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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. It will become a hotbed for innovation in 2016 and the coming years. Tip: Tim Kastelle has posted a worthwile series on how to implement lean startup for innovation initiatives.

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The Future of Corporate-Startup Collaboration

The Inovo Group

New software technologies and tools will make it possible to create Startup Collaboration Platforms that enable the relationships to become more automated, structured and efficient. They had recognized that many innovative initiatives fail in the early stage of development due to, among other things, a lack of secure funding.

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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. Often, it’s due to the speed at which they can innovate and this has a lot to do with their size.

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11 Artificial Intelligence Eureka!s for Organizations: my recap of World Summit AI 2017

Open Innovation EU

In his 2016 book the Fourth Industrial Revolution Klaus Schwab mentions 6 basic technologies that are based on AI and currently impacting business: 1) the Internet of Things (IoT), 2) Autonomous Vehicles, 3) Advanced Robotics, 4) 3D-printing, 5) new materials and 6) the biological revolution. legislation on data.

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DELL Technologies: The First Thing to Know

Information Playground

After spending the majority of 2016 meeting and collaborating with my new DELL Technologies colleagues, two clear customer benefits began to emerge: Decades of experience between EMC and Dell will result in economic benefits to customers. Backup and Recovery: Data protection ( Legato ).

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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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Tech Disruptor – The Process Mining Unicorn Celonis

ITONICS

Imagine losing hours of productivity each day due to unnecessary steps in business processes. Celonis, as a software provider, is seeking to disrupt the management consulting sector. The intelligent Big Data technology analyzes and visualizes all processes within a company and detects weak points. How did it start?