Algebraic Machine Learning

This white paper explains, in simple terms, the main ideas behind Algebraic Machine Learning (AML) and provides insights on how and why it works. AML is a symbolic method that is good for reasoning and has the advantage of being able to learn from data. AML can use continuous input and output, can deal with uncertainty and can combine learning from both, data and formulas. These unique properties show that the main limitations of symbolic methods can be overcome and open a path to a more transparent, trustworthy and understandable AI.

AI from a laptop

In this post we will briefly outline our understanding of human-centered and Explainable AI (xAI) and the differences and opportunities we see. We will then present our preliminary work on an algebraic machine learning approach as an example to combine both.

ALMA at FIWARE Global Summit

 

ALMA was present at the FIWARE Global Summit 2022. The event, hosted in Gran Canaria, gathered people from all over the world interested in the framework of open source technologies, open standards, data spaces and smart data models.

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