CUA is continuing to invest in customer experience (CX) and digital innovation with the extension of its virtual assistant trial in its health business. Encouraged by the success of'Sam', the virtual sales assistant for health insurance, CUA Health has signed on with Flamingo Ai to extend the artificial intelligence (AI)-powered assistant's use. This follows Australia's largest credit union also expanding the implementation of the member experience program in April. CUA piloted Confirmit's'Fast Track for Contact Centres' in CUA Direct call centres before expanding the program to include in-branch feedback. CUA Health has been trialling Flamingo Ai's technology live with potential health insurance customers for the past two months.

These devices, particularly the smart mobile phones have transformed over a period of time from merely communication tools to smart and highly personal devices enabling to assist the users in their variety of day-to-day situations in their daily life. In the real word, users' interest on "Mobile Phones" is more and more than other platforms like "Desktop Computer" or "Tablet Computer" over time [36]. People use mobile phones not only for voice communication between individuals but also for various activities such as applications (mobile apps) using, Internet browsing, emailing, using online social network, instant messaging etc [28]. Recent advances in the sensing capabilities of smart mobile phones make them enable to collect the rich contextual information and users' various activity records with mobile phones through the device logs. These historical mobile phone data are simply as the collection of the past contexts and user's activities with the mobile phones for these past contexts. These are phone call logs [39] having phone call activities, app usages logs [45] having various mobile application usages, mobile phone notification logs [22] having the responses with various notifications from different applications, web logs [13] having Internet browsing activities of the mobile phone users. The main characteristic of such kind of phone log data is that it contains the actual diverse activities of the users in different contexts in their real world life. Modeling smartphone user behaviors by developing various computational machine learning methods (rule-based learning) in order to analyze different behavioral patterns in different contexts, and eventually predict the next behaviors or detect strange behaviors utilizing such mobile phone data, can be used for build- 2 Iqbal H. Sarker*

Machine learning models are capable of capturing the structure-property relationship from a dataset of computationally demanding ab initio calculations. In fact, machine learning models have reached chemical accuracy on small organic molecules contained in the popular QM9 dataset. At the same time, the domain of large crystal structures remains rather unexplored. Over the past two years, the Organic Materials Database (OMDB) has hosted a growing number of electronic properties of previously synthesized organic crystal structures. The complexity of the organic crystals contained within the OMDB, which have on average 85 atoms per unit cell, makes this database a challenging platform for machine learning applications. In this paper, we focus on predicting the band gap which represents one of the basic properties of a crystalline material. With this aim, we release a consistent dataset of 12500 crystal structures and their corresponding DFT band gap freely available for download at https://omdb.diracmaterials.org/dataset. We run two recent machine learning models, kernel ridge regression with the Smooth Overlap of Atomic Positions (SOAP) kernel and the deep learning model SchNet, on this new dataset and find that an ensemble of these two models reaches mean absolute error (MAE) of 0.361 eV, which corresponds to a percentage error of 12% on the average band gap of 3.03 eV. The models also provide chemical insights into the data. For example, by visualizing the SOAP kernel similarity between the crystals, different clusters of materials can be identified, such as organic metals or semiconductors. Finally, the trained models are employed to predict the band gap for 260092 materials contained within the Crystallography Open Database (COD) and made available online so the predictions can be obtained for any arbitrary crystal structure uploaded by a user.

The last few decades have witnessed innovations in modern medicine, science and technology at a much faster rate than at any time before in history. A large portion of the credit goes to computers, for helping us solve problems more efficiently and therefore at a faster pace. Most recently, this has included the rise of Artificial Intelligence (AI), machine learning as well as neural networks that can simulate human thought patterns. They can then apply their more efficient brains to issues that desperately require resolution, many of which are in STEM fields like medicine or cryptography. STEM stands for science, technology, engineering and mathematics, but a far wider range of academic disciplines fall under this description. Courses one could study range from aerospace engineering and astronomy to civil engineering and statistics.

UniServices has followed Mercedes Benz's investment into Soul Machines with its own commitment of US$2m to a US$15m funding round announced recently by the company. UniServices, which owns 15% of the company, made the investment through its $20m University of Auckland Inventors Fund. Soul Machines was spun out of the University of Auckland in July 2016 with a Series A investment round by some of the world's leading AI investors. The University of Auckland Inventors Fund was formed in 2016, with capital provided from UniServices' retained earnings from its commercialisation business. Designed to fill a gap in the market for very early-stage capital in deep-tech IP based businesses, and to foster academic and student entrepreneurship, the Fund is typically the first investor in University-derived start-ups. It syndicates with local and global investors, including Horizon Ventures, Brandon Capital and the IP Group, that collectively have over $1bn of capital.

A robot holding a human brain in a virtual display isolated on a binary data numbered background, as an Artificial Intelligence (AI) in futuristic digital technology and medical concept/3-D illustration. The last few decades have witnessed innovations in modern medicine, science and technology at a much faster rate than at any time before in history. A large portion of the credit goes to computers, for helping us solve problems more efficiently and therefore at a faster pace. Most recently, this has included the rise of Artificial Intelligence (AI), machine learning as well as neural networks that can simulate human thought patterns. They can then apply their more efficient brains to issues that desperately require resolution, many of which are in STEM fields like medicine or cryptography. STEM stands for science, technology, engineering and mathematics, but a far wider range of academic disciplines fall under this description.

Artificial intelligence (AI) and emotional intelligence (EI) and how they can optimise the customer experience (CX) is the focus of an investment by Daimler Financial Services into New Zealand start-up, Soul Machines. The undisclosed strategic investment in Soul Machines aims to further develop artificial and emotional intelligence for a multi-channel, customer-service pilot using an avatar'Sarah' with facial recognition. Soul Machines is a leader in the field of emotional Intelligence for use in machines and digital avatars. Soul Machines has created a number of avatars including Nadia, a virtual human voiced by Cate Blanchett that's being trialled by the National Disability Insurance Agency (NDIA). Nadia was designed to operate across multiple channels from the outset to create a consistent interaction for clients, with the face being just one representation.

McKinsey reported that 400 to 800 million jobs worldwide will be lost by 2030. Not enough time for an entire generation to retrain for completely new jobs. As co-founder of Transhumanism Aus, where we investigate systematic changes to society and humanity, I know only too well what exponential technology is doing to jobs. In Australia alone, some of the nation's largest employers such as NAB will be slashing 6000 jobs over the next three years, while ANZ has already cut over 5000 people from it's workforce. Job automation is real and happening right now.

A small metal droplet can propel a wheeled robot forward with a simple electric current. The technique paves the way for larger robots that can trundle like tumbleweeds through unfriendly terrain. Shi-Yang Tang at the University of Wollongong in Australia and his colleagues started with a plastic wheel about five centimetres across with walls along its edges, shaped like a car tyre. Inside the wheel they placed a drop of liquid metal made mostly of gallium.

Clever crows can assemble tools from two or more components without any help, a feat previously seen only in humans and great apes. The birds were filmed slotting together rod pieces to create a tool long enough to extract a morsel of food which scientists had hidden away. In one experiment, they were presented with disassembled syringes, and created the right length of tool without any prompt or demonstration. The birds' ability to anticipate what an unseen object will be able to do matches the intelligence of a human toddler, Oxford University researchers said. The animals in the experiment were New Caledonian crows - a species native to a large Pacific island east of Australia of the same name.