Oceania


Interview with Alessandra Rossi: an insight into the RoboCup virtual humanoid league

AIHub

Alessandra Rossi is a member of both the technical and organising committees for the RoboCup Humanoid League. We spoke to her about the Humanoid League Virtual Season, which concluded with the grand final of the virtual soccer competition, and a three day workshop. The Humanoid League Virtual Season (HLVS) has been driven by two main core motivations: firstly to allow teams to have support for continuous testing while making progresses and changes to their software, and secondly, to keep the teams connected throughout the year, thus strengthening the community and collaboration between teams. We wanted to let teams use the longer periods between games, and the continuous games throughout the year to test novel approaches, with less risk, and to aid their success in the overall tournament. In addition, this way, teams can thoroughly analyse the collected data between games, and make informed decisions on how to improve and implement their approaches for the following match.


The use of Augmented Reality in Real Estate is no longer a gimmick

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Technology has completely infiltrated the built environment. Between IoT connectivity in buildings, indoor wayfinding and virtual tours, real estate is no longer the tech-averse industry it once was. In the context of digitization, there are new uses for Augmented Reality (AR). The technology has evolved from a marketing gimmick to a solid strategy for asset managers to improve their built environments. The premise of AR technology is the real-time integration of digital information to "augment" the user's physical experience.


Data on Machine Learning Described by Researchers at University of New South Wales (Learning from machines to close the gap between funding and expenditure in the Australian National Disability Insurance Scheme): Machine Learning

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By a News Reporter-Staff News Editor at Insurance Daily News -- New research on artificial intelligence is the subject of a new report. According to news reporting originating from Canberra, Australia, by NewsRx correspondents, research stated, "The Australian National Disability Insurance Scheme (NDIS) allocates funds to participants for purchase of services." Our news reporters obtained a quote from the research from University of New South Wales: "Only one percent of the 89,299 participants spent all of their allocated funds with 85 participants having failed to spend any, meaning that most of the participants were left with unspent funds. The gap between the allocated budget and realised expenditure reflects misallocation of funds. Thus we employ alternative machine learning techniques to estimate budget and close the gap while maintaining the aggregate level of spending. Three experiments are conducted to test the machine learning models in estimating the budget, expenditure and the resulting gap; compare the learning rate between machines and humans; and identify the significant explanatory variables."


Artificial intelligence tool identifies lung cancer risk

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As artificial intelligence and machine learning technologies continue to be developed, they may become powerful tools in many fields, including that of medicine. AI, complementing human experience and judgement, has already shown promise as a prognostic tool. Recent research using an AI program to help identify, from the results of chest scans, the risk of lung cancer is an example of the technique in action. Lung cancer is the second most common form of cancer worldwide, according to the World Cancer Research Fund. In Australia, it is the leading cause of cancer deaths and Cancer Australia estimates lung cancer accounted for 17.7% of all deaths from cancer in 2021.


Let's talk robotics with Tom Caska -- EXAPTEC

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Tom is also a co-inventor of an advanced 3D flight navigation algorithm for drones which is being utilised in new software applications for Aerologix. Tom guest lecturers at one of Australia's top universities – The University of New South Wales, teaching subject matter on Unmanned flight, he also holds a position on a government subcommittee dedicated to developing rules and regulations for unmanned aerial vehicles. Tom's passion for disruptive technology is infections, he is always looking for new challenges, especially drone tech and IoT. Tom has a very successful track record of establishing, executing and delivering large complex technical projects, Tom recently set up the largest drone network in Australia to monitor 1700 km of coastline to enhance swimmer safety. Tom enjoys complex problem solving and welcomes the challenge of empowering team members and creating new innovative ways to solve real-world problems. He has a high passion for life and enjoys a healthy lifestyle, and loves adventure sports such as kitesurfing, mountain biking when time permits.


UK fines Clearview AI £7.5M for scraping citizens' data

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Clearview AI has been fined £7.5 million by the UK's privacy watchdog for scraping the online data of citizens without their explicit consent. The controversial facial recognition provider has scraped billions of images of people across the web for its system. Understandably, it caught the attention of regulators and rights groups from around the world. In November 2021, the UK's Information Commissioner's Office (ICO) imposed a potential fine of just over £17 million on Clearview AI. Today's announcement suggests Clearview AI got off relatively lightly.


How AI can help the world fight wildfires

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The threat of wildfires has never been greater than it is today. In recent years, countries around the world – from the US, Argentina and Brazil to Italy, Greece and Australia – have been gravely affected by wildfires. This has resulted in many human and animal deaths, as well as the loss of millions of hectares of forests. And wildfire risks continue to grow – a recent UN Environment Programme report warns that the number of wildfires will rise by 50% by 2100 and governments are not prepared.


Using Data Science To Revolutionize Geological Logging

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The University of Western Australia (UWA) and Rio Tinto Iron Ore (RTIO) have entered into a four-year, $6.1 million research partnership to develop innovative data science solutions (artificial intelligence) for automated geological logging to improve mining practice. The partnership, which follows more than 10 years of collaboration between UWA's data science team and RTIO, will employ five full-time researchers and provide training opportunities for a number of industry-driven PhD programmes. Dr Daniel Wedge, from (CDG) in UWA's School of Geosciences, said UWA's expertise will be resorted to help RTIO's mine geology team tackle the challenge of objective well geological materials. "Until recently, geologist's specialists had to manually interpret and document material found in core samples, a process that was time-consuming and challenging," Dr Wedge said. "Our project can use artificial intelligence: machine learning, pc vision, spacial modelling and improvement techniques to integrate disparate borehole information, together with analysis, imagery, geochemical and natural science informationalong side chemical analysis, imagery, geochemical and earth science info, to."RTIO head Dr. Angus McFarlane said the past partnership between UWA and RTIO has led to the commercialisation of UWA's automated downhole image analysis software and three joint patent applications for RTIO-driven machine learning-based geological modelling.


Lead Data Scientist

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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. Q-Telco is the new joint venture between Quantium and Telstra to unlock the full potential of data and AI for Telstra and its customers. We'll do this by combining our market leading data science and AI capabilities with Telstra's customer, product and network data assets. This new partnership will not only provide personalised and data-enabled products and offers for Telstra's customers, but it will also embed proactive and predictive AI and machine learning across Telstra's core business.


How machine learning is helping patients diagnosed with the most common childhood cancer

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New software developed by Peter Mac and collaborators is helping patients diagnosed with acute lymphoblastic leukemia (ALL) to determine what subtype they have. ALL is the most common childhood cancer in the world, and also affects adults. "Thirty to forty percent of all childhood cancers are ALL, it's a major pediatric cancer problem," says Associate Professor Paul Ekert from Peter Mac and the Children's Cancer Institute, who was involved in this work. More than 300 people are diagnosed with the disease in Australia each year, and more than half of those are young children under the age of 15. Determining what subtype of ALL a patient has provides valuable information about their prognosis, and how they should best be treated.