DIREC TALKS: Formal Verification and Machine Learning Joining Forces
In this DIREC talk Kim Guldstrand Larsen presents and discusses how to combine formal verification and AI in order to obtain optimal AND guaranteed safe strategies.
Embedded AI
AI currently relies on large data centers and centralized systems, necessitating data movement to algorithms. To address this limitation, AI is evolving towards a decentralized network of devices, bringing algorithms directly to the data. This shift, enabled by algorithmic agility and autonomous data discovery, will reduce the need for high-bandwidth connectivity and enhance data security and privacy, facilitating real-time edge learning.
HERD: Human-AI Collaboration: Engaging and Controlling Swarms of Robots and Drones
Today, robots and drones take on an increasingly broad set of tasks. However, such robots are limited in their capacity to cooperate with one another and with humans. This project aims to address multi-robot collaboration and design and evaluate technological solutions that enable users to engage and control autonomous multi-robot systems.
EXPLAIN-ME: Learning to Collaborate via Explainable AI in Medical Education
Together with clinicians, this project aims to develop explanatory AI that can help medical staff make qualified decisions by taking the role as a mentor who provides feedback and advice for the clinicians. It is important that the explainable AI provides good explanations that are easy to understand and utilize during the medical staff’s workflow.
Business Transformation and Organisational AI-based Decision Making
Together with industry, the project aims to develop methods and tools that enable industry to develop new efficient solutions for exploiting the huge amount of business data generated by enterprise systems, with specific focus on tools and responsible methods for the use of process insights for business intelligence and transformation.
AI and Blockchains for Complex Business Processes
Together with industry, this project aims to develop methods and tools that enable the industry to develop new efficient solutions for exploiting the huge amount of business data generated by enterprise and blockchain systems, with specific focus on tools and responsible methods for the use of process insights for business intelligence and transformation.
Mobility Analytics using Sparse Mobility Data and Open Spatial Data
The amount of mobility-related data has increased massively which enables an increasingly wide range of analyses. When combined with digital representations of road networks and building interiors, this data holds the potential for enabling a more fine-grained understanding of mobility and for enabling more efficient, predictable, and environmentally friendly mobility.
Deep Learning and Automation of Image-Based Quality of Seeds and Grains
Today, manual visual inspection of grain is still one of the most important quality assurance procedures throughout the value chain of bringing cereals from the field to the table.
Together with industrial partners, this project aims to develop and validate a method of automated imaging-based solutions that can replace subjective manual inspection and improve performance, robustness and consistency of the inspection.
