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Key Innovation Issues for 2016 and Beyond

Integrative Innovation

In the course of this first month of 2016, I was asked a couple of times what my prospects are for the year ahead when it comes to key innovtion issues. Hence, I gave it some thought, starting by revisting an earlier reflection: Beginning of 2013, Tim Kastelle and I identified four key issues in innovation management for the time to come.

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7 Habits of Highly Innovative Companies

ITONICS

Even though it took 7 months for the founders to persuade Bosch leadership that their vision is doable, the startup developed a software with machine learning and analytics integrated within the networks of the retailer and the IoT application. Startups are generating a lot of innovation covering every aspect of consumer’s life.

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Applications of Artificial Intelligence (AI) in business

hackerearth

Recent advances in AI have been helped by three factors: Access to big data generated from e-commerce, businesses, governments, science, wearables, and social media. Improvement in machine learning (ML) algorithms—due to the availability of large amounts of data. Manufacturing. Conclusion.

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A New Way of Thinking About the Automotive Industry

Qmarkets

Referring to the over 1 million deaths and 15 million injuries caused by car accidents globally each year, Schmidt speaking to shareholders in 2016 bemoaned : "How could you accept that? On the 6 th of July Qmarkets will host leaders from a variety of organizations at the Munich Automotive Innovation Day 2017. embed][link].