Oceania
Machine Learning in Insurance: Nature Abhors a Straight Line...What About Actuaries? - DataRobot
Colin Priest is a Fellow of the Institute of Actuaries of Australia and has worked in a wide range of actuarial and insurance roles, including Appointed Actuary, pricing, reserving, risk management, product design, underwriting, reinsurance, relationship management, and marketing. Over his career, Colin has held a number of CEO and general management roles, where he has championed data science initiatives in financial services, healthcare, security, oil and gas, government and marketing. He frequently speaks at various global actuarial conferences. Colin is a firm believer in data-based decision making and applying machine learning to the insurance industry. He is passionate about the science of healthcare and does pro-bono work to support cancer research.
How artificial intelligence could affect your job
Tesla CEO Elon Musk has been warning about the risks of artificial intelligence and machine learning for some time now. The billionaire has said that developments in robotics will lead to disruption in the job market. Boston-area economists concluded earlier this year that human wages decline when robots are introduced. Jobs that are repetitive and can be taken over by AI like manual testing, infrastructure management, BPO and system maintenance will likely decline over the next five years. Some tech jobs could see the biggest impact from AI.
Comparing Distance Measurements with Python and SciPy
Clustering, or cluster analysis, is used for analyzing data which does not include pre-labeled classes. Data instances are grouped together using the concept of maximizing intraclass similarity and minimizing the similarity between differing classes. This translates to the clustering algorithm identifying and grouping instances which are very similar, as opposed to ungrouped instances which are much less-similar to one another. As clustering does not require the pre-labeling of classes, it is a form of unsupervised learning. At the core of cluster analysis is the concept of measuring distances between a variety of different data point dimensions.
Artificial intelligence provides adviser advantage
Artificial intelligence is reshaping wealth management and a digital infrastructure specialist believes financial advice practices will greatly benefit from implementing AI in the workplace. Dimension Data believes artificial intelligence is not just for robots and automating traditional blue-collar workplaces - it will also be of great benefit to financial advisers. The firm's chief technology officer for Australia, Debra Bordignon, said AI will cover "the generalist research and problem solving of first-year lawyers, financial advisers, accountants, and doctors." Her comment comes from Dimension Data's latest e-book that aims to provide executive guidance around the assessment of a business' digital enterprise capability. She said leaders across all industries lack tools and models for cohesive strategy and execution, "and so approaches are often piecemeal, falling short of what is required to flourish in the digital social era." "IT leaders are scrambling to understand which strategic assets and capabilities they need to bridge analogue and digital worlds. They want to know how to take the culture and business models associated with dynamic start-ups and bring them into mature enterprises," Bordignon said.
How artificial intelligence could put an end to prisons as we know them
Dan Hunter is a prison guard's worst nightmare. But he's not a hardened crim. As dean of Swinburne University's Law School, he's working to have most wardens replaced by a system of advanced artificial intelligence connected to a network of high-tech sensors. Called the Technological Incarceration Project, the idea is to make not so much an internet of things as an internet of incarceration. Professor Hunter's team is researching an advanced form of home detention, using artificial intelligence, machine-learning algorithms and lightweight electronic sensors to monitor convicted offenders on a 24-hour basis.
Graph Classification via Deep Learning with Virtual Nodes
Pham, Trang, Tran, Truyen, Dam, Hoa, Venkatesh, Svetha
Learning representation for graph classification turns a variable-size graph into a fixed-size vector (or matrix). Such a representation works nicely with algebraic manipulations. Here we introduce a simple method to augment an attributed graph with a virtual node that is bidirectionally connected to all existing nodes. The virtual node represents the latent aspects of the graph, which are not immediately available from the attributes and local connectivity structures. The expanded graph is then put through any node representation method. The representation of the virtual node is then the representation of the entire graph. In this paper, we use the recently introduced Column Network for the expanded graph, resulting in a new end-to-end graph classification model dubbed Virtual Column Network (VCN). The model is validated on two tasks: (i) predicting bio-activity of chemical compounds, and (ii) finding software vulnerability from source code. Results demonstrate that VCN is competitive against well-established rivals.
Artificial Intelligence 'Vastly More Risk' Than North Korea โ Elon Musk
His stark warning came at a time when the US and North Korea remain on heightened alert amid spiraling tensions on the Korean Peninsula. Earlier this week, both sides degenerated to open threats, demonstrating readiness to use coercive force if provoked to do so. Whereas the US said it may rely on strategic bombers to hit North Korean targets, the Asian nation's military announced that a plan of striking the American airbase in Guam will be ready soon. Adding fuel to the crisis, President Donald Trump said the US military assets are "locked and loaded" in case if Pyongyang misbehaves. The heated exchange โ coupled by saber-rattling โ has revived the threat of war on the Korean Peninsula, with many speculating on its impact on global affairs.
Elon Musk: AI Poses 'Vastly More Risk Than North Korea'
As many in the United States and abroad are watching as tensions grow with North Korea, Tesla founder and CEO Elon Musk issued a warning about artificial intelligence. "If you're not concerned about AI safety, you should be. The tweet also included a photo that reads, "In the end the machines will win." Musk also warned that artificial intelligence should be regulated the same way anything that could pose a danger to the public is. This is not the first time Musk has warned people about AI.
Elon Musk: Artificial Intelligence Is More Dangerous Than North Korea
Elon Musk, hellbent on progressing the technological feats of humankind including artificial intelligence, would like you to know that artificial intelligence poses a greater threat to your fragile existence than threat-of-the-week North Korea. Elon Musk, a man who told a gathering of governors that "AI is a fundamental risk to the existence of human civilization" last month, is tweeting through the constant news of Donald Trump throwing Guam under the bus and egging on a nuclear power by comforting us with the threat of an evil artificial intelligence. Why do American political and business leaders seem to be practically begging North Korea to deep fry our asses on Twitter? Remember when Twitter was just bad joke punchlines and awkward "I meant to type that into the search bar, woops" scenarios? That was sort of fun.
Australia will reap $2.2 trillion opportunities if it doubles AI: report
A new report indicates that Australia must double its pace for artificial intelligence and robotics automation to achieve up to $2.2 trillion opportunity by 2030. While doing this, the country must urgently prepare to support over 3 million workers who may lose their jobs. Economics and strategy consulting firm AlphaBeta has released a report, which showed that automation can take away an average four hours of work every week from Aussie workers over the next 15 years if its rate is doubled. AlphaBeta director Andrew Charlton said the reality is that automation alters every job. He explained it is not so much about the jobs, but how the jobs will be done.