Making a high-quality gear cannot be learned simply from an Internet search. You may find guidelines, papers, rules, lectures, and videos. However, applying this general knowledge to a specific production process and dealing with uncertainties and disruptions requires special know-how, most of which resides in people's heads and networks and is acquired to a large extent through "learning by doing." Over 10 years ago, the vision of Industry 4.05 was announced at the Hannover Fair 2011 as part of the German/European High-Tech Strategy and adopted internationally by the Japanese Industrial Value Chain Initiative, the Advanced Manufacturing Initiative in the U.S., the Chinese Made in China 2025 strategy, the South Korean Manufacturing 3.0, and the U.K.'s High-Value Manufacturing Catapult research center. This "fourth industrial revolution" follows the earlier stages of mechanization (steam engine), mass production (assembly lines), and IT-based electronic automation.

Welcome to the second Communications Regional Special Section spotlighting European countries and Israel. On a relatively small portion of the Earth, this region includes almost 50 countries with enormous cultural and socioeconomic diversity that is also reflected in the richness of its business structures and computer science research. The first Hot Topic article in this section illustrates the high overall share of European public research on a global scale, and further highlights significant differences within the region. We are happy to report the authors in this special section represent 15 countries throughout Europe plus Israel. An important goal emphasized by the European Union (E.U.) and many individual countries is to attain digital sovereignty of the private and public sectors, while further developing areas of traditional industrial and design strengths into the future.

We strive to understand social systems and to model human behavior via computational methods and new kinds of data. We are a group of computational scientists working in interdisciplinary contexts and settings. We offer courses on algorithmic methods for mining and understanding textual data and networks.

Big data, artificial intelligence (AI), Industry 4.0--these terms are thrown around by technologists today, conjuring dystopian images of dark silos of personal data on file, endless automation, and robots running our factories. But what is Industry 4.0? Will Industry 4.0 cut jobs or create them? BusinessBecause caught up with Professor Tobias Meisen, head of the Institute of Information Management in Mechanical Engineering (IMA) at Germany's RWTH Aachen University, who leads a host of new professional courses on Industry 4.0, to find out more. Here's five things you should know about Industry 4.0: A 2011 German government initiative, Industry 4.0 marks a new wave of automation developments in manufacturing, brought about by cutting-edge technologies like big data, artificial intelligence (AI) and the Internet of Things (IoT).

Just as we learn from our mistakes, they are--well, learning from our mistakes too. A database of Atari Gameplay was unleashed to show AI what's what with game play. Tech sites are talking about this Atari Grand Challenge dataset--worthy of attention as the dataset, said Dan Robitzski in Inverse, gives AI systems access to new ways of learning and honing skills over time. The researchers stated in their paper that "We collect and describe a large dataset of human Atari 2600 replays – the largest and most diverse such data set publicly released to date." Jordan Pearson, Motherboard: "Computer scientists from RWTH Aachen University in Germany and Microsoft Research have released the largest-ever database of human playthroughs for some of the most popular games for the Atari 2600."

Artificial intelligence is slowly proving that that video games aren't a total waste of time, at least for machines: It's through learning to play games that AI algorithms can acquire all sorts of generalizable skills, like problem-solving. Now, computer scientists from RWTH Aachen University in Germany and Microsoft Research have released the largest-ever database of human playthroughs for some of the most popular games for the Atari 2600. Artificial agents using deep learning techniques will be able to pull patterns out of these playthroughs and learn from them. According to a paper posted to the arXiv preprint server this week, which is undergoing peer review, the database contains more than 45 hours of gameplay from five games: Q*Bert, Ms. Pacman, Space Invaders, Video Pinball, and Montezuma's Revenge. Video games are an increasingly popular training ground for AI to solve general problems, like how to quickly arrive at a course of action, or how to effectively learn in an environment where the rewards for learning are sparse, which is notoriously the case for Montezuma's Revenge .