Artificial Intelligence and Digitization
Deep learning in industry
Systems that learn independently from large amounts of data are reality. This has been made possible by several parallel IT developments: On the one hand, the cloud revolution has made massive computing power affordable and accessible. On the other hand, industry 4.0 with its omnipresent sensors produces enormous amounts of data. Artificial intelligence and machine learning are supposed to elicit valuable knowledge from the flood of data.
Applications of artificial intelligence and machine learning
- Natural language processing
- Image recognition and processing
- Expert systems:
- Deep Learning
- Robotics and pathfinding
- Optimization and heuristics
Expert lectures of SCCH
Artificial Intelligence and Digitization, Dr. Thomas Natschläger
Technologies such as predictive analytics, big data and deep learning associated with artificial intelligence are on everyone's lips. Along industrial value-added chains there are many areas and applications that make use of them or enable them to do so. On the basis of selected examples, it will be discussed which methods can already be used profitably today, and which methods are being researched and developed.
The Opportunities of Transfer Learning for Industry, DI Theodorich Kopetzky
Deep Learning sets new standards for machine learning problems such as image recognition or speech processing. Deep learning methods have a catch, however; they are especially hungry for data and fine tuning can be very time-consuming. This is exactly where Transfer Learning comes in. The aim is to transfer implicit knowledge from already learned models to new problems and thus make it reusable. The potential of transfer learning is explained by current projects.
Further information about the event
Thursday, November 16,08:00 - 13:30, IBM Client Center Vienna, Obere Donaustraße 95,1020 Vienna.
Click here to register online