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Goldman Sachs World Cup Analytics Show Limits of Big Data

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If you're a fan of the World Cup, you probably had your sights set on a winner before the tournament kicked off. Maybe you really liked how Spain's team was shaping up (despite the coaching shifts), or you wanted to root for an underdog such as Japan or Croatia. Goldman Sachs, which knows a little something about probability and risk, built a sophisticated data model to predict the World Cup's eventual winner. This model leveraged machine learning to simulate 1 million possible evolutions, and updated throughout the tournament, according to Bloomberg. With that kind of setup, you'd think that the algorithms would get at least a few match outcomes right.


Insurance 2030--The impact of AI on the future of insurance

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The industry is on the verge of a seismic, tech-driven shift. A focus on four areas can position carriers to embrace this change. Welcome to the future of insurance, as seen through the eyes of Scott, a customer in the year 2030. Upon hopping into the arriving car, Scott decides he wants to drive today and moves the car into "active" mode. Scott's personal assistant maps out a potential route and shares it with his mobility insurer, which immediately responds with an alternate route that has a much lower likelihood of accidents and auto damage as well as the calculated adjustment to his monthly premium. Scott's assistant notifies him that his mobility insurance premium will increase by 4 to 8 percent based on the route he selects and the volume and distribution of other cars on the road. It also alerts him that his life insurance policy, which is now priced on a "pay-as-you-live" basis, will increase by 2 percent for this quarter.


Insurance 2030--The impact of AI on the future of insurance

#artificialintelligence

The industry is on the verge of a seismic, tech-driven shift. A focus on four areas can position carriers to embrace this change. Welcome to the future of insurance, as seen through the eyes of Scott, a customer in the year 2030. Upon hopping into the arriving car, Scott decides he wants to drive today and moves the car into "active" mode. Scott's personal assistant maps out a potential route and shares it with his mobility insurer, which immediately responds with an alternate route that has a much lower likelihood of accidents and auto damage as well as the calculated adjustment to his monthly premium. Scott's assistant notifies him that his mobility insurance premium will increase by 4 to 8 percent based on the route he selects and the volume and distribution of other cars on the road. It also alerts him that his life insurance policy, which is now priced on a "pay-as-you-live" basis, will increase by 2 percent for this quarter.


5 Examples of Machine Learning

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Machine learning is a subset of AI systems that has become an essential tool for many. The phrase is used to describe the process of a programs ability to learn without being explicitly programmed. Essentially, we are talking about programs that write themselves. Investment firms, traders and hedge funds are using machine learning to create artificial intelligence with the ability to predict when the market will rise and fall. After making predictions these programs then automatically buy and sell based on those predictions.


At least two cool ways that AI can help insurance companies

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Machine learning could be used to underwrite faster, reduce fraud and assess vehicle damages more accurately, Lawrence Wong, Munich Re Canada's director of application development, said Tuesday.


How Artificial Intelligence is changing how we do business?

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Can I have an AI and two blockchains? That's a joke but people tend to confuse or misuse the terms. There is undoubtedly a hype around these terms. In this post we are going to talk about AI (Artificial Intelligence), what it is and whether it is able to achieve what it is promising. We are going to do this, while going through the cases presented at the AI Congress 2018. The AI Congress took place in the O2 in London on 30th and 31st January 2018 and brought together people from different industries to talk about AI and network. Its aim was to focus on how AI can be effectively monetised and the ever-growing opportunities for enterprises to take advantage of artificial intelligence.


Top 5 Machine Learning Use Cases for 2018 - DZone AI

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Artificial intelligence (AI) is being deployed more and more frequently across industries. Far from the typical sci-fi fantasy depiction of robots with human-level intelligence, AI's purpose in business today is frequently to automate tasks that humans have done in the past, such as picking products at a warehouse for order fulfillment, but also to find hidden patterns in data that lead to actionable insights.


Top 5 Machine Learning Use Cases for 2018 GigaSpaces Blog

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Artificial Intelligence (AI) is being deployed more and more frequently across industries. Far from the typical sci-fi fantasy depiction of robots with human-level intelligence, AI's use in business today is frequently used to automate tasks that humans have done in the past, such as picking products at a warehouse for order fulfillment but also to find hidden patterns in data that lead to actionable insights.


What Are Smart Cities (And Why Should We Care)?

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You can be forgiven if your first reaction to hearing the term "smart cities" is an eye roll. Sure, we have smart diapers, smart toothbrushes and smart faucets, but cities? How is that even possible?


Can math predict what you'll do next?

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Good scientists are not only able to uncover patterns in the things they study, but to use this information to predict the future.