I live in Brisbane, Australia. I graduated in 2015 with a Dual Major in Food Science and Nutrition. It took me five years to do a three-year undergraduate degree. I thought I wanted to be a doctor. Probably because I was following what my friends were doing rather than creating my own path.

Regulatory and compliance issues are some of the most important, complex and resource-consuming problems to solve for any organization, especially for startups with limited resources. Over decades of development, regulatory requirements and documentation have grown into a matter of special expertise and skills to decode. Globally, $80 billion is spent on governance, risk and compliance, and the market is only expected to grow, reaching $120 billion in the next five years . According to ANZ, National Australia Bank has estimated that the cost of regulatory compliance has risen from $A86 million annually in 2012 to $A177 million in 2013 and $A265 million in 2014. Westpac was reported to spending $A300 million on compliance last year.

For over 50 years, Disneyland and its sister parks have been a showcase for increasingly technically proficient versions of its "animatronic" characters. First pneumatic and hydraulic, and more recently fully electronic, these figures create a feeling of life and emotion inside rides and attractions, in shows and, increasingly, in interactive ways throughout the parks. The machines they're creating are becoming more active and mobile in order to better represent the wildly physical nature of the characters they portray within the expanding Disney universe. And a recent addition to the pantheon could change the way that characters move throughout the parks and influence how we think about mobile robots at large. I wrote recently about the new tack Disney was taking with self-contained characters that felt more flexible, interactive and, well, alive than "static," pre-programmed animatronics.

Like most people, coffee is one of the most important rituals in my morning routine. There's something about the aroma and taste that kick-starts my ability to have a great day. So imagine my surprise when I found out that a favorite coffee shop was closed before I had to jump on an early-morning flight home. The employees were in the shop, but the gate locked out coffee aficionados, like me, that really needed that jolt of caffeine. Although this experience was understandably a letdown, it was also a source of inspiration.

Willis Towers Watson, a leading global advisory, broking and solutions company, and Relativity6, Inc., a machine learning and artificial intelligence (AI) insurance-technology company, today announced that Willis Towers Watson has selected the Relativity6 platform to predict and optimise customer retention and win-back. Brent Lehmann, General Manager Affinity & Commercial Australasia said the partnership with such an innovative technology company will help to ensure Willis Towers Watson remains competitive in the marketplace. "Relativity6's product offerings are a good fit to accomplish our strategic objectives across the organisation, so we are very excited to partner with them to take full advantage of the data that we have accumulated within our core systems in Australia." Alan Ringvald, Chief Executive Officer at Relativity 6, commented: "We are honoured to partner with such a distinguished organization. We believe that our solution will enable Willis Towers Watson to better serve their customers and ultimately drive significant top line revenue growth. We've engaged with top-tier insurers in the U.S. and Latin America, and this is a fantastic opportunity to expand our footprint with a truly global insurance broking brand."

Implicit discourse relation recognition is a challenging task as the relation prediction without explicit connectives in discourse parsing needs understanding of text spans and cannot be easily derived from surface features from the input sentence pairs. Thus, properly representing the text is very crucial to this task. In this paper, we propose a model augmented with different grained text representations, including character, subword, word, sentence, and sentence pair levels. The proposed deeper model is evaluated on the benchmark treebank and achieves state-of-the-art accuracy with greater than 48% in 11-way and $F_1$ score greater than 50% in 4-way classifications for the first time according to our best knowledge.

A healthtech company using AI to digitize the diagnosis system has raised a new funding round. MetaOptima Technology has raised $8.6 million to grow its cutting-edge DermEngine platform. The Series A round was led by the Australian Skip Capital and AirTree Ventures, with respective fund principals Scott Farquhar and Daniel Petre joining the MetaOptima board. "Our vision is bold: we want to be in every major dermatology centre and skin cancer clinic in Australia, and we're well on track to making that a reality," said Maryam Sadeghi, CEO and co-founder of MetaOptima. "With the support of AirTree Ventures and Skip Capital, we're confident our platform will continue to shape and change the state of play for both healthcare professionals and patients."

A team of data scientists, researchers and clinicians from UNSW Sydney have won a major prize at the second annual Healthcare Artificial Intelligence Datathon held at the National University of Singapore (NUS). The two-day event – organised jointly by the National University Health System (NUHS), Massachusetts Institute of Technology (MIT) and NUS – hosted more than 200 local and international data scientists and clinicians last weekend to address current problems in healthcare with the latest machine learning and artificial intelligence technologies. The joint UNSW-NUS team won first prize in the Critical Care Track, competing against eight other teams to analyse clinical data contained in the MIT/Philips eICU Collaborative Research Database, comprising information on more than 200,000 patients treated in intensive care units in US hospitals over the past five years. The UNSW-NUS team included researchers Oluwadamisola Sotade, Dr Mark Hanly and Oisin Fitzgerald from UNSW's Centre for Big Data Research in Health, Dr Tim Churches, data scientist from the Ingham Institute for Applied Medical Research and UNSW South Western Sydney Clinical School, and Dr Peter Straka from UNSW Mathematics and Statistics. "The installation of next-generation electronic medical records systems in ICUs and throughout hospitals enable very sophisticated machine-learning and artificial intelligence algorithms to be developed to assist busy clinicians in patient care and treatment decision making." said Dr Churches.

TUM is the only German university among the ten most influential institutions in the field of artificial intelligence (AI). The top spots in the rankings are held by the Massachusetts Institute of Technology (MIT) and Carnegie Mellon University, both in the USA, and Nanyang Technological University in Singapore, with which TUM maintains a close partnership. Half of the top ten positions are held by Asian universities. The only European representative apart from TUM is the University of Granada in Spain, which ranks fourth. The report also includes country rankings.

We unify recent neural approaches to one-shot learning with older ideas of associative memory in a model for metalearning. Our model learns jointly to represent data and to bind class labels to representations in a single shot. It builds representations via slow weights, learned across tasks through SGD, while fast weights constructed by a Hebbian learning rule implement one-shot binding for each new task. On the Omniglot, Mini-ImageNet, and Penn Treebank one-shot learning benchmarks, our model achieves state-of-the-art results.