Facebook is using a combination of pattern recognition, live chat support from crisis support organizations and other tools to prevent suicide, with a focus on its Live service. There is one death by suicide every 40 seconds and over 800,000 people kill themselves every year, according to the World Health Organization. "Facebook is in a unique position--through friendships on the site--to help connect a person in distress with people who can support them," the company said Wednesday. The move by Facebook appears to aim to prevent the live-streaming of suicides on the Live platform, which was launched in April last year, and allows people, public figures and pages to share live videos with friends and followers. The company said that its suicide prevention tools for Facebook posts will now be integrated into Live, giving people watching a live video the option to reach out to the person directly and to report the video to the company.

Peter Shulman, an associate history professor at Case Western Reserve University in Ohio, was lecturing on the reemergence of the Ku Klux Klan in the 1920s when a student asked an odd question: Was President Warren Harding a member of the KKK? He confessed that he was not aware of that allegation, but that Harding had been in favor of anti-lynching legislation, so it seemed unlikely. But then a second student pulled out his phone and announced that yes, Harding had been a Klan member, and so had four other presidents. For most of its history, Google did not answer questions. Users typed in what they were looking for and got a list of web pages that might contain the desired information.

It seems like everyone wants to invest in artificial intelligence (AI). And it's not just the tech giants: USAA is using AI to protect its users from identity theft and Under Armour has connected its health app, MyFitnessPal, to IBM Watson so users can get a more thorough read of their health. AI is already a $15 billion dollar industry, according to the MIT Technology Review, with more than 2,600 companies developing their own tech, and the value of AI is reported to rise to over $70 billion by 2020. Because of AI's business opportunities, hundreds of designers in digital agencies, people who were taught to create products and services that live on the Internet, are starting to build physical products that interact with us, respond to our moods, and make decisions for us. It's a challenge that requires every skill they've learned, plus many they haven't. Still, designers know the basics: The principles of user-centric design lay the groundwork for building a great AI system.

This article is courtesy of Techstars, the best global ecosystem for entrepreneurs to bring new technologies to market. From inspiration to IPO, Techstars empowers the world's most promising entrepreneurs throughout their lifelong journey by providing a global ecosystem made up of tens of thousands of community leaders, founders, mentors, investors, and corporate partners. More consumers are getting used to purchasing their items online, through voice activation or on their smartphone. But there are more solutions that need to happen in retail and startups are starting to respond. After walking the floors of CES and other events, talking with our corporate partners, and meetings with hundreds of startups, here are some trends I'm seeing for 2017 for retail technology for startups.

As more self-driving cars hit the road in the coming years, sophisticated communications systems will rely on a fast, reliable network that's capable of being a data superhighway. Self-driving or autonomous cars are a hot topic, but the road to autonomous driving is curvy and complicated. It's full of blind turns as engineers, automakers, regulators and data scientists map out a radically different future for automobiles. That future is fast approaching. In January, the BMW Group, Intel and Mobileye said a fleet of about 40 of their autonomous test vehicles will be on roads by the second half of 2017.

After building up the human component of their network of suicide prevention organizations, Facebook is now bringing in the machines: The social media company announced they have updated their suicide prevention tools with artificial intelligence to identification of those at risk as well as improve the reporting process and speed up response time. On a company blog post from Vanessa Callison-Burch, Jennifer Guadagno and Antigone Davis (Facebook's Product Manager, Researcher, and Head of Global Safety, respectively) described key features of the updates, which include the integration of their prevention tools with Facebook Live and a testing phase of AI-powered pattern recognition to identify posts likely to include thoughts of suicide. "Based on feedback from experts, we are testing a streamlined reporting process using pattern recognition in posts previously reported for suicide," the company stated. "This artificial intelligence approach will make the option to report a post about'suicide or self injury' more prominent for potentially concerning posts like these." As Facebook tests that tool, employees will review posts flagged by the software and provide resources if the situation calls for it, even if no one has reported the post yet.

Arrival Amy Adams stars in this elegant, involving science-fiction drama that is simultaneously old and new, revisiting many alien-invasion conventions but with unexpected intelligence, visual style and heart. Elle Paul Verhoeven's brilliantly booby-trapped thriller starring Isabelle Huppert is a gripping whodunit, a tour de force of psychological suspense and a wickedly droll comedy of manners. The Founder Michael Keaton gives a performance of ratty, reptilian brilliance as Ray Kroc, the American salesman who turned a California burger stand into the global fast-food behemoth that is McDonald's, in John Lee Hancock's shrewd and satisfyingly fat-free biopic. I Am Not Your Negro As directed by the gifted Raoul Peck, this documentary on James Baldwin uses the entire spectrum of movie effects, not only spoken language but also sound, music, editing and all manner of visuals, to create a cinematic essay that is powerful and painfully relevant. La La Land Starring a well-paired Ryan Gosling and Emma Stone, writer-director Damien Chazelle's tuneful tribute to classic movie musicals is often stronger in concept than execution, but it's lovely and transporting all the same.

Scientists have developed a new artificial intelligence tool that can predict whether someone will attempt suicide as far off as two years into the future with up to 80 per cent accuracy. The team then combed through the electronic health records, which were anonymous, and identified more than 3,200 people who had attempted suicide. Using machine learning to examine all of those details, the algorithms were able to'learn' which combination of factors in the records could most accurately predict future suicide attempts. "The machine learns the optimal combination of risk factors. What really matters is how this algorithm and these variables interact with one another as a whole," said Jessica Ribeiro of Florida State University.

In Investment Management, we are just getting a grasp on this social media thing, marketing automation, and trying to simplify to an investor what Alts are –and I want you to concern yourself with something out, on the horizon? We are typically late to the party with bleeding edge marketing capabilities –a blessing and a curse. We let other industries test and learn while warming Compliance up to fancy newish "toys." We are pardoned time of these means to engage with investors and/or Financial Advisors but when leadership or sales partners get hip to these channels, we play catch-up with aggressive deadlines. Not to mention the impact to our brand with not having parity with our friends in other categories.

Scientists have developed a new artificial intelligence tool that can predict whether someone will attempt suicide as far off as two years into the future with up to 80 per cent accuracy. The team then combed through the electronic health records, which were anonymous, and identified more than 3,200 people who had attempted suicide. Using machine learning to examine all of those details, the algorithms were able to'learn' which combination of factors in the records could most accurately predict future suicide attempts. "The machine learns the optimal combination of risk factors. What really matters is how this algorithm and these variables interact with one another as a whole," said Jessica Ribeiro of Florida State University.