Verónica Castro-AllendeThe RAIDO project is pioneering a transformative approach to artificial intelligence development, emphasizing ethically-minded sustainable AI technologies. Funded by an 8 million euro grant from Horizon Europe, RAIDO seeks to reshape the AI landscape by integrating cutting-edge methodologies that prioritize data efficiency, energy conservation, and socially responsible AI practices. Coordinated by the Joef Stefan Institute (JSI), RAIDO is built on four pillars that focus on optimizing computing resources, advancing artificial data generation, embedding fairness and transparency through explainable AI (XAI), and reducing energy consumption across various platforms. As RAIDO progresses, it will validate its groundbreaking technologies through high-impact demonstrators in sectors such as healthcare, smart farming, energy management, and robotics. These real-life applications illustrate RAIDO’s potential to revolutionize AI by making it more sustainable, reliable, and transparent. From improving energy grid management with AI-driven optimization to enhancing precision agriculture through multispectral imaging, RAIDO’s contributions are setting new standards for Green AI. This project not only strengthens Europe’s leadership in AI research but also sets a benchmark for future AI developments that align technological advancement with environmental consciousness and social responsibility.
Pioneering Trustworthy and Sustainable AI for a New Era
The RAIDO project represents a pioneer in artificial intelligence ( AI ) technologies, evoking a new era of trustworthy and environmentally conscious AI. RAIDO’s main objectives are to reshape the Artificial landscape by incorporating cutting-edge methodologies into a systematic platform that prioritizes data efficiency and energy conservation as well as promotes social AI practices. This integrated approach makes it easier to create AI solutions that are both effective and moral, making AI more visible and trustworthy for both businesses and researchers.
RAIDO ( Grant No. 101135800 ) is a project that received funding from Horizon Europe‘s call HORIZON-CL4-2023-HUMAN-01-01. The project, which started on January 1st, 2024, is funded by an 8 million euro Research and Innovation Action Grant that will be in place for 36 months. The Joef Stefan Institute ( JSI) serves as RAIDO’s coordinator.
RAIDO’s framework is constructed around four strong pillars, each focusing on important aspects of AI optimisation and sustainability. The second pillar reduces the need for large, sympathetic datasets by advancing sophisticated artificial data generation techniques and novel data curation techniques. The next pillar introduces AI models and orchestrators that optimize computing resources while maintaining high performance. The third pillar, which incorporates fairness and transparency directly into AI models through creative explainable AI (XAI) techniques, is at the heart of the third pillar. The fifth pillar, which focuses on deployment, makes use of AI orchestration to reduce and lower the energy consumption of AI systems across a range of platforms.
The RAIDO use cases:
As RAIDO progresses, it is poised to validate its groundbreaking technologies through four high-impact real-life demonstrators, each designed to address specific challenges and opportunities within different sectors: Healthcare, Smart Farming, Robotics, and Energy Management. These demonstrators help to demonstrate the platform’s viability by demonstrating its adaptability to various business needs, as well as demonstrate its ability to revolutionize AI applications.
Energy grid management
This demonstration uses AI-driven optimisation to increase energy grid reliability and efficiency. RAIDO leverages its components to optimise AI models, making them reputable, reliable, and energy efficient. It is able to better predict energy demands and integrate alternative energy sources. This includes the use of Digital Twins, which help reduce waste and promote energy sustainability.
Precision agriculture
The next demonstrator uses AI to improve crop yield and resource management in the field of bright farming. RAIDO uses multispectral imaging and AI analytics to identify plant diseases first and forecast crop growth, enabling farmers to make informed decisions that increase productivity while lowering climate impact. This demonstration demonstrates how AI can make traditional farming more accurate and managed.
Healthcare personalisation
The second demonstrator explores the use of AI in individualized healthcare, especially in pharmacogenetics. RAIDO’s AI models use genomic data to model adult responses to various medications, aiming to improve treatment options and lessen adverse drug reactions. This application demonstrates the ability of AI to scale-up healthcare, providing more effective treatments that are tailored to specific genetic profiles.
Robotics for bio-based composites
Finally, the robotics demonstration uses AI to improve and enhance the fiber-reinforced composite manufacturing processes at plants. RAIDO uses cutting-edge machine learning methods and human-in-the-loop systems to drastically shorten the time and expense involved in producing these green materials while enhancing their structural properties.
Each demonstrator tests RAIDO’s useful applications, showcasing green, effective, and ethical AI solutions across different industries, shaping a better future.
The RAIDO project makes a significant contribution to the realization of Green AI by firmly rooted itself in the intersection of next-generation Artificial technology and ecological practices. The RAIDO initiative is a step forward in developing innovative standards for AI development in addition to strengthening Europe’s position as a leader in world Artificial research. These standards are carefully crafted to minimize ecological impact and are deeply connected to the fundamental human values of fairness and transparency. As such, RAIDO is setting a benchmark for future AI projects, proving that technological advancement can really go hand-in-hand with environmental consciousness and social responsibility.
