AML IP Workload Distribution Scenario

The AML-IP tool can be used to parallelize complex computational tasks, deploying it locally, remotely, or even at the same time. Keep reading to discover how!

Algebraic AI at Conexion AIHUB-Industria

ALMA was represented by Algebraic AI at Conexión AIHUB-Industria, an event organized by the CSIC (Spanish National Research Council) for companies and researchers to discuss, promote and consolidate public-private collaboration in R&D&I in artificial intelligence.

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.

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.

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