We are really pleased to announce the date of our first Meetup for the IBM PowerAI Melbourne group. Please note - this meetup is being hosted by our awesome sponsors Advent One Pty Ltd (https://www.adventone.com). Our Presenters.... Dr Adam Makarucha is a data scientist within the IBM Systems team where he is developing deep learning use cases and demonstrations for clients on IBM's PowerAI platform. He recently completed his postdoctorate at IBM Research Australia, working within the Cognitive Analytics team on deep learning applications for the financial services industry. He has worked on machine and deep learning since joining IBM in 2015, primarily focused on natural language processing as well as risk and compliance.

Sarah Jeong, a technology journalist hired by the New York Times and vilified online for tweets comparing "dumbass f****** white people" to dogs and saying they would "all go extinct soon", has been targeted for harassment by dishonest trolls, her former employer has claimed. Editors at The Verge, an online tech magazine, denounced what they called "disingenuous" criticism of Ms Jeong by "people acting in bad faith". The senior writer had been the victim of a Gamergate-style campaign designed to "divide and conquer by forcing newsrooms to disavow their colleagues", they suggested. Ms Jeong, 30, posted a string of offensive and apparently racist messages including "#CancelWhitePeople" and "white men are bulls***" up to five years ago. After being uncovered they quickly spread and were picked up by conservative media including the Daily Caller and Gateway Pundit websites.

New Zealand Prime Minister Jacinda Ardern said those are the things she has obsessed over the most as a new parent, and that the experience of focusing on such basic needs for her baby girl has helped her appreciate why people with young families may not find time for politics. "So it's our job to make sure that we are serving the needs of people, regardless of whether they have time to engage with what we're doing or not," she said. "That's something that's been really amplified for me." Ardern spoke on Thursday at her bungalow in Auckland as she prepared to return to the capital, Wellington, after six weeks of leave following the birth of her daughter, Neve. Ardern, 38, is just the second elected world leader in recent history to give birth while holding office, and her story has provided inspiration for working mothers around the world.

Often referred to as the Amazon of China, JD.com started in 1998 as a brick-and-mortar store in Beijing, but it has aspirations to be the world's leading e-commerce retailer. Based on its tremendous growth, it might not take long for the company to get there. Richard Liu, the company's founder, CEO, and chairman, has even gone so far to predict his company won't need humans and said, "I hope my company would be 100% automation someday…no human beings anymore, 100% operated by AI and robots." JD.com and its competitors such as Amazon, Alphabet, Tencent, Alibaba and more are not only racing to be the world's largest e-commerce business but to create the operating system for retail in the future. JD.com is driving business with artificial intelligence, big data, and robotics while building the retail infrastructure for the 4th industrial revolution.

Mining heavyweights BHP, Roy Hill and Alcoa have joined forces with universities and the CSIRO to develop a new data science training centre to upskill workers in the local resources sector. The $3.9 million Training Centre for Transforming Maintenance being funded by the Australian Research Council will be based at Curtin University and will be supported by Adelaide and Western Australia universities. Federal Education and Training Minister Senator Simon Birmingham says the new centre will equip engineers and graduates with data analytics skills to better manage the vast and expensive array of assets owned by mining and energy operators around the country. The centre's director, professor Andrew Rohl, said the effective maintenance of those assets is essential for the $205 billion annual output of the Australian resources sector. "However, maintenance management practices have changed little in the last 20 years and are ripe for a digital overhaul that will bring developments in computational methods, statistics, applied mathematics and artificial intelligence to determine how, when and why maintenance is conducted," said Rohl. "The new centre, which will bring together the relevant research and industry expertise, will enable the development and adoption of new practices to improve productivity and asset reliability for industry and to foster a new maintenance technology service sector for national and international markets."

Machine learning software accounts for a significant amount of energy consumed in data centers. These algorithms are usually optimized towards predictive performance, i.e. accuracy, and scalability. This is the case of data stream mining algorithms. Although these algorithms are adaptive to the incoming data, they have fixed parameters from the beginning of the execution. We have observed that having fixed parameters lead to unnecessary computations, thus making the algorithm energy inefficient. In this paper we present the nmin adaptation method for Hoeffding trees. This method adapts the value of the nmin parameter, which significantly affects the energy consumption of the algorithm. The method reduces unnecessary computations and memory accesses, thus reducing the energy, while the accuracy is only marginally affected. We experimentally compared VFDT (Very Fast Decision Tree, the first Hoeffding tree algorithm) and CVFDT (Concept-adapting VFDT) with the VFDT-nmin (VFDT with nmin adaptation). The results show that VFDT-nmin consumes up to 27% less energy than the standard VFDT, and up to 92% less energy than CVFDT, trading off a few percent of accuracy in a few datasets.

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an important question is what makes deep neural networks able to generalize well from the training set to new data. In this article, we provide an overview of the existing theory and bounds for the characterization of the generalization error of deep neural networks, combining both classical and more recent theoretical and empirical results.

Apple has become the world's first publicly traded company to be valued at $1 trillion - 42 years after Steve Jobs and Steve Wozniak began the firm in a Silicon Valley garage. The stock rose nearly 3 percent following a strong third-quarter earnings report earlier this week, briefly hitting a session high of $207.05 in midday trading before falling back below $207. This briefly pushed Apple over the historic trillion dollar mark. Apple chief executive officer Steve Jobs stands in front of a photo of himself, right, and Steve Wozniak, left, during an Apple event in San Francisco in 2011. Apple's stock market value is greater than the combined capitalization of Exxon Mobil, Procter & Gamble and AT&T. It now accounts for 4 percent of the S&P 500.

Now artificial intelligence (AI) has come up with a detailed breakdown of someone's character by mapping tiny eye movements against a list of personality traits. A study, by the University of South Australia, tracked the eye movements of 42 participants as they went about their daily lives doing ordinary tasks around a university campus. The recorded movements were then compared to the result of personality questionnaires completed by the subjects. Next, researchers used machine learning algorithms to map individual's eye movements with the'big five' personality traits - openness to experience, conscientiousness, extroversion, agreeableness and neuroticism. They found that each individual's unique pattern of eye movements could be linked to their personality traits.

The HPC Advisory Council has posted the Agenda for their upcoming meeting in Perth, Australia. Hosted by the Pawsey Supercomputing Centre, the event takes place August 28-29. The hosts have added a powerful international dialog session to the second annual conference agenda featuring an impressive list of leading HPC centres and industry representatives. This year's program also includes a wide variety of invited and contributed talks on high performance computing, artificial intelligence, and cutting-edge research and development from industry notables throughout the region and beyond. The 2018 agenda also features hands-on tutorials, the latest trends, newest technologies and breakthrough works along with the latest best practices in applications, tools and techniques.