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5 ways artificial intelligence is driving the automobile industry 7wData

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Now, let's look at the different ways in which artificial intelligence will drive the automobile industry in the future: Artificial intelligence is a kind of intelligence developed as a result of excellent scientific experiments. However, there is a difference between Artificial Intelligence and Machine Learning. Toyota has gone a step further and has brought together Big data, Machine Learning and Artificial Intelligence to create highly responsive autonomous systems that aid in mobility for those who are "less able to drive". DL techniques have been very useful in the automobile industry as it aids in advanced driving assistance systems and autonomous driving.


The Moral Imperative of Artificial Intelligence

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Some labor economists have viewed Polanyi's Paradox as a major barrier for AI, arguing it implies a limit on its potential to automate human jobs. Indeed, the automation of driving has been a major challenge for AI research over the past decade. Thus, the automation of driving would be hugely beneficial, saving lives and preventing injuries on a massive scale. In the balance, life saving and injury prevention must take precedence, and we have a moral imperative to develop and deploy automated driving.


Machine learning is making self-driving cars smarter, but it can also make their workings more mysterious

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Two recent accidents involving Tesla's Autopilot system may raise questions about how computer systems based on learning should be validated and investigated when something goes wrong. But machine learning techniques are increasingly used to train automotive systems, especially to recognize visual information. For example, a deep learning neural network can be trained to recognize dogs in photographs or video footage with remarkable accuracy provided it sees enough examples. A team at Princeton designed an automated driving system based largely on deep learning.


Navistar takes command of big data for truck design, breakdown prevention

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Besides supporting internal customers in truck design and engineering, the analytics group uses advanced statistics and machine learning techniques to benefit its external customers. The model predicts failures for more than 40,000 combinations of diagnostic trouble codes (DTCs) by make, model and year of vehicle. When alerts are found for International trucks, its customer service group can address the problem directly with the fleet customer. The team used the technique to analyze the usage patterns of 100,000 vehicles by engine operating hours, miles, idling time, etc.


One Button to Help Them All

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How do you satisfy the "one button" trick to help solve the menu and button configuration dilemma on the vehicle dashboard? One reason I chose to move into the automotive group at SAS is their proven approaches and experience with applying machine learning techniques to help these situations. Driverless vehicles, connected cars, e-hailing, car sharing, and other innovative offerings are reshaping our industry. In the case of getting the dashboard to work intuitively, conveniently and effectively with the driver, machine learning techniques are a wise choice.


The Moral Imperative of Artificial Intelligence

#artificialintelligence

Some labor economists have viewed Polanyi's Paradox as a major barrier for AI, arguing it implies a limit on its potential to automate human jobs. Indeed, the automation of driving has been a major challenge for AI research over the past decade. Thus, the automation of driving would be hugely beneficial, saving lives and preventing injuries on a massive scale. In the balance, life saving and injury prevention must take precedence, and we have a moral imperative to develop and deploy automated driving.


The First Person to Hack the iPhone Built a Self-Driving Car. In His Garage.

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He drives through San Francisco's Potrero Hill neighborhood and then onto Interstate 280. The technology he's building represents an end run on much more expensive systems being designed by Google, Uber, the major automakers, and, if persistent rumors and numerous news reports are true, Apple. More short term, he thinks he can challenge Mobileye, the Israeli company that supplies Tesla Motors, BMW, Ford Motor, General Motors, and others with their current driver-assist technology. At 14, he was a finalist in the prestigious Intel International Science & Engineering Fair for building a robot that could scan a room and figure out its dimensions.