Preserving data privacy in Machine Learning pipelines with Federated Learning

FAME's project blog
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.

Leveraging Large Language Models for Financial Predictions

FAME project blog
In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.

FAME: Federated Decentralized Trusted Data Marketplace for Embedded Finance

IEEE
Due to its multivariate and multipurpose use and reuse, data’s worth is dramatically increasing, leading to an era characterized by the generation of data marketplaces towards accessing, selling, sharing, and trading data and data assets.

Multi-cloud provisioning of business processes

The Cloud offers enhanced flexibility in the management of resources while it promises the reduction of its cost as well as its infinite scalability. In this way, due to these advantages, there is a recent move towards migrating business processes (BPs) in the Cloud.