Pogrebna is a pioneer in behavioural data science – a field that combines behavioural science and data science techniques to better understand, model and predict the behaviour of humans, algorithms and complex systems in the face of risk and uncertainty. "I warmly welcome Professor Pogrebna to the University and look forward to working with her to establish the Cybersecurity and Data Science Institute," Charles Sturt pro vice-chancellor (Research and Innovation) Professor Mark Evans said. "Professor Pogrebna comes to the University with a wealth of experience. This includes being the Lead of the Behavioural Data Science strand at The Alan Turing Institute – the national centre for AI and data science in London where she is also a Fellow working on hybrid modelling approaches between behavioural science and data science (e.g. According to Evans, Pogrebna helps leaders in businesses, charities and the public sector better understand why they make the decisions they make and how they can optimise their behaviour to achieve higher profit, better social and commercial outcomes, and bolster the wellbeing of their teams. Pogrebna said her goal as executive director of the Cybersecurity and Data Science Institute is to avoid'building a silo'. "I have spent several weeks visiting our researchers across the University's campuses and became aware of the incredible work they are doing," she said. "The new Institute will aim to support our local talent and build on it, seeing how we can develop new research collaborations in Australia as well as internationally.

Nine months since the launch of our first commercial product, the OpenAI API, more than 300 applications are now using GPT-3, and tens of thousands of developers around the globe are building on our platform. They also want a way to edit their address in checkout and save multiple payment methods." "GPT-3's ability to identify themes from natural language and generate summaries allows Viable to give product, customer experience, and marketing teams at companies across industries a better understanding of their customers' wants and needs," said Daniel Erickson, CEO of Viable. Algolia uses GPT-3 in their Algolia Answers product to offer relevant, lightning-fast semantic search for their customers. When the OpenAI API launched, Algolia partnered with OpenAI to integrate GPT-3 with their advanced search technology in order to create their new Answers product that better understands customers' questions and connects them to the specific part of the content that answers their questions. Algolia Answers helps publishers and customer support help desks query in natural language and surface nontrivial answers. "We've seen great results from Algolia Answers on questions that are difficult to answer with textual search alone," said Peter Buffington, Product Manager at ABC Australia. "It was able to return very relevant, evergreen content from our news archives for questions such as'Why does a volcano erupt?'" "GPT-3 allows Algolia to answer more complex queries than ever before with our Algolia Answers product, identifying deeper contextual information to improve the quality of results and deliver them in seconds," said Dustin Coates, Product and GTM Manager at Algolia. We require developers to implement safety measures such as rate limits, user verification and testing, or human-in-the-loop requirements before they move into production. Nine months since the launch of our first commercial product, the OpenAI API, more than 300 applications are now using GPT-3, and tens of thousands of developers around the globe are building on our platform. They also want a way to edit their address in checkout and save multiple payment methods."

Since 2002, Quantium have combined the best of human and artificial intelligence to power possibilities for individuals, organisations and society. Whether it be building forecasting engines that are driving down food wastage or creating mapping tools to support targeted measures in combatting human trafficking, Quantium believes in better goods, services, experiences, and championing the benefits of data for a brighter future. Our partnership with Woolworths has given us un-paralleled access to customer behaviour data of over 10 million customers that we leverage to provide insights for our diverse range of Woolworths client stakeholders. We've taken this partnership deeper by establishing Wiq. Wiq is our joint venture with Woolworths which will lead a data-driven transformation agenda for Woolworths and commercialise retail products globally.

Instrumental variable (IV) is a powerful approach to inferring the causal effect of a treatment on an outcome of interest from observational data even when there exist latent confounders between the treatment and the outcome. However, existing IV methods require that an IV is selected and justified with domain knowledge. An invalid IV may lead to biased estimates. Hence, discovering a valid IV is critical to the applications of IV methods. In this paper, we study and design a data-driven algorithm to discover valid IVs from data under mild assumptions. We develop the theory based on partial ancestral graphs (PAGs) to support the search for a set of candidate Ancestral IVs (AIVs), and for each possible AIV, the identification of its conditioning set. Based on the theory, we propose a data-driven algorithm to discover a pair of IVs from data. The experiments on synthetic and real-world datasets show that the developed IV discovery algorithm estimates accurate estimates of causal effects in comparison with the state-of-the-art IV based causal effect estimators.

Fortunately, the search proved successful. But it wasn't a human who found the promising molecules. It was a machine learning program. One compound has been patented under the name Halicin in homage to HAL, the artificial intelligence (AI) in Arthur C Clarke's classic 2001: A Space Odyssey. Halicin works differently from existing antibiotics, disrupting the bacteria's ability to access energy, and researchers hope bacteria may struggle to develop resistance to it.

NASA is set to launch its'CAPSTONE' spacecraft mission later this month to orbit around the moon, in preparation for a new lunar space station. The craft, which is around the size of a microwave oven and weighs just 55 pounds, will blast off from the Māhia Peninsula, New Zealand some time between June 13-22. It will test the stability of a halo-shaped orbit around the moon before this is used by Lunar Gateway, NASA's planned lunar outpost. Lunar Gateway will one day serve as a'staging area' for landing humans on the moon and potentially as a jumping point for missions to Mars. Pictured is an artist's impression of CAPSTONE in orbit around the moon with the Earth in the background.

Atmospheric Extreme Events (EEs) cause severe damages to human societies and ecosystems. The frequency and intensity of EEs and other associated events are increasing in the current climate change and global warming risk. The accurate prediction, characterization, and attribution of atmospheric EEs is therefore a key research field, in which many groups are currently working by applying different methodologies and computational tools. Machine Learning (ML) methods have arisen in the last years as powerful techniques to tackle many of the problems related to atmospheric EEs. This paper reviews the ML algorithms applied to the analysis, characterization, prediction, and attribution of the most important atmospheric EEs. A summary of the most used ML techniques in this area, and a comprehensive critical review of literature related to ML in EEs, are provided. A number of examples is discussed and perspectives and outlooks on the field are drawn.

BambooHR, the industry's leading cloud-hosted software provider dedicated to powering the strategic evolution of human resources, announced it has added Ease to its Marketplace. Ease, an online benefits enrollment solution built for insurance brokers and used by employers, and BambooHR will now offer joint customers an integration that will eliminate duplicative data entries between HR and benefits systems, reducing the risk of errors, and saving joint customers time. The BambooHR Marketplace includes 119 applications that integrate with BambooHR and gives partners the opportunity to leverage the BambooHR open API to build these connectors and integrations. They can also promote and showcase their solutions to over 27,000 BambooHR customers, from hiring and onboarding, people and culture, compensation, benefits and more, all designed to give joint customers the ability to streamline their HR experience across the board. Selects Riskified to Help Deliver a More Secure and Frictionless Shopping Experience for Customers in Australia and New Zealand "Ease provides a simple way to set up and manage benefits, giving employees access to key details related to their benefits and employment in one place," said Shama Madhvani, director of business development and strategic partnerships at BambooHR.

Prime Video is playing host to a vast range of sci-fi stories, from the absolute classics to the hidden gems more people need to watch. One of those is Coherence, widely regarded as the best hidden sci-fi gem out there. How cool and intriguing is that title? Beyond the Infinite Two Minutes is a low-budget time travel comedy from Japanese filmmaker Junta Yamaguchi. The wild premise: A café worker discovers his TV can show him what happens 2 minutes into the future.

Monitoring whales in remote areas is important for their conservation; however, using traditional survey platforms (boat and plane) in such regions is logistically difficult. The use of very high-resolution satellite imagery to survey whales, particularly in remote locations, is gaining interest and momentum. However, the development of this emerging technology relies on accurate automated systems to detect whales, which are currently lacking. Such detection systems require access to an open source library containing examples of whales annotated in satellite images to train and test automatic detection systems. Here we present a dataset of 633 annotated whale objects, created by surveying 6,300 km2 of satellite imagery captured by various very high-resolution satellites (i.e. WorldView-3, WorldView-2, GeoEye-1 and Quickbird-2) in various regions across the globe (e.g. Argentina, New Zealand, South Africa, United States, Mexico). The dataset covers four different species: southern right whale (Eubalaena glacialis), humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), and grey whale (Eschrichtius robustus).