Big data analysis algorithms, statistical methods, querying engines, decision support heuristics for solving computationally complex problems and processing approaches all share one common aspect: they are created to benefit us, humans. However, we lack the capacity to manually process all this data and its often highly technical analyses.
Imec targets the design of operational decision support agents -personalized and intelligent agents- who reason over the data for us, and provide us with understandable conclusions and recommendations. These self-sustaining agents and compliant robotics are the end-game that all major players in the market are currently working towards.
This demands both deep learning, using multi-layered processing and algorithmic abstraction to make data patterns learnable, and transfer learning, applying knowledge across problem sets. Both are specialties of imec researchers at UGent and KU Leuven.