Learn how to build Intelligent Distributed Systems in ROS2 using AML-IP for Cloud Model Serving to Edge Robots with this presentation delivered by Raúl Sánchez-Mateos.
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ALMA is an EU-funded project that aims to leverage Algebraic Machine Learning (AML) properties to develop a new generation of interactive, human-centric machine learning systems.
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!
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.
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.
The ALMA project leverages AML properties to develop a new generation of interactive, human-centered machine learning systems.
Coordinator Office Address
Plaza de la Encina 10-11, Núcleo 4, 2ª Pl.
28760 Tres cantos - Madrid (España)
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952091.