Optus has selected Nokia’s IMPACT Internet of Things (IoT) platform to provide device management and data collection capabilities to their customers. 

Both companies have agreed on a joint go-to-market strategy to bring IoT solutions to Optus customers across multiple industry segments in Australia.

Nokia’s industry leading IoT Device Management Platform (DMP) will enable Optus to provide its customers with simple access to Narrow Band-IoT device data, from low power devices, and remote device management at scale. This can be done regardless of device type. Nokia and Optus will work together to help create smart cities and support enterprise customers across industries, including mining, utilities and transportation. 

Anticipated industry applications include cost effective waste management, supply chain optimization, logistics management and scene analytics for improved safety and security.   

The alliance builds on Nokia’s longstanding relationship with Optus. Nokia is working collaboratively with the operator to manage and maintain its network infrastructure. The two companies launched Australia’s first 5G commercial services in early 2019, making Optus the first operator globally to deploy Nokia’s FastMile 5G indoor gateway in a live network. Nokia and Optus also successfully launched a 5G Fixed Wireless Access service using the 5G New Radio standard.

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CERA researchers have contributed to a new roundtable report by the Australian Academy of Health and Medical Sciences on the role artificial intelligence could – and should – play in the future health landscape.

Ophthalmology is at the forefront of the artificial intelligence (AI) revolution in healthcare.

Powerful imaging technologies combined with deep learning algorithms are transforming our ability to screen for eye diseases, with some new tools now able to analyse images of the retina at least as well as doctors.

A new report published by the Australian Academy of Health and Medical Sciences (AAHMS) is now calling for a national conversation about the opportunities and challenges that AI technologies bring to the future of Australian healthcare.

CERA Deputy Directors Professor Robyn Guymer and Associate Professor Peter van Wijngaarden were among 34 experts across health, technology, academia, industry and government who took part in a roundtable meeting exploring these issues.

The resulting report, Artificial Intelligence in Health: Exploring the Opportunities and Challenges, concludes that if we are to successfully harness the potential value of intelligent health technologies, we need to determine a national pathway for its ethical and responsible use, and how the current health care model will need to adapt to technological changes and their impact on healthcare delivery.

CERA Deputy Directors Professor Robyn Guymer and Associate Professor Peter van Wijngaarden contributed to the roundtable report.

At CERA, AI is playing an increasingly significant role in research innovation. CERA researchers are demonstrating that AI tools have the potential to make eye screening more accessible and convenient for patients, and to help doctors predict the progression of eye disease.

“New technologies have the potential to detect the early signs of disease – without the need to attend an eye clinic – and determine who needs to be referred to an eye care professional for a more detailed assessment,” says Associate Professor van Wijngaarden.

“Whilst not yet in mainstream use, research studies are revealing the potential to test patients at locations that suit them – in their own home, a photobooth in a shopping centre or during a visit to another health care provider, such as a GP.”

In ophthalmology and across the healthcare industry, judicious use of AI technologies could potentially allow for more cost-effective care, reduce stressful workloads for clinicians, and provide more flexibility and empowerment for patients.

Challenges to consider for the future

While AI technologies offer incredible potential, the AAHMS report also reveals the complexity of this emerging landscape.

This includes challenges around ensuring validity, safety, ethics and accountability for decision-making.

“Optimism about the potential of AI to enhance access to care and convenience for patients needs to be tempered by the limitations of the technology and the readiness of patients and health systems for its use,” says Associate Professor van Wijngaarden.

“Acceptance of AI by patients and care providers, its performance in real world clinical settings and its place alongside medical professionals all need to be evaluated.”

Associate Professor van Wijngaarden says a broad range of perspectives need to be considered to determine a pathway.

“The report highlights that it is high time to initiate a national conversation about how best we should use AI in healthcare to ensure that we are optimally placed to benefit from the safe and appropriate use of this technology.

“Broad-based consultation involving consumers, regulators, researchers, care providers, technology developers and governments are needed.”

Read the full report, Artificial Intelligence in Health: Exploring the Opportunities and Challenges, from the Australian Academy of Health and Medical Sciences.

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Monash University and Eastern Health’s Turning Point are using a $1.2 million (AUD) grant from Google to address major mental health challenges in society.

A joint project between Monash University and Eastern Health’s Turning Point, are using Artificial Intelligence (AI) to streamline the coding of national suicide-related ambulance data to help paramedics respond more effectively and ultimately prevent potential suicide rates.

Ambulances are often the first point of contact in a crisis, making ambulance clinical records a unique data source to help inform suicide prevention efforts. In partnership with the Population Health team at Turning Point, Monash Faculty of Information Technology (IT) researchers are implementing specialised machine learning technologies to filter through ambulance data and categorise suicide-related mental health cases.

As the only Australian grant recipients of the 2019 Google AI Impact Challenge, the project will annotate a large database of clinical records into categories such as suicide attempt, suicidal ideation and self-injury without suicidal intent. This task is currently carried out by human annotators who interpret individual paramedic clinical records and categorise it accordingly.

By using the data that has been previously annotated, the machine learning model will be able to augment and accelerate the challenging work of categorising and filtering through tens of thousands of records per month.

A key outcome of the project has been ensuring greater efficiency and accuracy in data classification. With preliminary studies showing that two-thirds of the data processing can be eliminated, potentially reducing staff workload by over 30 per cent, thereby freeing them up for other tasks, and limiting their exposure to explicit content.
Implementing this machine learning model will result in the timely and cost-effective identification and coding of suicide-related ambulance data, to better inform policy and public health responses for suicide prevention.

By accurately classifying data records, researchers will be able to determine behaviours and relationships associated with certain classifications. For example, how self-harm incidents can relate to other factors such as violence, drug use and socioeconomic status.

AI project lead Wray Buntine, Professor of Data Science and AI in the Faculty of IT, said the project was driven by the University and Google’s shared commitment to social good.

“The coaching and support we’ve received through the Google AI Impact Challenge has been invaluable and amplified our project’s overall impact. The interactive sessions we’ve had with members of Google’s Emerging Tech Design team have allowed us to work with international leaders across the fields of people-centred AI. Through our shared values, we’re committed to using IT for social good,” Professor Buntine said.

By leveraging Google’s expertise and tools, researchers have been able to explore new ways of tackling a major societal challenge.
Program Manager at Google.org, Mollie Javerbaum, said the project is a great example of how emerging AI technology can be leveraged to create positive social impact while advancing the AI ecosystem.

“The Monash University and Turning Point teams have continued to make meaningful strides towards improving their suicide monitoring system through the application of AI,” Ms Javerbaum said.

Turning Point is a national addiction treatment centre, dedicated to providing high quality, evidence-based treatment to people adversely affected by alcohol, drugs and gambling, integrated with world-leading research and education.
Turning Point Director and Monash University’s Professor of Addiction Studies and Services, Dan Lubman, believes the initiative has the potential to make a positive impact across the globe – and set international standards in supporting suicide prevention efforts.
“The project will uncover critical suicide trends and potential points of intervention to better inform policy and public health responses. The technology we’re developing will create opportunities for adoption internationally,” Professor Lubman said.
“We’re already thinking of new ways to present our latest results to policymakers so that they can more quickly respond to merging issues,” said Dr Debbie Scott, Strategic Lead of Population Health at Turning Point.

Monash and Turning Point researchers were among other Google AI Impact Challenge grantees presenting at the Google AI Impact Challenge Summit in San Francisco last week. Positioning Monash University and Eastern Health’s breakthrough research on a global stage.

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Google has included the prime supporter of its UK-based DeepMind man-made reasoning examination unit to its very own AI group.

Mustafa Suleyman affirmed the news on Twitter on Thursday, saying that he would join Google approach boss Kent Walker and Jeff Dean, the senior VP of Google AI, in January.

“Following a great decade at DeepMind, I’m eager to declare that I’ll be joining @Kent_Walker, @JeffDean, and the awesome group at Google to chip away at circumstances and effects of applied AI advancements,” Suleyman said in his tweet. “Can hardly wait to get moving! More in Jan as I start the new position!”

Suleyman will be taking a shot at AI strategy issues for Google, an organization agent revealed to Business Insider. The delegate didn’t state what Suleyman’s title will be.

In tweets, both Walker and Dean invited Suleyman to Google.

In the meantime, in a blog entry, DeepMind CEO Demis Hassabis lauded Suleyman’s work with the unit. Google and parent organization Alphabet are progressively consolidating DeepMind’s AI work into their different divisions, thanks in huge part to Suleyman’s endeavors, he said.

“Mustafa assumed a key job over the previous decade getting DeepMind off the ground, and propelled a progression of imaginative joint efforts with Google to diminish vitality utilization in server farms, improve Android battery execution, advance Google Play, and discover approaches to improve the lives of patients, medical attendants, and specialists the same,” Hassabis composed.

Suleyman likewise helped initiate the organization’s questionable wellbeing division. Two years prior, that division was found to have inappropriately acquired access to the wellbeing records of 1.6 million UK patients.

After Suleyman declared an impermanent leave from DeepMind recently, there was a theory he may stop the organization and Google through and through. That move corresponded with Google’s declaration that it would ingest some portion of DeepMind’s wellbeing centered tasks into its own more extensive social insurance unit, Google Health.

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Organisations in Australia and Singapore are among the most advanced in the Asia-Pacific (APAC) region in making data central to their business through the widespread use of data analytics, a new survey has found.

According to the Data Readiness Index (DRI) developed by technology analyst firm IDC, Australian firms earned the highest average score of 3.54, followed by those in Singapore with a score of 3.52.

The Tableau commissioned study also placed organisations in three bands – leading, developing, and lagging – based on their ability to harness data to achieve key business outcomes.

Just 20% of the 700 organisations in Australia, China, Hong Kong, India, Japan, Singapore and South Korea that took part in the study made it into the leading band, with a majority in the developing (66%) and lagging (14%) categories.

Singapore had the most organisations (52%) in the leading band, where they tend to do better in areas such as governance, collaboration and employee data skills. Such organisations produced an average of 90% better business outcomes than laggards, the study revealed.

“Organisations in APAC are at an inflection point of their digital transformation. While many recognise the critical role data plays in this strategy, they are struggling to become truly data-driven,” said JY Pook, senior vice-president of Tableau APAC.

“In order to remain competitive and realise the business benefits [of data analytics], organisations need to adopt a holistic and tailored approach to drive data readiness,” he added.

Chris Marshall, associate vice-president for analytics, big data and artificial intelligence at IDC APAC, said the DRI captures an organisation’s ability to harness data to achieve its key performance indicators.

“We see big differences in DRI across functions and industries throughout Asia. The factors that drive DRI like skills, leadership, technology, governance and process also vary widely. These reveal some valuable lessons for business leaders about the initiatives to prioritise in particular circumstances,” he added.

This was demonstrated during an industry event in July 2019 where organisations are clearly not at the same stage in turning data into critical assets. Some are still ascertaining the business value of their data, while others are already using data to improve their operations.

Speaking at the ConnectGov Leaders Summit in Edinburgh, Singapore Exchange (SGX) vice-president and head of data science and visualisation Sigrid Rouam said just 5% of the company’s data is being monetised, while the global average among its peers is 30-40%.

Rouam said SGX is now looking to grow that figure by providing new data services, such as data visualisation, to external customers, effectively extending the value of its data beyond internal use.

At SP Digital, the digital services arm of Singapore utility provider SP Group, data has always been critical to its operations, enabling it to control and manage the country’s critical energy infrastructure.

About three years ago, the company embarked on a digital transformation initiative, which, among other areas, includes building a data lake to house all its data, according to SP Digital CEO Chang Sau Sheong.

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The Commonwealth Bank of Australia (CBA) has built a Customer Engagement Engine it has touted as powering customer experience through the use of artificial intelligence (AI) and machine learning.

“[It] is an advanced system which combines AI, machine learning, and our customer data to continuously optimise and prioritise across all of the available messages, alerts, conversations, and communications we can have with our customer at any given time, across all of our channels,” CBA chief analytics officer Andrew McMullan said.

“And all of that in real time.”

Speaking with media at the launch of the bank’s new app, McMullan said CBA runs over 200 machine learning models on top of 157 billion data points. He said these models are continuously “optimising, prioritising, and returning the next best personal message to our customers as they interact with us across all channels”.

McMullan said the bank has invested a lot in automated machine learning capability.

“So maybe there’s a message that we want to test with some of our customers, in one of the assets within the mobile app, we’ll push that message live and in the background we’ll switch on one of our advanced machine learning models,” he explained.

“As our customers engage with that message, maybe a click through a ‘yes, please’, or ‘no, thanks’, the machine learning model in the background is learning from that to really more accurately predict which type of customers really enjoy experiences with that particular message.”

When CBA is happy with the performance of the model, McMullan said it would switch that conversation on and add it to the system to become another message that will be shared with customers.

“As I navigate my way through the experiences in the mobile app, each of the assets has been personalised by making a call to the Customer Engagement Engine to say, ‘What’s the next best message to determine this particular communication?'”

Providing a scale of the system, McMullan said that each day the bank’s applications make over 20 million calls to the Customer Engagement Engine to return personalised messages.

Over the next 12 months, the bank expects it will have the opportunity to deliver 3 billion personalised messages to its customers.

“One of my favourites is our Smart Alerts … on credit cards. We’re constantly monitoring our customer data and if a customer hasn’t paid the minimum amount or paid down their credit card balance, three days out from being due, we will send them an alert,  make it really easy to click through to make a payment,” McMullan said, offering an example of how the bank is using the Customer Engagement Engine.

“If you haven’t done that and your payment is due in two days, another alert. One day, same day, even one day’s grace. The last 12 months alone, we’ve built the ability to send over 20 million alerts to our customers to help them avoid fees and charges on credit cards.”

Another example is how CBA is trying to help customers manage their bills.

McMullan said that by using natural language processing, the bank is attempting to better understand all the regular payments and bills that a customer has in order to identify any anomalies.  

He shared a personal anecdote where he was on a monthly subscription that had a price hike.

“You can see [from that] example there are hundreds of opportunities for us to just notify our customers and let them know that something has changed, and then they can decide what to do from there,” he said.

The final example McMullan shared was helping the bank by using the system during the application process.

“Our customers begin an application and for many reasons they drop out. Maybe they haven’t submitted the document, finished entering a specific field, or even signed the document. The Customer Engagement Engine is constantly scanning over that, identifying exactly what the customer needs to do next, and we’ll reach out to the customer to let them know what it is that they need to do to continue the application process,” he explained.

“We are determined to improve the financial wellbeing of our customers and  communities.”

According to McMullan, for customers that have been receiving the personalised messages, the net promoter score is up to six points higher than it is from customers that don’t receive messages.

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