TECHNOLOGIES such as artificial intelligence (AI), machine learning (ML), the internet of things (IoT), 5G, and robotics have plenty of potential in the healthcare space. However, most healthcare organizations are unable to leverage those technologies because they neither have the digital infrastructure nor the technology talent to turn their vision into real projects. "Health services have a lot to do before they can make the most of these opportunities," Waitematā District Health Board (DHB) Clinical Director Innovation Robyn Whittaker told Tech Wire Asia underscoring the fact that industry professionals aren't oblivious to the power that technology holds. Whittaker and her team at Waitematā DHB have just made it to the list of finalists in the talent accelerator category at the IDC Digital Transformation Awards. To prepare for the digital age, Whittaker's team is working on the foundational layers, digitizing data, and making it available for clinicians and researchers looking to make sense of that data.

The rise in online hate speech and the way it is reflected in the offline world is a hot topic in politics right now. The internet has given everyone a voice, which clearly has positive implications for the way citizens can publicly challenge authority and debate issues. It's fairly commonly assumed that this form of hate speech, particularly when encountered alongside other factors such as social deprivation or mental illness, has the potential to radicalize individuals in dangerous ways, and inspire them to commit illegal and violent acts. Just as terrorist organizations like ISIS can be seen using hate speech in videos and propaganda material intended to incite violence, racist and anti-Islamic material is thought to have inspired killers like Anders Breivik, who killed 69 youths in a 2011 shooting spree, and the 2019 Christchurch mosque shooting in which 51 died. So far these links between online and real-world actions, though common sense tells us they are likely to exist, have been difficult to prove scientifically.

Adcore Inc. (ADCO:TSX.V), the developer of machine-learning powered advertising technologies, reported record second quarter financials, including an increase in revenue growth of 53% year over year. Adcore uses artificial intelligence (AI) algorithms to automate online search and shopping advertising and is used by digital agencies and advertisers to enhance and maximize search engine marketing. The company also announced two major contracts for online advertising, one with the Israeli Government Advertising Agency for CA$125 million over five years, and the second with Experience Oz, Australia and New Zealand's number one site for travel experiences, with an online advertising budget of up to CA$5 million per year. "Our growth continues to outpace the market and our competitors, with yet another record quarter of revenue and earnings,-- said Omri Brill, Adcore's CEO. "Our outlook for the second half of the year, historically the stronger half of the year, remains extremely bullish and we expect to make several exciting announcements over the coming months to drive shareholder value." The firm has developed three sets of tools to assist advertising agencies and advertisers with digital media marketing. Ben Mann, founder and director of Experience Oz, stated, "Adcore is the perfect partner to take our search and shopping to the next level.

UNSW Sydney has transformed the learning experience for engineering students with an AI-infused and Teams-enriched solution while instituting reforms designed to reduce the risk of student drop outs. UNSW Sydney is one of Australia's leading universities with around 17,000 students enrolled in the engineering faculty. The large student cohort means that there can be 500 students enrolled in a class at any one time. To optimise their learning opportunity and reduce the risk of drop out, Dr David Kellermann, a senior lecturer in the school of mechanical and manufacturing engineering, has developed and deployed Microsoft Teams to promote collaboration and communication. This has been augmented by artificial intelligence and rich data analytics.

Human "exceptionalism" is for many people an unquestioned assumption. For the religious, it is a God-given fact; for humanists, it is a celebration of our unique mental capacities.

The graph represents a network of 3,948 Twitter users whose tweets in the requested range contained "futureofwork ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 28 August 2019 at 13:13 UTC. The requested start date was Tuesday, 27 August 2019 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 5,000. The tweets in the network were tweeted over the 2-day, 1-hour, 37-minute period from Saturday, 24 August 2019 at 22:22 UTC to Tuesday, 27 August 2019 at 00:00 UTC.

We propose a novel framework, learning to transfer learn (L2TL), to improve transfer learning on a target dataset by judicious extraction of information from a source dataset. Our framework considers joint optimization of strongly-shared weights between models of source and target tasks, and employs adaptive weights for scaling of constituent loss terms. The adaptation of the weights is done using a reinforcement learning (RL)-based policy model, which is guided based on a performance metric on the target validation set. We demonstrate state-of-the-art performance of L2TL given fixed models, consistently outperforming fine-tuning baselines on various datasets. In addition, in the regimes of small-scale target datasets and significant label mismatch between source and target datasets, L2TL outperforms previous methods by a large margin.

Barrister and human rights advocate Fiona McLeod, who delivered the Solomon Lecture titled Accountability in the age of the artificial, said accountability was under threat in Australia and internationally. Ms McLeod called for a robust national integrity commission. "We have settled for a'trust us or vote us out' model of democracy and a veneer of transparency resulting in a piecemeal and un-strategic approach to accountability," she said. "For example, the federal government committed to bring in a Commonwealth integrity commission after its hand was forced by independents in the last Parliament. "The original preferred model of a closed hearings, with no power of the commission to initiate inquiries, appeared to me more like a benign hall monitor issuing'don't run' notices than a body capable of balancing competing public and private interests, of driving a culture of anti-corruption throughout government, private organisations and the community."

Artificial intelligence (AI), machine learning and deep learning have become entrenched in the professional world. AI-style capabilities are being embraced and developed globally (over 26 countries/regions have or are working on a national AI strategy) for many different purposes -- from ethics, policies and education to security, technology and industry, the scope is broad and multi-faceted. If, like many others, you are unclear as to what this new terminology means, below is a diagram depicting the hierarchy of AI, machine learning and deep learning for you to consider. In healthcare, the opportunities are vast and significant. Just from a financial point of view, AI has the potential to bring material cost savings to the industry.

The days of debating if artificial intelligence (AI) will impact the music industry are over. Artificial intelligence is already used in many ways. Now it's time to consider how much it will influence how we create and consume music. Just as it does for other industries, in the music industry, AI automates services, discovers patterns and insights in enormous data sets, and helps create efficiencies. Companies in the music industry need to accept and prepare for how AI can transform business; those that won't will be left behind.