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3 Ways Companies Are Building a Business Around AI

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Many other companies, including Microsoft and Amazon, also already offer AI tools which, like Google Cloud, where I work, will be sold online as cloud computing services. The painful process of acquiring and correctly tagging the data, including time and location information for new pictures the company and customers take, gave CAMP3 what Ganssle considers a key strategic asset. Blinker has filed for patents on a number of the things it does, but the company's founder and chief executive thinks his real edge is his 44 years in the business of car dealerships. As much as the world changes, deep truths -- around unearthing customer knowledge, capturing scarce goods, and finding profitable adjacencies -- will matter greatly.


How BMW Uses Artificial Intelligence And Big Data To Design And Build Cars Of Tomorrow

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But technology is not just limited to the cars it builds, its business model is built on Big Data which drives everything it does across design, engineering, production, sales and customer support. Thanks to Artificial Intelligence (AI), data-driven predictive analytics and other cutting edge technologies BMW is able to build the cars of today while at the same time envisaging and bringing to reality the cars of tomorrow. It has stated that its aim is for its vehicles to achieve full "level 5" autonomy by 2021. More details of how this would be achieved began to emerge earlier this year when BMW announced a partnership with Intel, which itself had recently acquired Mobileye, a leader in computer vision technology.


The data don't lie: Using machine learning to fight insurance fraud

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So, how can insurers effectively analyse data help to combat insurance fraud? In addition, telematics-based solutions are helping insurers reduce fraud and manage risk effectively using big data technologies. Organisations such as Octo Telematics have transformed how insurers assess risk, deliver crash and claim services and detect fraud. The ability to identify high-risk policies early on and spot more valuable business opportunities will save insurers time and money dealing with expensive and complex policies down the line.


How big data is transforming the automotive industry

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By 2020, the connected car market report states that connected car services will account for approximately $40 billion annually. These services include infotainment, navigation, fleet management, remote diagnostics, automatic collision notification, enhanced safety, usage based insurance, traffic management and, lastly, autonomous driving. The root of these applications is big data, as increasing amounts of data are collected from remote sensors; this information is being interpreted and leveraged to transform the automotive industry into one of automation and self-sufficiency. By using the information gleaned from smart sensors, the industry can benefit from compiling custom insurance plans, monitoring driver behaviour, performance and safety.


How BMW Uses Artificial Intelligence And Big Data To Design And Build Cars Of Tomorrow

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But technology is not just limited to the cars it builds, its business model is built on Big Data which drives everything it does across design, engineering, production, sales and customer support. Thanks to Artificial Intelligence (AI), data-driven predictive analytics and other cutting edge technologies BMW is able to build the cars of today while at the same time envisaging and bringing to reality the cars of tomorrow. It has stated that its aim is for its vehicles to achieve full "level 5" autonomy by 2021. More details of how this would be achieved began to emerge earlier this year when BMW announced a partnership with Intel, which itself had recently acquired Mobileye, a leader in computer vision technology.


The subtle, invisible AI that big Indian start-ups are using to get to know consumers better

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So, ShopClues plans to use advanced technologies to make it easier for shoppers to find the right size when buying clothes online, according to Utkarsh Biradar, vice-president of product at the company. It's also applying these technologies to help advertisers expand their reach effectively, using machine learning to identify "lookalike" targets that are similar to existing users as well as figuring out what kinds of ads users don't want to see. Ola, one of India's leading ride-hailing apps, is using data science and machine learning to track traffic, improve customer experience, understand driver habits and extend the life of a vehicle. Machine learning models log each customer's gender, brand affinity, store affinity, price preference, frequency, volume of purchases, and more, which become more accurate as the company collects more data.


Solution guide: Building connected vehicle apps with Cloud IoT Core

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GCP services, including the recently launched Cloud IoT Core provides a robust computing platform that takes advantage of Google's end-to-end security model. Device Management: To handle secure device management and communications, Cloud IoT Core makes it easy for you to securely connect your globally distributed devices to GCP and centrally manage them. Applications: Compute Engine, Container Engine and App Engine all provide computing components for a connected vehicle platform. Predictive Models: TensorFlow and Cloud Machine Learning Engine provide a sophisticated modeling framework and scalable execution environment.


The subtle, invisible AI that Indian unicorns have made a part of consumers' lives

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So, ShopClues plans to use advanced technologies to make it easier for shoppers to find the right size when buying clothes online, according to Utkarsh Biradar, vice-president of product at the company. It's also applying these technologies to help advertisers expand their reach effectively, using machine learning to identify "lookalike" targets that are similar to existing users as well as figuring out what kinds of ads users don't want to see. Ola, one of India's leading ride-hailing apps, is using data science and machine learning to track traffic, improve customer experience, understand driver habits and extend the life of a vehicle. Machine learning models log each customer's gender, brand affinity, store affinity, price preference, frequency, volume of purchases, and more, which become more accurate as the company collects more data.


In the Auto Industry, the Future Is Software--Not Machinery - Column

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But this was an autonomous Volvo, part of a small test fleet Uber operated in Pittsburgh, San Francisco, and Arizona. The Cal DMV had revoked the registrations for Uber's 16 test vehicles, and if the bureaucrats were motivated by the fear of a couple tons of undercooked technology circulating among the driving public, those fears seem to have been vindicated by the photos of the capsized Volvo. Note that around 17.5 million light-duty vehicles were sold last year, swelling the national fleet to more than 240 million vehicles, and only the most infinitesimal percentage of them has any autono mous ability what soever. A friend who works in so-called big data told me recently that the digital information generated by these test cars meas ures out in petabytes per day, a petabyte being 1 million gigabytes.


How AI will play a major role in the auto industry

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Artificial intelligence (AI) systems, blending data and advanced algorithms to mimic the cognitive functions of the human mind, have begun to simplify and enhance even the simplest aspects of our everyday experiences -- and the automotive industry is no exception. While self-driving cars and complex decision-making are the prime use cases for modern AI, the auto industry continues to search for new ways to engage customers through existing and new channels. Machine learning methods are particularly applicable when it comes to powering new insights within the auto industry because the data sets are large, diverse, and change quickly. Given the vast selection of cars and finance providers available, machine learning has the potential to help car buyers quickly find the vehicles and financing options that are right for them, vastly simplifying their customer journey.