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Industry 4.0

eZassi

Improving Industry 4.0 With Innovation Management In today’s rapidly evolving business landscape, staying ahead of the competition requires embracing Industry 4.0 What is Industry 4.0 Industry 4.0 Industry 4.0 Industry 4.0 Industry 4.0 Additive Manufacturing: New methods for Industry 4.0

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A New Way of Thinking About the Automotive Industry

Qmarkets

Recent trends suggest that the automotive industry might be next on Silicon Valley's disruption list. Besides a surge of auto tech startups and Tesla's success, Silicon Valley's new affair with the automotive industry is heightened by chatter about a secret car project by the most prominent disruptor of them all: Apple.

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The Innovation-Driven Disruption of the Automotive Value Chain (Part 2)

Corporate Innovation

Companies in the automotive value chain are faced with a challenging future. Because of problems such as pollution, climate change and loss of productivity due to long commute times, consumer attitudes towards car ownership and use are changing. Despite their high R&D investments, automotive OEMs are not considered top innovators.

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The Innovation-Driven Disruption of the Automotive Value Chain (Part 2)

Corporate Innovation

Companies in the automotive value chain are faced with a challenging future. Because of problems such as pollution, climate change and loss of productivity due to long commute times, consumer attitudes towards car ownership and use are changing. Despite their high R&D investments, automotive OEMs are not considered top innovators.

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Key Innovation Issues for 2016 and Beyond

Integrative Innovation

Accelerating dynamics and pace of disruption in most industries, in particular triggered by the pervasion of new technologies, lead to decreasing life times of existing business models. Enabled by the accelerating pace of digitalization, a new model for value creation is taking shape – spreading in almost any industry.

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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. Applications of AI. Source: McKinsey. Healthcare.