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Reliable AI and Data Optimisation

Project description

Developing trustworthy and green AI solutions

The EU-funded RAIDO project aims to create a unified platform for developing reliable, ethical and energy-efficient AI. Using tools such as digital twins and diffusion models, it will automate data curation to create high-quality and unbiased training data, and incorporate ethical safeguards to ensure AI systems are safe and fair, particularly in critical applications. The project will also integrate explainable AI and blockchain techniques to ensure the transparency and reliability of AI models. Lastly, it will develop data/compute-efficient models and an AI orchestrator to reduce energy consumption. The framework will be tested through four real-world demonstrators in applications such as smart grids, computer vision-based farming, healthcare and robotics.

Objective

RAIDO is a powerful framework solution designed to develop trustworthy and green artificial intelligence (AI). Trustworthy AI focuses on ensuring the reliability, safety, and unbiased optimization and deployment of AI systems, particularly in critical applications such as healthcare, farming, energy, and robotics. On the other hand, Green AI involves the development and deployment of energy-efficient and environmentally sustainable AI technologies, leading to reduced environmental impact and improved resource management.

RAIDO provides an array of automated data curation and enrichment methods, including digital twins and diffusion models, to create high-quality, representative, unbiased, and compliant training data. It also offers various data- and compute-efficient models and tools to create energy-efficient Green AI, such as few- and zero-shot learning, dataset and model search, data and model distillation, and continual learning.

To ensure the transparency, explainability, and reliability of the optimized AI models and data handling processes, RAIDO uses various XAI methods, decentralized blockchain, feedback-based reinforcement learning, novel KPIs, and visualization techniques. Additionally, the innovative AI orchestrator optimizes related tasks and processes, reducing the overall energy consumption and environmental footprint of the models during both development and deployment.

RAIDO emphasizes the development of dynamic interfaces that support the appropriate AI paradigms (central, distributed, dynamic, hybrid) and enable seamless adaptation to the needs of the use situation. Furthermore, RAIDO will be evaluated through four real-life demonstrators in key application domains, such as smart grids, computer vision-based smart farming, healthcare, and robotics, showcasing notable societal and market impact.

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Programme(s)

Topic(s)

Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

(opens in new window) HORIZON-CL4-2023-HUMAN-01-CNECT

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Coordinator

INSTITUT JOZEF STEFAN
Net EU contribution
€ 561 187,50
Address
Jamova 39
1000 Ljubljana
Slovenia
Region
Slovenija Zahodna Slovenija Osrednjeslovenska
Activity type
Research Organisations
Links
Total cost
€ 561 187,50

Participants (24)

Partners (6)