost hard to believe. In 2011 when I entered, Computer Vision was its own area with its own problems. It was buzzing with activity, there were people working on object detection, scene classification, attribute classification, action classification, pose estimation, etc, etc. The feeling was that we were going to have all of these systems in all of these different areas that we solve one by one and then we plug it together somehow and produce all these intermediates that we pass on elsewhere. I spent a lot of time thinking about what "solved" Computer Vision would look like - we'd extract everything out of the image and pass it on to some other people who worked on planning, or something like that.

Artificial intelligence will play a big role in the future of U.S. strategy in cyberspace, according to National Security Agency Director Adm. Michael Rogers, who told Congress Tuesday that relying primarily on human intelligence "is a losing strategy." "[We're] very much interested in artificial intelligence, machine learning, how we can do cyber at scale [and] at speed," Rogers testified before the Senate Armed Services Committee Tuesday. "Because if we're just going to take this largely human capital approach to doing business, that is a losing strategy." "It will be both incredibly resource intensive, and it will be very slow," Rogers added. "That is a big area of focus for us."

Bots are software powered by artificial intelligence that can perform simple tasks. Bookings by bots are outstripping the growth of the early app economy, according to a Citigroup research note reported by Bloomberg. Bots, short for chatbots, are software applications that use artificial intelligence to do simple tasks: answer a question, write an email or book travel. Earlier this year, Facebook CEO Mark Zuckerberg said the company's messaging service, Messenger, would introduce and promote other company's bots for roles like customer service. Citigroup analyst Mark May compared the growth rate of Apple's App Store in its first six months to the same early period for bot platforms on Facebook Messenger.

When Bob Lord announced he was leaving AOL in November last year, most people knew he was going to end up landing a big new role -- not least because he told The Wall Street Journal he wanted to run a public company or a company about to IPO. Lord spent more than a decade at ad agencies, ending up as global CEO at Publicis Groupe's digital technology division, presiding over almost 8,000 employees and 1.8 billion in revenue. In 2013, he left agency land to join AOL as its president, helping to grow revenue from 1.5 billion to more than 3 billion. Verizon, one of AOL's large clients, became so impressed with its programmatic advertising offering that it ended up acquiring the company for 4.4 billion in June last year. Lord is now at IBM, in the newly-created chief digital officer role. Lord hasn't quite replaced Ginni Rometty to run the company, but he has been charged with transforming "Big Blue" into a much slicker operation that he hopes will appeal as much to Silicon Valley techies as its traditional enterprise customers.

As the global population ages, the number of cancer cases is going up. New cancer diagnoses are expected to rise by 70% in the next 2 decades, from 14 million to around 22 million, according to an estimate by the World Health Organization. Corporate giants like Google and IBM are already focusing on making breakthroughs in oncology, using advanced AI algorithms for early detection and personalized treatment of cancer. We used the CB Insights database to find equity-funded startups that are using artificial intelligence to fight cancer. California-based CureMetrix has developed an algorithm for image analysis, which is currently being tested to identify lung cancer in x-rays and for breast cancer detection in mammograms.