eProsima is committed to fostering a more sustainable future. Leading the SustainML project, eProsima aims to significantly reduce the environmental impact of machine learning (ML) applications, reducing CO2 emissions and enhancing energy efficiency. By integrating the DDS communication layer into the SustainML framework, eProsima strives to optimize data sharing and enhance overall efficiency, aligning with SustainML’s ambitious environmental goals.
HORIZON-CLA-2021-HUMAN-01 is the call of the European Commission under which nine projects were funded. During these projects, solid scientific developments will be complemented by tools and processes for design, testing and validation, certification, software engineering methodologies, and approaches to modularity and interoperability at real-world applications. The funded projects propose standardization methods to foster the AI industry, helping to create and guarantee trustworthy and ethical AI and supporting the Commission regulatory framework.
CarbonTracker has released its latest v1.2.0 version, packed with new features and improvements for carbon monitoring enthusiasts
Prof. Dr. Paul Lukowicz, SustainML’s partner, delivered an insightful talk on the future of cognitive technologies and their application in intelligent production.
SustainML is committed to reducing the carbon footprint in the ML processes. With this goal in mind, the partner project University of Copenhagen, has developed a framework for self-supervised image segmentation.
SustainML is among these nine innovative projects dedicated to creating a sustainable ML framework for Green AI.
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This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070408.