eProsima is proud to announce the release of SustainML v0.1.0, the first official version of their backend and developer framework for sustainable machine learning. A comprehensive backend library and end-to-end developer framework designed to bring environmental awareness to every stage of machine learning. This inaugural release delivers all the core plumbing for orchestrating tasks, querying metadata, profiling energy and latency, and shipping a rich, Docker-based front-end.
On April 25, 2025, INRIA, a prominent partner in the SustainML project, presented significant research findings at the CHI Conference on Human Factors in Computing Systems (CHI 2025). Their paper, titled "Should I Choose a Smaller Model?: Understanding ML Model Selection and Its Impact on Sustainability", delves deeply into the sustainability considerations within Machine Learning (ML) model selection processes, underscoring the pressing need for environmentally responsible computing practices.
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
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.
