The Centre for Civil Society and Governance of The University of Hong Kong and a global tech giant recently jointly announced a request for proposals (RFP) for the company’s AR/VR Policy Research in the Asia Pacific region. This research initiative invites the region’s academic community to develop solutions-focused research to support the responsible development of augmented reality (AR) and virtual reality (VR) technologies.
This includes identifying positive approaches to address policy issues and challenges, as well as opportunities in the metaverse and augmented and virtual reality, ultimately giving people the power to build community and bring the world closer together.
With the metaverse becoming the next chapter of the internet, Meta’s vision is to have a billion people accessing the metaverse as part of their daily lives within ten years. That relies on people being in control of their experiences and feeling safe and secure. This RFP reaffirms the tech giant’s commitment to ensuring the responsible development and use of AR/VR technologies and building strong collaborations with policymakers, experts and industry partners to bring the metaverse to life.
The Director of the Centre for Civil Society and Governance stated that the RFP forms part of the Tech for Good Initiative that aims to bring scholars and practitioners together to catch up with the latest development of technologies and explore how the interplay between emerging technologies and public policy works. The Centre is committed to the attainment of a sustainable society and advanced technologies will help address some of the most critical sustainability challenges we are facing today.
The Centre for Civil Society and Governance of The University of Hong Kong and the company are inviting faculty to respond to this call for research proposals on the following topics:
The research initiative targets to award a total of 6 awards, each in the US$100,000 range funded by the firm’s XR Programs and Research Fund, a two-year US$50 million investment in programmes and independent external research to help in the effort of building the metaverse responsibly. The submission deadline is 25 July 2022, and the results will be announced on 5 September 2022.
The global augmented reality and virtual reality market, in the current year (2022), is expected to have a market size of US$37.0 billion and grow up to US$114.5 billion by 2027 within a 5-year forecast period at a market growth rate of 25.3%.
The driving factors behind this growth include increased healthcare applications of augmented reality, increased applications of augmented reality and virtual reality in retail and e-commerce, strong government funding for the facilitation of growth of the AR and VR market, partnerships between augmented reality device manufacturers and various service industries, the rise in the usage and demand for virtual reality in e-learning, medical training, increased demand of virtual reality in manufacturing divisions.
During the recently held Golden Jubilee celebration of the DSO National Laboratories (DSO) tag as the DSO50 Technology Showcase (TSC), the public was given an opportunity to have a glimpse of the five key technology domains innovations initiated by the agency in the areas of Cryptography, Cybersecurity, Miniaturised Radio Frequency and Electronics, Artificial Intelligence / Data Analytics and Unmanned Systems.
Behind the opening of this technology showcase has been 50 years of steady progress and good achievements, and I would say that after half a century, DSO is indispensable to the SAF. It is because of leveraging technology, science, manpower, and intellect that we’ve been able to overcome many, many vulnerabilities. Of course, our inherent vulnerabilities are immutable. That’s never going to change. We’re never going to be large or have more manpower than necessary. So, we’re thankful that we’ve reached this position with DSO.
– Dr Ng Eng Hen, Minister for Defence.
Dr Ng talked about how important DSO’s role in defence has been for the past 50 years and will be in the future. He said that it was a credit to the founding fathers and leaders who came after them that they saw its importance from the start.
He said that once the SAF was made, it needed the latest technology. They clearly didn’t have enough strategic depth. Singapore is a very small country with few people living there. And they realised very quickly that they needed to set up this group.
Many of these native technologies and solutions solve important operational problems and are often not available commercially. They can also be changed to meet specific and future operating needs. Most of these enabling technologies are usually hidden because they are built into systems to make them smarter and more reliable.
As Singapore’s national defence research and development organisation, DSO has the largest and most extensive technology show for guests from the Ministry of Defence (MINDEF), the Singapore Armed Forces (SAF), key public agencies, and industry partners.
The closed-door event had a unique exhibition about the DSO’s history, the capabilities it has built up over the past 50 years, and the R&D projects that MINDEF, the SAF, and the whole government will be working on in the future.
One important example is DSO’s work to make important electronic parts smaller and lighter while improving their performance in a variety of communication platforms and systems. Another important part of DSO’s solution is that it can find and stop AI that is trying to trick people by using fake news and fabricated media.
Meanwhile, Singapore recently launched its NeuSAR satellite into space under the direction of DSO. NeuSAR is a compact, high-performance satellite weighing 160 kg that has a Synthetic Aperture Radar (SAR) that is fully polarimetric. A SAR satellite “creates” photos by transmitting radio waves to the Earth’s surface and collecting the returns to create images, in contrast to optical cameras satellites that are limited to daytime and clear weather imaging circumstances.
NeuSAR is thus capable of taking images both during the day and at night, as well as in challenging weather due to dense cloud cover, precipitation, and even haze. It is a small satellite, offers consumers access to low-cost but high-quality satellite photos and is quicker, cheaper, and easier to manufacture.
The launch of NeuSAR represents a development in the Singapore space sector. It comes after the productive launches of the nation’s first satellite (X-SAT) in 2011 and its first industrial electro-optical satellite (TeLEOS-1) in 2015.
Knowing when to trust a model’s predictions is not always easy for workers who use machine-learning prototypes to help them make decisions, especially because these models are often so complex. Hence, users may use a technique known as selective regression, in which the model estimates its confidence level for each prediction and rejects if it is too confident. A human can then manually examine those cases, gather additional information, and make decisions about each one.
While selective regression has been shown to improve overall model performance, researchers at the Massachusetts Institute of Technology (MIT) and the MIT-IBM Watson AI Lab discovered that it can have a reverse impact on underrepresented groups of individuals in a dataset. With selective regression, the model’s certainty grows, as does its chance of making the correct prediction, but this does not always happen for all subgroups.
A model predicting loan approvals, for example, may make fewer errors on average, but it may make more incorrect predictions for Black or female applicants. One reason for this is that the model’s confidence measure was trained on overrepresented groups and may be inaccurate for underrepresented groups.
After identifying the problem, the MIT researchers developed two algorithms to address it. They demonstrate, using real-world datasets, that the algorithms reduce performance disparities that have harmed marginalised subgroups.
Regression is a method for estimating the relationship between a dependent and independent variable. Regression analysis is commonly used in machine learning for prediction tasks such as predicting the price of a home based on its features (number of bedrooms, square footage, etc.) With selective regression, the machine-learning model has two options for each input: make a prediction or abstain from making a prediction if it lacks confidence in its decision.
When the model abstains, the coverage—the portion of samples on which it bases predictions—decreases. The model’s overall performance ought to increase by restricting its predictions to inputs about which it is quite certain. However, this can potentially accentuate dataset biases, which happen when the model lacks sufficient data from subgroups. Underrepresented people may make mistakes or poor forecasts because of this.
The goal of the MIT researchers was to guarantee that, as the performance for each subgroup improves with selective regression, so does the overall error rate for the model. This threat is identified as a monotonic selective risk. To deal with the issue, the researchers designed two neural network algorithms that impose this fairness criterion.
One algorithm ensures that the model’s features contain all important information regarding sensitive factors like race. Sensitive qualities can’t be used for judgments owing to laws or policies. The second procedure uses calibration to ensure the model generates the same prediction for an input, regardless of sensitive properties.
The researchers tested these algorithms on high-stakes real-world datasets. A crime dataset uses socioeconomic data to forecast the number of violent crimes in communities. An insurance dataset predicts total annual medical expenses invoiced to patients. Both databases have personal information.
Implementing their techniques on top of a standard machine-learning method for selective regression reduced inequities by lowering error rates for minority groupings in each dataset. This was done without considerably increasing errors.
The researchers want to adapt their answers to other challenges, such as predicting property values, student GPA, or loan interest rate. To prevent privacy risks, they intend to use less sensitive information during model training.
They also want to enhance selective regression confidence estimates to avoid scenarios where the model’s confidence is low, but its prediction is true. This could reduce human workload and simplify decision-making.
A project team led by the Singapore General Hospital’s (SGH) Nursing Division has collaborated with a company that customises its PPE for hospital use. The hands-free solution uses artificial intelligence (AI) technology and the cloud to provide automated guidance and checks in accordance with SGH’s stringent PPE protocol.
PPE is the first line of defence against infectious diseases, according to Ang Shin Yuh, Deputy Director, Nursing Division, SGH, but it is only effective when worn correctly. Nurses assigned to the Community Care Facility at Singapore Expo in 2020 to care for COVID-19-positive migrant workers had to double-check each other’s PPE before entering the Halls.
“We also had to do a manual audit every single day to ensure compliance on the ground. It was labour intensive, and unsustainable. That realisation pushed us to think about automating the process using artificial intelligence and image recognition,” says Deputy Director Shin Yuh who also first mooted the project.
SGH is a not-for-profit institution that is wholly owned by the Singapore government. It is the flagship hospital of the public healthcare system that has identified problems and is actively working to resolve them.
Thus, SGH strives to ensure that all staff and visitors are properly wearing their PPE before entering an isolation facility. The nursing project team, on the other hand, had to first improve the solution to recognise Asian features and skin tones before tailoring it to the Hospital’s needs, including the types of PPE used.
The hospital was an ideal partner for deploying the cutting-edge PPE to train and monitor staff on infection control and prevention procedures. Hospitals save lives, and SGH is one of the institutions with innovative practices and improving nursing practises. This technology has now been fine-tuned and is ready to assist even more medical teams across Singapore and the region.
The customised solution consists of three modes – PPE Buddy, Train and Practice, and Visitor – that have been individually validated by the team with approximately 200 staff and visitors. When installed, the solution converts a tablet into a digital mirror that can be easily mounted on a tripod and carried into any area of need, or on any flat surface, such as a wall, with easy access to PPE supplies.
Using cutting-edge imaging technology, the system works hands-free to study clinicians and ensure that their PPE is properly applied. This improves infection control and lowers the risk to staff and patients.
The technology can be integrated into both existing and new infrastructure at the hospital. In the future, the solution can be further customised for disease-specific protocol, contact tracing, and image recognition for staff access. When the next pandemic strikes, SGH will be in the best possible position.
Meanwhile, SGH pioneers the 3D-printed chest implants in the region. Patients with moderate to severe symptoms may opt for the Nuss procedure, which is a minimally invasive surgery. The SGH was able to print the bioresorbable implant in collaboration with other medical institutions by using CT scan images of the patient processed by the SGH’s Department of Diagnostic Radiology for 3D printing. The fit was determined by placing a prototype model of the implant on SGH-printed chest wall models.
Currently, 3D models printed by SGH allow surgical teams to practise complex cases as well as pre-size and pre-shape implants prior to surgery. The SGH will capitalise on the potential of 3D printing and expand its use to improve patient care, beginning with the opening of its very own 3D printing Centre at the end of this year.
Under a new NSW Government program, NSW is working to push forward its place as a world leader in bushfire technology commercialisation and position itself for the international export of innovative bushfire solutions. The region’s Minister for Science, Innovation and Technology stated that the Bushfire Commercialisation Fund will help innovators translate their cutting-edge research into practical solutions that will improve bushfire detection, preparation and response.
Mr Henskens said that whether it’s artificial intelligence, drones or predictive mapping, the need is to commercialise disaster-resilient practical solutions, not just in NSW, but across Australia and around the world. By investing in local talent and their innovative research, the economy can be grown, jobs can be created and products can be developed that secure a brighter future for NSW.
A total of AU$ 16 million over three years has been allocated, with the first round of funding offering grants of between AU$ 200,000 and AU$ 8 million to individuals, companies, research institutions and universities, to help them commercialise their research.
The NSW Chief Scientist & Engineer said the program is the second initiative being rolled out under the Bushfire Response R&D Mission. He noted that the programme has been modelled on the highly successful Medical Devices Fund and Physical Sciences Fund, both of which have helped to scale businesses, attract investment from private capital and build the capability of NSW’s small-to-medium enterprises in key industry sectors.
About the Bushfire Response R&D Mission (BRM)
The NSW Bushfire Response R&D Mission (BRM) is the first NSW R&D mission recommended by the Turning ideas into jobs: Accelerating research & development in NSW Action Plan. The Action Plan recommended that the BRM focus on improving planning, preparations for and responses to bushfires – aligning with recommendation five of the recent NSW Bushfire Inquiry.
The NSW Government will direct $28 million into research and development and the promotion of new and emerging industries and technology to better prepare the state for future bushfires.
Based on the positive impact of the current innovation network and innovation programs, it is expected the BRM will generate roughly 200 new and sustainability technology jobs per year, equivalent to 2,000 jobs over the next decade.
The BRM has four objectives:
The most likely replacement for present silicon-based solar photovoltaics is a family of materials called perovskites. They have the potential for panels that are far lighter and thinner, which might be produced at ultra-high through placed at room temperature rather than at hundreds of degrees, and which are also less expensive and simpler to carry and install.
Researchers are working on encapsulating the perovskite in various protective materials to protect it from exposure to air and moisture. They are also researching the precise mechanisms that cause that degradation in the hope of developing formulations or treatments that are more inherently robust. A key discovery is that the breakdown is largely due to a process known as autocatalysis.
With this, researchers have developed a machine-learning approach that can significantly streamline the search for promising new candidate compositions for perovskites. This process is analogous to seeking a needle in a haystack. This novel strategy could expedite the creation of new alternatives.
While most machine-learning systems utilise raw data such as measurements of the electrical and other properties of test samples, they typically do not incorporate human experiences such as qualitative observations made by experimenters of the visual and other properties of test samples, or information from other experiments.
Consequently, the researchers devised a mechanism to include such external information into the machine learning model, utilising a Bayesian Optimisation-based probability component. This new system based on an innovative approach to machine learning could accelerate the development of optimised production methods and contribute to the realisation of the next generation of solar power.
This advanced technology, developed by the Massachusetts Institute of Technology and Stanford researchers enables the incorporation of data from previous trials and information based on the personal observations of experienced workers into the machine learning process.
It has improved the accuracy of the results and has already led to the production of perovskite cells with an energy conversion efficiency of 18.5 per cent, which is now viable for the current market.
On the other hand, manufacturing perovskite-based solar cells necessitate the simultaneous optimisation of a dozen or more factors, and that’s just one of many possible manufacturing methods.
Perovskites have a high tolerance for structural flaws, which is one of their major advantages. It can function well even with numerous imperfections and impurities, unlike silicon, which requires extremely high purity to function well in electronic devices.
However, at least a dozen variables may impact the outcome of this procedure. It is impossible to evaluate every conceivable combination of these factors through testing; hence, machine learning was required to lead the experimental procedure.
Thus, most of the existing research on machine-learning-driven perovskite PV fabrication focuses on spin-coating, a lab-scale technique and only a few organisations have the expertise in both engineering and computation to drive such advances.
Furthermore, perovskites continue to show enormous potential, and several businesses are now preparing to commence commercial manufacturing, but durability remains their greatest challenge. Perovskites degrade considerably faster than silicon solar panels, which preserve up to 90 per cent of their power production after 25 years.
Initial samples lasted only a few hours, then weeks or months, but current formulations have useful lives of up to a few years, making them acceptable for applications where durability is not important. The primary goal of the researchers was to accelerate the process, so it required less time, fewer experiments, and fewer human hours to develop something that is usable right away, for free, for the industry.
The director general of the Intellectual Property (IP) Office of the Philippines (IPOPHL), Rowel S. Barba, called for more support to maximise the benefits of IP in establishing a cohesive digital economy during the recently held 63rd Assemblies of the Member States of the World Intellectual Property Organisation (WIPO).
“We underscore the importance of strengthening the ASEAN IP systems through digital transformation and are working closely with all stakeholders to accelerate these changes in response to the call at the 53rd ASEAN Economic Minister Meeting in 2021,” says Director General Rowel, who is also the chair of the ASEAN Working Group on IP Cooperation (AWGIPC).
The fourth industrial revolution, the digital economy, and even the economic recovery have all been addressed in initiatives and mid-term plan frameworks by numerous ASEAN sectoral groups, he continued.
These strategic plans’ IP clauses demonstrate how highly IP is regarded for encouraging a creative and inventive culture in the digital world. Along with these regional initiatives for digitalisation, the AWGIPC will lead efforts to enhance the ASEAN IP Portal in support of the ASEAN cross-pillar digital activities.
The ASEAN member states have the option of modernising the 1995 ASEAN Framework Agreement for Intellectual Property Cooperation (AFAIPC) into a “modern, up-to-date, forward-looking agreement, relevant to industry and more responsive to regional and global changes.”
The WIPO-ASEAN Regional Technical Cooperation Implementation and Monitoring Plan for Intellectual Property (RTCIP) 2019–2025 is one illustration. The RTCIP functions well as a framework for tracking WIPO’s actions connected to ASEAN objectives because it covers 37 deliverables as part of the ASEAN’s IP Rights Action Plan 2016–2025.
The IPOPHL is looking forward to better engagement with WIPO and its member states to achieve the goal of accelerating the completion of deliverables under the ASEAN IPR Action Plan 2016-2025, with 75 per cent of the deliverables completed by March 2023. The agency has also acknowledged the WIPO’s Singapore Office and Division for Asia and the Pacific (WSO).
WSO has continually supported the ASEAN region through its capacity-building programmes for ASEAN IP offices, its online IP courses made available to ASEAN businesses, and its collaboration with IP practitioners and dialogue partners that provide technical assistance on IP in the region.
In the meantime, the agency has partnered with extensive research being undertaken by the Korean Institute of Patent Information (KIPI) to further automate the IPOPHL services. The study will provide recommendations for a medium- to long-term plan for IPOPHL to automate the operations that are identified.
To provide a value-added information infrastructure for Korea’s intellectual property, the Korean Intellectual Property Office (KIPO) established a related public institute known as KIPI. It is a specialist non-profit organisation that provides information on industrial property rights.
The most recent cooperation with KIPI helps IPOPHL implement its six-point BRIGHT Agenda. This shows how crucial partnerships are to future-proofing the agency’s services, especially as the country continues to support stakeholders in maximising the IP system for their pandemic recovery.
In November 2022, the IP automation consulting project between IPOPHL and KIPI will be finished, with the possibility of continuing cooperation with the Korean government.
All G20 member nations, in particular the delegates of the Digital Economy Working Group (DEWG), have a common goal of employing digital technology to promote the global economic recovery from the Covid-19 pandemic.
“Let’s together strengthen synergies and push for an inclusive, empowering and sustainable world recovery that can be carried out together,” says Johnny G. Plate, Minister of Communications and Information.
He stated that the DEWG meeting was characterised by numerous vigorous discussions. Despite these disparities, the G20 countries share a common goal, which is to promote global economic recovery using digital technologies. He asked all parties to support the DEWG series of events during Indonesia’s G20 chairmanship.
With this assistance, it is believed that Indonesia will accomplish two successes: success in terms of the discussion’s content and success in demonstrating the immense potential of super priority tourism locations as the event’s host.
In the meantime, Minister Johnny is optimistic that Indonesia will become a digital hub in Southeast Asia by 2024 if it has a sufficient digital infrastructure base. He stated that the Indonesian government is committed to achieving its goal of becoming the digital hub of ASEAN through the construction of digital infrastructure.
Massive upstream and downstream infrastructure development is conducted so that it can reach all regions of the country, and the government has supported the development of digital talent or digital human resources (HR). The inclusion of digital HR development in the G20’s agenda of priorities demonstrates not only the significance of digital HR development on a national level but also on a worldwide scale.
The Minister stated that they are concentrating on constructing digital downstream infrastructure in the form of cloud-computing-based national data centres in four sites, beginning in the Cikarang region of the West Java Province this year. In addition, he wants the private sector to develop data centres or engage in the construction of downstream digital infrastructure because the potential for growth is so great.
As of now, per capita data consumption in Indonesia is still very low, around 1 watt per capita, implying that the potential is very large when compared to neighbouring countries such as Singapore, where it is 100 watts per capita.
Several key components of developing digital talent were previously reported by OpenGov Asia. One of these is the importance of enlisting the help of stakeholders to adequately address the shifting dynamics of today’s global digital talent requirements.
Reasoning, problem-solving, and ideation, as well as analytical thinking and innovation, active learning and learning strategies, complex problem-solving, critical thinking and analysis, creativity, originality, initiative, leadership, and social influence, are all part of the skill set. Technology use, monitoring, and control, as well as technology design and programming, are also covered.
Minister Johnny also emphasised policy advancements in digital education management, stating that the five interconnected tactics are intended to help students improve their digital literacy. He mentioned the World Bank Group’s Five Strategies of Digital Skills Country Action Plan (DSCAP) as a resource or manual for digital educational institutions.
In addition, the Minister of Communication and Information emphasised the role of women in the realm of digital transformation. He stated that women will make up only 35 per cent of all STEM (Science, Technology, Engineering, and Mathematics) majors in the last few years and only 3 per cent of female students are enrolled in Information and Communication Technology (ICT) academic programmes.
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