Governments and politicians have failed to respond to the current refugee crisis, and that's being made painfully prominent by the fact that 65 million people had been forced from their homes last year. However, where governments fail, private citizens and ingenuity can help. Joshua Browder's DoNotPay has proved this with a robot lawyer who gives refugees free legal advice. According to the Guardian, the chatbot aids refugees through Facebook Messenger by asking them a series of question to determine which forms they have to hand in and whether they are eligible for asylum protection. The robot lawyer also uses the information to automatically fill out forms and send them in on behalf of his'clients'.

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.

The Toronto Raptors already have a manual ghosting system where coaches mark out where they think players should have been. It can create ghosts in real time, even in soccer (aka football) and other sports where the continuous play can lead to predictions that gradually veer from realistic outcomes. The scientists rely on imitation learning, where AI bases its actions on demonstrations, to keep that long-term prediction in check. The early results are promising. In an example soccer match between Fulham and Swansea, a league-average ghost team replacing Swansea performed about as well in a defensive situation... not well at all, unfortunately.

I recently stumbled across a research paper, Using Deep Learning and Google Street View to Estimate the Demograp..., which piqued my interest in derivative uses of data, an ongoing research interest of mine. A variety of deep learning techniques were used to draw conclusions about relationships of car ownership, political affiliation and demographics. For those headline skimmers, you may be led to believe that researchers have just uncovered a vastly cheaper and more timely approach to perform the national census and make predictive claims about the population. The researchers' contention that official statistics are expensive and lagging is spot on. The principal US unemployment survey is performed in person or via telephone.

IBM is teaming up with Salesforce to make it easier for Salesforce customers to use data from IBM's Watson artificial intelligence platform. As part of the partnership, IBM has signed a deal to deploy the Salesforce Service Cloud for internal use there. The value of the deal and proposed pricing of the joint products were not disclosed. The deal has several parts. Both companies, like many others in the tech industry, are making investments in artificial intelligence and machine learning, by which computer programs attempt to connect data in new ways to provide new kinds of insights and assistance to users, and both frequently cite the importance of AI in their sales pitches to customers.

At the last meetup we mentioned that we have created a survey to understand your experience of the meetup, what you want get from it and how we should develop it in the future. We (the meetup organisers) would be very grateful if you could take a few minutes to complete the survey. We will leave it live for a couple more weeks and let you know some of the main findings at the next meetup (which will be in Accenture on 27th March). Just click the bit.ly/mldublin link to get started or paste this link into a browser: bit.ly/mldublin

Last fall, Google introduced a new system for machine-assisted language translations, Google Neural Machine Translation system (GNMT), which takes advantage of deep neural networks to translate entire sentences – not just phrases – for greatly improved translations. The company put the system to work in Google Translate for eight language pairs in November, and is today expanding support to three more: Russian, Hindi and Vietnamese. Neural Machine Translation went into action late last year with support for translating to and from English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish. These represent the native languages of around one-third of the world's population, covering more than 35% of all Google Translate queries, the company said at the time. Today's news is also fairly significant in terms of scale, as in the U.S. alone, 1,292,448 people speak Vietnamese; another 836,171 speak Russian; and 586,173 speak Hindi, Google says, citing U.S. census data. And more languages will be added in weeks ahead, including Thai, which didn't quite make today's release.

A study of 100 people from a variety of ages and technical aptitudes conducted at business school Bentley University in Massachusetts found that just as with other humans, people form first impressions of chatbots that stick. The study was conducted as part of the school's Human Factors and Information Design program, by students working under Bentley adjunct lecturer Meena Kothandaraman, founder of the twig fish research practice, and in partnership with NeuraFlash, a Boston-based firm that uses AI for Salesforce consulting. The takeaway for botbuilders is obvious: However sophisticated your bot, or whether it hangs out with Maroon 5, its first greeting and responses to new contacts will determine whether they find it an automated annoyance or a new best friend.

When Disney's legendary storytellers engage with new technology, a new art form emerges. Today, computers are approaching and even exceeding human performance in areas like vision and natural language understanding, and innovative companies like Disney are combining these new technologies with top creative minds to bring experiences to life like never before. Relationships with favorite stories and characters are strengthened when watching a Disney film, or visiting a Disney park or owning a Disney consumer products. Now imagine if Disney characters were able to interact with you personally, reacting to your own unique traits and style. In this panel, hear how the technical teams, artists and storytellers across Disney are hard at work using AI and Machine Learning to extend the Guest experience.