Facebook has announced the addition of new resources -- aided by artificial intelligence -- to help identify and support at-risk users, specifically those who may be suicidal. In a post on the Facebook newsroom blog, product manager Vanessa Callison-Burch, researcher Jennifer Guadagno and head of global safety Antigone Davis note, "There is one death by suicide in the world every 40 seconds, and suicide is the second leading cause of death for 15–29 year olds. Experts say that one of the best ways to prevent suicide is for those in distress to hear from people who care about them." Facebook already provides suicide prevention tools -- rolled out over 10 years ago -- such as offering tips on how to find support and the option for users to report posts that contain self-harm or suicide-related content. The company is testing a new tool to aid this process: artificial intelligence.

Artificial intelligence advertising firm LoopMe has won an additional $10m funding, a total of $17 million to date, as machine learning becomes a vital part of digital marketing. The new funding was received from Impulse VC and Harbert European Growth Capital to support global growth and continued investment in artificial intelligence technology. Existing investors Holzbrinck Ventures and Open Ocean Capital also participated in the round. LoopMe now counts investment from UK, Germany, Finland, North America, China and Russia, signaling global support for its AI technology. LoopMe's AI technology learns how people feel about and react to advertising, and changes their advertising experience based on their individual feedback loop. Since receiving its previous round of funding in 2015, LoopMe reached profitability for the full year 2016, more than doubled its sales revenue and team size, opened offices in LA, Bangalore, Johannesburg and Moscow, and invested heavily in its technology.

Yesterday, the UK government announced their budget plans to invest in robotics, artificial intelligence, driverless cars, and faster broadband. "The UK understand the very real positive impact that RAS [robotics & autonomous systems] will have on our society from now, of all time. It continues to see the big picture and today's announcement by the Chancellor is a clear indication of that. We can have better roads, cleaner cities, healthier oceans and bodies, safer skies, deeper mines, better jobs and more opportunity. That's what machines are for."

What if you could directly ask questions of your data and the software could respond with a selection, filter, or new visualization? In this DSC webinar, the Tableau Research team explains natural language queries and how they are (already) helping you visualize your data. This presentation includes an introduction to natural language processing (NLP), examples of how NLP is already used in Tableau's geocoding and map search, and a demonstration of some research prototypes that you might see in the not too distant future. Come participate in the discussion and tell us what things you would say to or ask your visualization!

DenseNet(Densely Connected Convolutional Networks) is one of the latest neural networks for visual object recognition that obtains state of the art results on many datasets. It's quite similar to ResNet but has some fundamental differences. This post assumes previous knowledge of neural networks(NN) and convolutions(convs). If you know how DenseNets works and interested only in tensorflow implementation feel free to jump to the second chapter or check the source code on GitHub. If you not familiar with any topics but want to get some knowledge -- I highly advise you this CS231n Stanford classes.

It has become an undeniable fact of life that people are going to Google their health symptoms. However, as most physicians are reminded every day by patients who come to the hospital or office armed with their smartphones or printouts of their search results, the internet often leads people to draw erroneous or even harmful conclusions about their health. Fed up with the confusion and misinformation of patients he was encountering as a third-year medical resident in 2014, Harvard Medical School student Andrew Le thought there had to be a better way. Over the past three years, Le and his colleague Eddie Reyes worked with a team at the Innovation Laboratory at Harvard to develop a digital health tool that would function as a health-specific search engine while also giving patients pointers and compassion along the way. "Right now, the status quo is Googling symptoms and getting scared. That is the front door of healthcare," Le told MobiHealthNews in an interview.

At JPMorgan, a learning machine is parsing financial deals that once kept legal teams busy for thousands of hours. The program, called COIN, for Contract Intelligence, does the mind-numbing job of interpreting commercial-loan agreements that, until the project went online in June, consumed 360,000 hours of lawyers' time annually. The software reviews documents in seconds, is less error-prone and never asks for vacation. While the financial industry has long touted its technological innovations, a new era of automation is now in overdrive as cheap computing power converges with fears of losing customers to startups. Made possible by investments in machine learning and a new private cloud network, COIN is just the start for the biggest U.S. bank.

From Amazon shopping recommendations, Facebook image recognition, and personal assistants like Siri*, Cortana*, and Alexa*, your phone is becoming a portal to real-world applications of artificial intelligence. Learn more about how A.I. is becoming part of your everyday life, and how your phones are your direct connection to the evolving world of artificial intelligence.

Whether an A.I. ought to be granted patent rights is a timely question given the increasing proliferation of A.I. in the workplace. One might argue that Intellectual Property (IP) laws and IP Rights were designed to exclusively benefit human creators and inventors[7] and thus would exclude non-humans from holding IP rights. However, many IP laws were drafted well before the emergence of A.I. and in any case, do not explicitly require that a creator or inventor be'human.' The World Intellectual Property Organization's (WIPOs) definition of Intellectual Property talks about creations of the mind[9] but does not specify whether it must be a human mind. Similarly, provisions in laws promoting innovation and IP rights, such as the so-called Intellectual Property Clause of the U.S. Constitution[10], also do not explicitly mention a'human' requirement.

Conversable is'conversational intelligence' platform to help non-programmers impart human knowledge into conversation robots. Conversable is used by hockey fans with Budweiser Red Lights goal-synced products to access light-device-smartphone setup tutorials, access troubleshooting advice and receive further support from live customer service reps through Facebook Messenger. Artificial Intelligence (AI) has had something of a makeover and renaissance in recent times. We have stopped using the term to describe fantasy Sci-Fi robots and started to talk about real software robots that we often call'bots' that we build to serve our needs automatically. Botification is now a thing.