The famous St Petersburg Paradox shows that the theory of expected value does not capture the real-world economics of decision-making problem. Over the years, many economic theories were developed to resolve the paradox and explain the subjective utility of the expected outcomes and risk aversion. In this paper, we use the concept of the net utility to resolve the St Petersburg paradox. The reason why the principle of absolute instead of net utility does not work is because it is a first order approximation of some unknown utility function. Because the net utility concept is able to explain both behavioral economics and the St Petersburg paradox it is deemed a universal approach to handling utility. Finally, this paper explored how artificial intelligent (AI) agent will make choices and observed that if AI agent uses the nominal utility approach it will see infinite reward while if it uses the net utility approach it will see the limited reward that human beings see.

The Australian Security Intelligence Organisation (ASIO) has a problem, it collects too much data and might miss something. "That's the problem we are dealing with right now, given the threats are at the unprecedented level," recently installed Director-General of Security Mike Burgess said during his 38th day on the job. "There is the potential to miss something, the application of data analytics helps us to reduce the possibility of that being an event." ASIO is currently undertaking an enterprise-wide transformation that it believes will place it "at the forefront of agencies" using artificial intelligence and machine learning, according to its recent annual report. Providing an update on the project, Burgess said the organisation has so far put a new operating structure and model in place, as well as other foundational work subject to further government approvals.

Tinder's interactive choose-your-own-adventure series will expand to users globally after a successful roll out. According to a report from CNN, the dating service's first-ever foray into pre-recorded content, called'Swipe Night', translated to a 26 percent increase in matches over a typical Sunday night with a 12 percent increase in messages. The company reportedly plans to expand outside of the US to all of its users across the globe starting February 2020. The series, which'aired' on the app this month, allows users to match with other dating hopefuls by clicking their way through an interactive narrative. It's designed to match users based on the choices they make during a short'first-person apocalyptic adventure.'

Spending on artificial intelligence (AI) in the Asia-Pacific region is expected to surge by more than 50 percent on an annual basis to US$6.2 billion this year, market advisory firm International Data Corp (IDC) said. "Artificial intelligence is having an impact across many industries with widespread utilization, but is still at a nascent stage in the Asia-Pacific," IDC associate market analyst for Asia-Pacific Ritika Srivastava said in a report on Friday last week. "From providing chatbots for better customer service to improving the efficiency of operations and tasks for their business models, industries like banking, retail and professional services are spending in this technology at scale," Srivastava said. The banking industry would lead the way in spending on AI and contribute about 10.7 percent of overall spending in the Asia-Pacific region, the report said. Banks would mostly focus on AI/cognitive systems for fraud analysis and investigation, while also investing in automated customer service agents, it said.

In recent years, machine learning and artificial intelligence have made a way into all areas of homes, lives and businesses. Today, the technology is becoming increasingly ubiquitous such as from AI assistants like Alexa or Siri, speech translator, GPS finding location, smart devices etc. These days, you can find exciting evidence of machine learning innovation in marketing today as it is applied to pay-per-click, created more intelligent email campaigns and chatbots. Here, GoodFirms has conducted a survey based on AI and Machine Learning for PCC Campaign Management. In this research, PPC Gurus (Duane Brown, Ed Leake, Gianluca Binelli, Jeff Sauer, Kirk Williams, Larry Kim, Luca Senatore, Martin Roettgerding, Navah Hopkins, Patrick Gilbert) were contacted that are experts in digital marketing.

Special report ImageNet – a data set used to train AI systems around the world – contains photos of naked children, families on the beach, college parties, porn actresses, and more, scraped from the web to train computers without those individuals' explicit consent. The library consists of 14 million images, each placed into categories that describe what's pictured in each scene. This pairing of information – images and labels – is used to teach artificially intelligent applications to recognize things and people caught on camera. The database has been downloaded by boffins, engineers, and academics to train hundreds if not thousands of neural networks to identify stuff in photos – from assault rifles and aprons to magpies and minibuses to zebras and zucchinis, and everything in between. In 2012, the data set was used to build AlexNet, heralded as a breakthrough development in deep learning since it marked the first time a neural network outperformed traditional computational methods at object recognition in terms of accuracy.

A new flu vaccine designed by artificial intelligence has gone on trial in the United States in what researchers are claiming is a world first. Scientists at Flinders University in Australia have developed what they describe as a "turbo-charged" flu vaccine with an extra component that stimulates the human immune system to make more antibodies against the flu virus than a normal vaccine, thus making it more effective. Nikolai Petrovsky, professor of medicine at Flinders University in Australia and the lead researcher on the vaccine, said that as far as he knew this was the first time a flu vaccine had been developed using AI that had progressed to a trial in humans. He said that the use of AI had accelerated the vaccine discovery process, cut costs massively and had enabled the development of a more effective vaccine. He said using AI streamlined the vaccine development process.

Last March, Google took the wraps off of Coral, a collection of hardware development kits and accessories intended to bolster the development of machine learning models at the edge. It launched in select regions in beta, but the tech giant today announced that it's graduating to a "wider" and global release. All Coral products -- including the $150 Coral Dev Board, the $74.99 Coral USB Accelerator, and the $24.99 5-megapixel camera accessory -- are available for sale at electronics retailer Mouser and for large-volume sale through Google's sales team. The company says that by the end of the year, it'll expand distribution into new markets including Taiwan, Australia, New Zealand, India, Thailand, Singapore, Oman, Ghana, and the Philippines. Coinciding with Coral's general availability, the Coral website -- which now lives at Coral.ai -- has been revamped with better organization for docs and tools, testimonials, and "industry-focused" pages. Additionally, it links to a new set of examples aimed at providing solutions to common AI problems, such as image classification, object detection, pose estimation, and keyword spotting.

Tracking the health of underwater species is critical to understanding the effects of climate change on marine ecosystems. Unfortunately, it's a time-consuming process -- biologists conduct studies with echosounders that use sonar to determine water and object depth, and they manually interpret the resulting 2D echograms. These interpretations are often prone to error and require pricey software like Echoview. Fortunately, a team of research scientists hailing from the University of Victoria in Canada are developing a machine learning method for detecting specific biological targets in acoustic survey data. In a preprint paper ("A Deep Learning based Framework for the Detection of Schools of Herring in Echograms"), they say that their approach -- which they tested on schools of herring -- might measurably improve the accuracy of environmental monitoring.

Virtus Health has announced in partnership with Harrison-AI and Vitrolife that it will commence randomised controlled trials of its artificial intelligence (AI) technology, called Ivy, by the end of the year. Speaking at The Future of Health event in Sydney this week, Virtus Health group CEO Sue Channon explained the tests will be used to further validate the use of AI when it comes to in-vitro fertilisation (IVF). She explained how for the last 12 months, embryologists have been using Ivy as a supporting tool to increase the potential success of pregnancy through IVF. "At this stage Ivy is still a supporting tool, we're not letting Ivy make the decision on its own," she said, explaining how one patient got pregnant during the cycle that Ivy was used after five unsuccessful IVF cycles. "We are seeing an improvement of pregnancy outcome as a result of Ivy."