Today I am back at the Data Fest Data Summit 2018, for the second day. I'm here with my EDINA colleagues James Reid and Adam Rusbridge and we are keen to meet people interested in working with us, so do say hello if you are here too! I'm liveblogging the presentations so do keep an eye here for my notes, updated throughout the event. As usual these are genuinely live notes, so please let me know if you have any questions, comments, updates, additions or corrections and I'll update them accordingly. We've just opened with a video on Ecometrica and their Data Lab supported work on calculating water footprints. I'd like to start by thanking our sponsors, who make this possible. And also I wanted to ask you about your highlights from yesterday. These include Eddie Copeland from Nesta's talk, discussion of small data, etc. Data science has a huge impact for the business world, but also for societal good. I wanted to talk about the 5 i's of data science for social good: So, the number one, is the Interest. The data can attrat people to engage with a problem. Everything we do is digital now. And all this information is useful for something. No matter what your passion, you can follow this as a data scientist. I wanted to give an example here… My background is astrophysics and I love teaching people about the world, but my day job has always been other things. About 20 years ago I was working in data science at NASA and we saw an astronomical – and I mean it, we were NASA – growth in data. And we weren't sure what to do with it, and a colleague told me about data mining. It seemed interesting but I just wasn't getting what the deal was. We had a lunch talk from a professor at Stanford, and she came in and filled the board with equations… She was talking about the work they were doing at IBM in New York. And then she said "and now I'm going to tell you about our summer school" – where they take kids from inner city kids who aren't interested in school, and teach them data science. Deafening silence from the audience… And she said "yes, we teach the staff data mining in the context of what means most for these students, what matters most. And she explained: street basketball. So IBM was working on a software called IBM Advanced Calc specifically predicting basketball strategy. And the kids loved basketball enough that they really wanted to work in math and science… And I loved that, but what she said next changed my life. My PhD research was on colliding galaxy. It was so exciting… I loved teaching and I was so impressed with what she had done.

During this past week, AI Singapore signed three Memorandum of Understanding (MOUs), reiterating AI Singapore's commitment to pursue research, develop skills and talent, as well as embrace new technologies in AI-related areas. The three MOUs were signed with the National Trades Union Congress (NTUC), Intel Corporation and PwC Singapore. AI Singapore [1] was launched in May 2017 by the National Research Foundation (NRF) of Singapore with up to S$150 million in funding to catalyse, synergise and boost Singapore's AI capabilities. AI Singapore's key programmes include fundamental research, addressing Grand Challenges and conducting 100 experiments in collaboration with companies to tackle real-life business problems. It also runs an AI Apprenticeship programme through a collaboration with the Infocomm Media Development Authority (IMDA).

Artificial intelligence promises to be a paradigm shift for many applications from manufacturing to finance, and from defense to education. Given the vast potential, focus on AI has sharpened around the world, including in China. Decision makers in Beijing and around the country are paying attention and have begun shaping a legal and policy regime that favors the development of AI. Research and investment in AI on both sides of the Pacific has led to cross-border collaboration – both in terms of talent and capital. Last December, Google announced that it will open an AI research center in Beijing, in part to leverage AI talent there. A month earlier, San Diego-based Qualcomm announced a strategic investment in SenseTime, a Chinese company specializing in facial-recognition software.

For D3 templates for producing many of these chart types in FT style, see our Visual Vocabulary repo. The full content of the poster, along with links to related material, including research and examples of best practice. This is a work in progress. Emphasise variations ( /-) from a fixed reference point. Typically the reference point is zero but it can also be a target or a long-term average. Can also be used to show sentiment (positive/neutral/negative).

Adam Kassam is the chief resident physician in the department of Physical Medicine & Rehabilitation at Western University in London, Ont.. Naila Kassam is a family physician and adjunct professor in the department of Family Medicine at Western University. By honing the incredible potential of neural nets -- the assembly of computer networks -- in a way that mirrors the architecture of the human brain, Dr. Hinton has unlocked the learning power of machines. In so doing, he has become the darling of a burgeoning area of computing that has the ability to completely revolutionize the practice of medicine and the delivery of health care. Geoffrey Hinton of the University of Toronto is among the foremost researchers in the field of machine-learning and artificial intelligence. As AI begins to take off, will the health-care industry be receptive to technological disruption despite its notorious aversion to change? What is clear is that it will be crucial for the medical community to use its clinical expertise to help leverage technology and AI to improve the delivery of health care.

Although deep learning has produced dazzling successes for applications of image, speech, and video processing in the past few years, most trainings are with suboptimal hyper-parameters, requiring unnecessarily long training times. Setting the hyper-parameters remains a black art that requires years of experience to acquire. This report proposes several efficient ways to set the hyper-parameters that significantly reduce training time and improves performance. Specifically, this report shows how to examine the training validation/test loss function for subtle clues of underfitting and overfitting and suggests guidelines for moving toward the optimal balance point. Then it discusses how to increase/decrease the learning rate/momentum to speed up training. Our experiments show that it is crucial to balance every manner of regularization for each dataset and architecture. Weight decay is used as a sample regularizer to show how its optimal value is tightly coupled with the learning rates and momentums.

An important problem in the social sciences is estimating the effect of a policy intervention on an outcome over time. When interventions take place at an aggregate level (e.g., city or state), researchers make causal inferences by comparing the post-intervention outcomes for affected units ("treated") against the outcomes of a group of unaffected units ("control"). The synthetic control method (SCM) (Abadie, Diamond, and Hainmueller 2010) has become a popular method for making causal inferences on observational time-series. The method compares a single treated unit outcome with a synthetic control that combines the outcomes of multiple control units on the basis of their pre-intervention similarity with the treated unit. The SCM has several limitations.

The United States military carried out its first ever drone strike against Qaeda militants in southern Libya this weekend, signaling a possibly significant expansion of the American counterterrorism campaign in the North African nation. Until now, the Pentagon had focused its counterterrorism strikes in Libya almost exclusively on Islamic State fighters and operatives farther north -- eight since President Trump took office. In 2016, the military conducted nearly 500 airstrikes in the coastal city of Surt over several months to destroy the Islamic State's stronghold there. But the attack on Saturday that the military's Africa Command said had killed two militants -- later identified by a spokeswoman as belonging to Al Qaeda's branch in northwestern Africa -- took place in the country's southwest, a notorious haven for a deadly mix of Al Qaeda and other extremist groups that also operate in the Sahel region of Niger, Chad, Mali and Algeria. "This appears to be the continuation of expanding AFRICOM activity in Libya's ungoverned areas," said Deborah K.

The shooting at the school in Florida was devastating, and it appears clear that Russia has been manipulating public opinion in the U.S. to stoke the flames of a divisive argument on guns. What is being missed is a brewing problem that potentially could have an even more devastating impact. Competing for our eyeballs is the news that the U.S. president kissed a woman without her permission. That story has served as a distraction from far more horrendous attacks against women in the tech industry and in government. Intel showcased virtual reality at the Olympics, but almost no one cared.

A copy of'The Observer' shows an advertisement paid by Facebook in London, March 25, 2018. Facebook Chief Executive Mark Zuckerberg apologized for a "breach of trust" involving misused data from millions of Facebook users. The ads also appeared in The New York Times, Washington Post and Wall Street Journal. SAN FRANCISCO -- As Facebook continues to buffet winds of criticism, its founder took out full page ads in U.S. and British newspapers Sunday to apologize to consumers for not properly securing their personal data. "This was a breach of trust, and I'm sorry we didn't do more at the time," Mark Zuckerberg said in the signed ad, which was published in The New York Times, The Wall Street Journal, The Washington Post and six British papers.