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Trustworthy AI Cluster

Trustworthy AI Cluster

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.

New Carbon Tracker Release

New Carbon Tracker Release

CarbonTracker has released its latest v1.2.0 version, packed with new features and improvements for carbon monitoring enthusiasts

Challenges in Embedded Devices & Artificial Intelligence

Challenges in Embedded Devices & Artificial Intelligence

Prof. Dr. Paul Lukowicz, SustainML’s partner, delivered an insightful talk on the future of cognitive technologies and their application in intelligent production.

Introducing a Simple and Efficient Framework in Green AI

Introducing a Simple and Efficient Framework in Green AI

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.

Carbontracker: Predicting the Deep Learning CO2 footprint

Carbontracker: Predicting the Deep Learning CO2 footprint

Carbontracker is a tool for tracking and predicting the carbon footprint and energy expenditure of Deep Learning (DL) training.

eProsima
IBM
DFKI
Inria
University Copenhagen
Uc3m
Technische Universität Kaiserslautern
Logo ALMA

SustainML is among these nine innovative projects dedicated to creating a sustainable ML framework for Green AI.

Coordinator Office Address

Plaza de la Encina 10-11, Núcleo 4, 2ª Pl.
28760 Tres cantos - Madrid (España)

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General information

EN-Funded_by_the_EU-POSThis project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070408.