Interview 2

AI and machine learning

The following interview snippets were given by Dr. Sebastian Lapuschkin and cover the topic of AI and machine learning, gives an approach about automation and mentions further examples of machine learning.

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The interviewee, Dr. Sebastian Lapuschkin, is the Head of Explainable Artificial Intelligence Group at Fraunhofer HHI in Berlin. He is in charge of conducting research towards the explainability of artificial intelligence.


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True or false?

Machine learning aims at finding data-driven automation solutions when the automation goal cannot be reached explicitly.




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True or false?

Machine learning aims at finding manual solutions to human problems based on data.




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True or false?

Machine learning is a data-driven approach in order to find human solutions to problems caused by machines.




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True or false?

Big Data describes the approach to collect and organise larger and complex data from various sources.




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True or false?

In order to conduct machine learning efficiently, you need representative data that describes your problem sufficiently.




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True or false?

Having a lot of data means the data is automatically good and can describe your problem.




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Machine learning is used in face recognition, for example in digital video cameras, webcams and surveillance systems. The scope of application for machine learning is very large. In interviewee’s labs they use machine learning for natural disaster prevention, in which they track climate data and air pollution data from the previous years and then train a model which should be able to predict weather and climate factors. Deep learning is being used in many complex processes like image recognition.


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