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Published in: KI - Künstliche Intelligenz 1/2018

01-02-2018 | Editorial

From Big Data to Big Artificial Intelligence?

Algorithmic Challenges and Opportunities of Big Data

Authors: Kristian Kersting, Ulrich Meyer

Published in: KI - Künstliche Intelligenz | Issue 1/2018

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Abstract

Big Data is no fad. The world is growing at an exponential rate, and so is the size of data collected across the globe. The data is becoming more meaningful and contextually relevant, breaks new ground for machine learning and artificial intelligence (AI), and even moves them from research labs to production. That is, the problem has shifted from collecting massive amounts of data to understanding it, i.e., turning data into knowledge, conclusions, and actions. This Big AI, however, often faces poor scale-up behaviour from algorithms that have been designed based on models of computation that are no longer realistic for Big Data. This special issue constitutes an attempt to highlight the algorithmic challenges and opportunities but also the social and ethical issues of Big Data. Of specific interest and focus have been computation- and resource-efficient algorithms when searching through data to find and mine relevant or pertinent information.

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The Scientific journal "KI – Künstliche Intelligenz" is the official journal of the division for artificial intelligence within the "Gesellschaft für Informatik e.V." (GI) – the German Informatics Society - with constributions from troughout the field of artificial intelligence.

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Footnotes
1
The Economist, issue of Feb 25th, 2010
 
2
IBM’s “10 Key Marketing Trends for 2017 and Ideas for Exceeding Customer Expectations”, https://​www-01.​ibm.​com/​common/​ssi/​cgi-bin/​ssialias?​htmlfid=​WRL12345USEN, accessed Dec 3, 2017
 
8
Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research)
 
Metadata
Title
From Big Data to Big Artificial Intelligence?
Algorithmic Challenges and Opportunities of Big Data
Authors
Kristian Kersting
Ulrich Meyer
Publication date
01-02-2018
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 1/2018
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-017-0523-7

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