Industrial Artificial Intelligence

Activity: Talk or presentationOther talk or presentationscience-to-public

Description

Technological revolutions often come in three distinct phases: basic research, scale-up, and industrial application—each characterized by differing degrees of methodological diversity: high in research, low during scaling, and moderate in industrial deployment. Historic breakthroughs such as the steam engine and the Haber-Bosch process exemplify this pattern and their transformative societal impact. A similar trajectory is now evident in the development of modern artificial intelligence (AI).
In the scale-up phase, large language models (LLMs) emerged as the most visible and widely deployed form of AI. While LLMs represent powerful methods for knowledge representation, they have not fundamentally redefined the core of AI itself. This phase was dominated by the transformer architecture. Recently, however, alternative architectures—such as state-space models and recurrent neural networks—have also been successfully scaled. A notable example is the Long Short-Term Memory (LSTM) network, which has been significantly enhanced to xLSTM. In many language tasks, xLSTM now surpasses transformers in performance. The xLSTM-based model TiRex has set new standards in time series forecasting, outperforming U.S. industry leaders like Amazon, Salesforce, and Google, as well as Chinese competitors such as Alibaba.
We are now entering the third phase: industrial AI, where the focus shifts to adapting and deploying AI systems in real-world, high-impact applications. Time series analysis plays a central role in this phase, enabling intelligent solutions across key domains: predictive maintenance (equipment failure detection), demand forecasting, route and logistics optimization, smart grid energy forecasting, traffic prediction, predictive diagnostics in healthcare, dynamic pricing in retail, algorithmic trading in finance, and automated quality control in manufacturing.
Period19 Nov 2025
Event titleExner Lectures 2025
Event typeConference
LocationWien, AustriaShow on map
Degree of RecognitionNational

Fields of science

  • 101019 Stochastics
  • 102003 Image processing
  • 103029 Statistical physics
  • 101018 Statistics
  • 101017 Game theory
  • 102001 Artificial intelligence
  • 202017 Embedded systems
  • 101016 Optimisation
  • 101015 Operations research
  • 101014 Numerical mathematics
  • 101029 Mathematical statistics
  • 101028 Mathematical modelling
  • 101026 Time series analysis
  • 101024 Probability theory
  • 102032 Computational intelligence
  • 102004 Bioinformatics
  • 102013 Human-computer interaction
  • 101027 Dynamical systems
  • 305907 Medical statistics
  • 101004 Biomathematics
  • 305905 Medical informatics
  • 101031 Approximation theory
  • 102033 Data mining
  • 102 Computer Sciences
  • 305901 Computer-aided diagnosis and therapy
  • 102019 Machine learning
  • 106007 Biostatistics
  • 102018 Artificial neural networks
  • 106005 Bioinformatics
  • 202037 Signal processing
  • 202036 Sensor systems
  • 202035 Robotics

JKU Focus areas

  • Digital Transformation