Summary The paper builds on the literature of Positive and Unlabeled (PU) learning and formulates a new risk objective that is negatively bounded. The need is mainly motivated by the fact that the state of the art risk formulation for PU can be unbounded from below. This is a serious issue when dealing with models with high capacity (such as deep neural networks), because the model can overfit. A new lower-bounded formulation is provided. Despite not being unbiased, the new risk is consistent and its bias decreases exponentially with the sample size. Generalization bounds are also proven.

Thank you for joining us on "The cloud hub: From cloud chaos to clarity." With any new technology-based tools, enterprises face concerns and cybersecurity risks. ChatGPT, the chatbot that created ripples in the internet world, could be used to generate malicious code. Read this article to know how you can mitigate the risks.

The Gradient Institute, with support from Minderoo Foundation, recently released a report on the growing risk of Artificial Intelligence (AI) to business along with open source software for companies to combat the risk. Here, Bill Simpson-Young who is CEO of Gradient Institute and former CSIRO, talks about the dangers of Artificial Intelligence for business. What are the dangers of Artificial Intelligence we need to be aware of for business? AI used by businesses can have many benefits to businesses and their customers such as being able to perform actions for the customer at great speed and customised specifically for that customer. For example, every time you use a map app on your phone, the speed, accuracy, and relevance for you is made possible by AI.

The Gradient Institute, with support from Minderoo Foundation, recently released a report on the growing risk of Artificial Intelligence (AI) to business along with open source software for companies to combat the risk. Here, Bill Simpson-Young who is CEO of Gradient Institute and former CSIRO, talks about the dangers of Artificial Intelligence for business. What are the dangers of Artificial Intelligence we need to be aware of for business? AI used by businesses can have many benefits to businesses and their customers such as being able to perform actions for the customer at great speed and customised specifically for that customer. For example, every time you use a map app on your phone, the speed, accuracy, and relevance for you is made possible by AI. AI is also used in deciding your news feed, whether you get matched for a job opening and whether you are successful with a loan application.

Although it's not the only risk associated with AI, the potential for a machine to become biased with its data is definitely a concern for insurers. AI bias can come from a few sources, says Chantal Sathi, founder and president of Cornerstone AI and its debiasing software, BiasFinderAI.

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Artificial intelligence (AI) technologies offer profoundly important strategic benefits and hazards for global businesses and government agencies. One of AI's greatest strengths is its ability to engage in behavior typically associated with human intelligence -- such as learning, planning, and problem solving. AI, however, also brings new risks to organizations and individuals, and manifests those risks in perplexing ways. It is inevitable that AI will soon face increased regulation.

Black swan events are not unknown to the insurance industry. By their nature, these kinds of events can happen at any given moment and without warning or historical precedent. However, for the insurance industry, and for all of us, Covid-19 has proven that new risks are emerging, and we need insurers to demonstrate now more than ever that they are here to protect us. While the economy is showing some signs of recovery, insurers must not forget the lessons they have learned from Covid-19 and they should see it as an opportunity to grow and improve. For the insurance industry, the lesson is clear: the risks policyholders face are changing, and digital innovation can help the industry respond.

At last, it is here! Few new technologies have ever been more anticipated and more predicted than the self-driving car. Anyone who drives cannot help but imagine not having to drive any more. It has been said that they will change our cities, our homes, our commerce, even our fundamental way of life. But at the same time, the actual progress has seemed … well … glacial, to the casual driver's eye.

At last, it is here! Few new technologies have ever been more anticipated and more predicted than the self-driving car. Anyone who drives cannot help but imagine not having to drive any more. It has been said that they will change our cities, our homes, our commerce, even our fundamental way of life. But at the same time, the actual progress has seemed … well … glacial, to the casual driver's eye.

In the months following the failed Apollo 13 mission, investigators discovered that a seemingly benign event two years earlier was the root cause of this near national disaster. Engineers handling one of two oxygen tanks built for the service module accidentally let one slip and fall. I once dropped my iPhone from my seat at a hockey game and watched helplessly as it fell 15 feet toward the cement floor. Miraculously, it landed at just the right angle and survived. In a fateful moment years before launch, at the North American Aviation plant in Downey, California, a simple slip of just two inches created enough structural damage to set in motion a series of failures that nearly killed three astronauts.