EnliteAI use case from the ELISE project
Real-Time, Multi-Modal, High Resolution Image Synthesization from Point Clouds
ELISE is a network of artificial intelligence research hubs. Based on the highest level research, it spreads its knowledge and methods in academia, industry and society. The network invites all ways of reasoning, considering all types of data applicable for almost all sectors of science and industry. We do this while being aware of data safety and security, and striving to explainable and trustworthy outcomes. ELISE works in cooperation with ELLIS (European Laboratory for Learning and Intelligent Systems). ELISE is part of the EU Horizon 2020 ICT-48 portfolio, and is coordinated by Aalto University.
ELISE connects to the ELLIS Society. The project was set up to attract students and experienced researchers, to sustain itself at the highest level of research in academia, and to spread its knowledge and methods in research, industry and society.
ELISE starts from machine learning as the current core technology of AI. The network invites all ways of reasoning, and considers all types of data which are applicable for almost all sectors of science and industry. ELISE works from an awareness of data safety and security, while striving to achieve explainable and trustworthy outcomes.
The project was active in 2020-2024. The objectives were:
Objective 1: Establish a network of excellent researchers and laboratories that act as local anchors across Europe, representing the community; provide experts within society; and coordinate a joint effort across the continent.
Objective 2: Build an attractive training network for junior scientists that keeps them in Europe by offering the highest quality training for Academic Excellence in Machine Learning.
Objective 3: Make industry involved with elite academic research so that participating companies’ AI/ML research competences will rival those of large industry laboratories.
Objective 4: Establish a sustainable ecosystem of machine learning stakeholders covering the value network to facilitate and accelerate a broad integration of machine learning technologies.
Objective 5: Make concrete research-based steps to obtain ethical, robust, and trustworthy AI / ML methods and practices.
ELISE implemented six different activity streams:
Real-Time, Multi-Modal, High Resolution Image Synthesization from Point Clouds
Fully Synthetic Longitudinal Real-World Data From Hearing Aid Wearers for Public Health Policy Modeling
Deliverable of the ELISE project on AI policies