- Ericsson Cognitive Labs focus on the development of cutting-edge technologies such as Geometric AI and Machine Learning, with applications both in the world of telecommunications and in other areas from which society can benefit.
- In Spain, one of the reference regions of Ericsson’s R&D activities in Cognitive Networks Solutions (CNS), Ericsson and Universidad Pontificia Comillas (ICAI) have established a partnership to drive joint research in AI.
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Ericsson (NASDAQ:ERIC, news, filings) launches Cognitive Labs, an innovative initiative dedicated to research and development in artificial intelligence (AI). Cognitive Labs focuses on advanced technologies, such as Graph Neural Networks (GNN), Active Learning and Large-Scale Language Models, that the company uses to develop its solutions and that will be fundamental to the next generation of mobile communications. The initiative will not have a dedicated physical location but will operate virtually with teams and activities centered in a few key locations such as Madrid, Malaga and Cairo to start. With Cognitive Labs, Ericsson reaffirms its commitment to continuous improvement and efficiency in its technology solutions, while extending their application to other areas such as healthcare, from which society as a whole can benefit.
The initiative, in collaboration with the open source community, will enable Ericsson to further advance AI research, attract researchers and data scientists, and create better solutions for their customers.
As part of its commitment to the open-source community, Cognitive Labs has established three distinct labs to continue its research activities and develop libraries as reusable components:
- GAI Lab (Geometric Artificial Intelligence Lab): focusing on Geometric AI, explainability in geometric learning, graph generation and temporal GNNs. It is expected to have a major impact in areas such as drug discovery or the search of more efficient drugs.
- MLR Lab (Machine Learning and Reasoning Lab): Dedicated to optimizing training models and reinforcement learning. The research developed within this group is expected to have a significant impact on time and energy savings in the training of AI models, and the creation of digital twins that simulate the reality that surrounds us.
- FAI Lab (Fundamental Artificial Intelligence Lab): Focuses on creating foundational AI models, such as LLMs. This Lab is focused on researching technologies that will have a major impact on automating processes and improving efficiency. It will lead the way in creating language models in telecommunications.
Jean-Christophe Laneri, Head of Cognitive Network Solutions at Ericsson, says: “Cognitive Labs represents our commitment to lead innovation in AI and make a significant contribution to the open source community. Our mission is to create world-class research that can benefit the academic community and enhances our products to better serve our customers.”
Agreement with Universidad Pontificia Comillas
Ericsson Spain is positioned as one of the reference regions for Cognitive Labs, thanks to the important R&D activities that Ericsson carries out from Madrid and Málaga around Cognitive Networks Solutions (CNS).
This is further strengthened by the recent agreement reached with Universidad Pontificia Comillas through its Engineering School (Comillas ICAI). As part of the Cognitive Labs initiative, Ericsson Spain has signed a research alliance with the university to collaborate in open source initiatives and joint publications.
The close collaboration between top data scientists and engineers from Ericsson and ICAI’s teams will enable Ericsson Spain to lead innovation at the national and European levels, strengthening its position as a benchmark in technology and development.
For more information about Cognitive Labs and to learn more about other research from this initiative, visit Ericsson Cognitive Labs hub site, and the Ericsson Cognitive Network Solutions portfolio page.
About Ericsson Cognitive Networks Solutions
Ericsson’s AI research in mobile communications focuses on network optimization, generating digital twins to simulate the behavior of offline telecom networks, and incident detection using advanced state-of-the-art models to even detect a problem even before it occurs.
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