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Artificial Intelligence

Definition: Artificial Intelligence ABB is an Application Component that enables the implementation of algorithms, machine learning, and deep learning techniques to enable machines to perform tasks that typically require human-like intelligence, such as perception, reasoning, learning, and decision-making

Source: European Comision

Source reference: https://digital-strategy.ec.europa.eu/en/library/definition-artificial-…

Last modification: 2024-01-28

Identifier: http://data.europa.eu/dr8/ArtificialIntelligenceApplicationComponent

LOST view: Technical view - application

EIRA concept: eira:ArchitectureBuildingBlock

ABB name: eira:ArtificialIntelligenceApplicationComponent

Example: The following implementation is an example on how this specific Architecture Building Block (ABB) can be instantiated as a Solution Building Block (SBB): PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. https://pytorch.org/

Interoperability Saliency: The Artificial Intelligence Application Component ABB is salient for technical interoperability because it provides tools and components that are able to perform operations that would require human intervention such as perception, reasoning, learning, and decision-making. By training artificial intelligence components, digital public services could reach an additional level of maturity increasing efficiency and effectiveness on interoperable processes without requiring human intervention.

Interoperability Dimension: Structural IoP

Additional identifier: http://data.europa.eu/dr8/ArtificialIntelligenceApplicationComponent

EIF Layer: TechnicalApplication

EIRA properties

Namespace URI
rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#
skos: http://www.w3.org/2004/02/skos/core#
dct: http://purl.org/dc/terms/
eira: http://data.europa.eu/dr8/
Property Value
rdf:type http://www.w3.org/2004/02/skos/core#Concept
skos:notation Properties of Artificial Intelligence
dct:identifier http://data.europa.eu/dr8/ArtificialIntelligenceApplicationComponent_Properties
dct:identifier http://data.europa.eu/dr8/ArtificialIntelligenceApplicationComponent
skos:prefLabel Properties of Artificial Intelligence
eira:PURI http://data.europa.eu/dr8/ArtificialIntelligenceApplicationComponent
dct:type eira:ArtificialIntelligenceApplicationComponent
dct:modified 2024-01-28
eira:synonym
skos:definition Artificial Intelligence ABB is an Application Component that enables the implementation of algorithms, machine learning, and deep learning techniques to enable machines to perform tasks that typically require human-like intelligence, such as perception, reasoning, learning, and decision-making
eira:definitionSource European Comision
eira:definitionSourceReference https://digital-strategy.ec.europa.eu/en/library/definition-artificial-intelligence-main-capabilities-and-scientific-disciplines
skos:example The following implementation is an example on how this specific Architecture Building Block (ABB) can be instantiated as a Solution Building Block (SBB): PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. https://pytorch.org/
eira:iopSaliency The Artificial Intelligence Application Component ABB is salient for technical interoperability because it provides tools and components that are able to perform operations that would require human intervention such as perception, reasoning, learning, and decision-making. By training artificial intelligence components, digital public services could reach an additional level of maturity increasing efficiency and effectiveness on interoperable processes without requiring human intervention.
skos:note
eira:concept eira:ArchitectureBuildingBlock
eira:iopDimension Structural IoP
eira:view Technical view - application
eira:eifLayer TechnicalApplication