The long AI winter is over. Instead of being a punchline, machine learning is one of the hottest skills in tech right now. Companies are scrambling to find enough programmers capable of coding for ML and deep learning. While no one programming language has won the dominant position, here are five of our top picks for ML libraries for Java. It comes as no surprise that Weka is our number one pick for the best Java machine learning library.

Would your banking experience be more satisfying if you could gaze into the eyes of the bank's customer service chatbot and know it sees you frowning at your overdraft fees? Professor and entrepreneur Mark Sagar thinks so. Sagar won two Academy Awards for novel digital animation techniques for faces used on movies including Avatar and King Kong. He's now an associate professor at the University of Auckland, in New Zealand, and CEO of a startup called Soul Machines, which is developing expressive digital faces for customer service chatbots. He says that will make them more useful and powerful, in the same way that meeting someone in person allows for richer communication than chatting via text.

Artificial intelligence (AI) is simultaneously overhyped, misunderstood, and already hugely impactful, according to Pegasystems CTO Don Schuerman, who said many organisations were already successfully using the technology before it became an industry buzzword. Schuerman told ZDNet that he has been encouraging his clients to take a look at what pragmatic AI technologies they can employ to deliver real benefits to how they interact with customers, rather than succumbing to the hype. The best example is what the Commonwealth Bank of Australia (CBA) is doing, he said. "They've got Pegasystems' product called the Customer Decision Hub, which uses predictive analytics and adaptive or self-learning analytics to figure out in real time what the best offer or service is, or recommendations are, to put in front of a customer either to improve their satisfaction rate and retention rate, for example," he explained. In implementing the technology, CBA has increased its branch sell rates by 13 percent, which Schuerman said is a significant impact to the business.

If all the would-be mothers are thinking of taking DHA supplements hoping to boost their child's IQ, they should keep the thought aside. In latest findings from a study published in Tuesday's edition of the Journal of the American Medical Association (JAMA), researchers found that providing DHA to a baby while it is in the mother's womb does not increase their IQ levels as compared to the babies who do not get the supplement. The study was originally conducted in 2010, 2011 and 2012 when researchers in Australia enlisted 2,399 pregnant women to participate in a clinical trial. The women were divided into two groups, one of which was given capsules that comprised of 800mg of DHA per day and the others were given a placebo that did not contain DHA but had vegetable oil in it. The results of the follow up IQ test -- the Wechsler Abbreviated Scale of Intelligence, Second Edition, was conducted to assess the benefits of DHA supplements on IQ levels of 7 year olds.

Australia is a one ride share company town. Want to take a trip in someone else's depreciating asset? Americans, of course, have an alternative: Lyft. So when director of strategic partnerships, Insiya Lokhandwala, appeared on the schedule of Brisbane's Myriad startup festival in late March, you had to wonder: Was Australia's moment finally here? Lyft's communication director was noncommittal.

Representing documents is a crucial component in many NLP tasks, for instance predicting aspect ratings in reviews. Previous methods for this task treat documents globally, and do not acknowledge that target categories are often assigned by their authors with generally no indication of the specific sentences that motivate them. To address this issue, we adopt a weakly supervised learning model, which jointly learns to focus on relevant parts of a document according to the context along with a classifier for the target categories. Derived from the weighted multiple-instance regression (MIR) framework, the model learns decomposable document vectors for each individual category and thus overcomes the representational bottleneck in previous methods due to a fixed-length document vector. During prediction, the estimated relevance or saliency weights explicitly capture the contribution of each sentence to the predicted rating, thus offering an explanation of the rating. Our model achieves state-of-the-art performance on multi-aspect sentiment analysis, improving over several baselines. Moreover, the predicted saliency weights are close to human estimates obtained by crowdsourcing, and increase the performance of lexical and topical features for review segmentation and summarization.

Competition amongst universities is set to increase with institutions closely differentiating themselves to attract and retain the best quality students, academics and staff. Key to this differentiation will be an extensive technology adoption and innovation strategy, enhancing the student experience, delivery of learning content, community engagement and campus management. The education technology (Edutech) market in Australia is expected to grow significantly amidst increasing student demand for education services and technology innovation, competition amongst institutions and decreasing acquisition costs. Frost & Sullivan anticipates that as the learning experience becomes increasingly digitised, technologies and solutions incorporating big data and analytics, collaboration, Augmented / Virtual Reality technology, Artificial Intelligence and learning management systems will play a key role within universities in the coming years. Frost & Sullivan's most recent analysis, Australian Edutech Market: Key Trends, Technologies and Opportunities 2016-2022 finds that the Australian Edutech Market is expected to grow to AUD 1.7 Billion by 2022.

We investigate different strategies for active learning with Bayesian deep neural networks. We focus our analysis on scenarios where new, unlabeled data is obtained episodically, such as commonly encountered in mobile robotics applications. An evaluation of different strategies for acquisition, updating, and final training on the CIFAR-10 dataset shows that incremental network updates with final training on the accumulated acquisition set are essential for best performance, while limiting the amount of required human labeling labor.

The launch of the Samsung Galaxy S8 March 29 will represent a comeback for the company's mobile unit, which is recovering by the Galaxy Note 7 disaster. What's unclear is how Samsung Galaxy S8 flagship phone will fare given the multiple unknowns the company is facing. Samsung's Galaxy S8 lands amid a backdrop of the company's January report on what went wrong with the Note 7 and how it is fixing its processes to prevent battery problems in the future. That report went a long way to allaying fears, but brand recoveries take time. The device will have new artificial intelligence tools via a service called Bixby.

The New Zealand branch of leading Asia-Pacific law firm MinterEllison, known as MinterEllisonRuddWatts, has launched a joint venture with tech investment platform Goat Ventures to develop a new legal AI company. The JV will provide NZ$2m as co-investment to develop a completely new legal AI business. The firm said it wanted to focus on AI because legal services are well suited to this technology. The MinterEllison project in New Zealand is different in that it is specifically looking at building a legal AI application, most other law firms that have invested in or supported new legal tech have had a more general outlook. Also, this JV is focused on creating just one standalone legal AI business and is not seeking to support start-ups in general or seeking to be an incubator or accelerator to other legal tech businesses.