On this page you can see what TNO develops in the field of AI
Appl.AI Flagship projects
Two flagship projects constitute a base on which other AI projects build.
The FATE flagship develops AI capabilities for a digital assistant that acquires and extends its expertise through continuous learning from multiple potentially confidential and biased (subject) data sources and from human experts who add to and reflect on the AI-outcomes. The system provides decision support for multiple user roles, such as a researcher, consultant and subject.
Our projects on AI
Learning with less labels
The Learning with Less Labels (LwLL) program aims to make the process of training machine learning models more efficient by reducing the amount of labeled data required to build a model by six orders of magnitude, and by reducing the amount of data needed to adapt models to new environments from tens to hundreds of labeled examples. This program is funded by the Defense Advanced Research Projects Agency (DARPA).
Collaborative anti money laundering
Individually, major banks are facing significant challenges with respect to detecting money laundering. Due to privacy regulations and data confidentiality banks cannot readily share data, which makes it challenging to collaborate. The goal of this joint research project is to develop a Proof of Concept Multi-Party Computation solution for collaborative monitoring and detection of money laundering.