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AI watch, Revisiting technology readiness levels for relevant artificial intelligence technologies

AI watch, Revisiting technology readiness levels for relevant artificial intelligence technologies

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Artificial intelligence (AI) offers the potential to transform our lives in radical ways. However, we lack the tools to determine which achievements will be attained in the near future. Also, we usually underestimate which various technologies in AI are capable of today. Certainly, the translation from scientific papers and benchmark performance to products is faster in AI than in other

non-digital sectors. However, it is often the case that research breakthroughs do not directly translate to a technology that is ready to use in real-world environments. This report constitutes the second edition of a study proposing an example-based methodology to categorise and assess several AI technologies, by mapping them onto Technology Readiness Levels (TRL) (e.g., maturity and availability levels). We first interpret the nine TRLs in the context of AI and identify different categories in AI to which they can be assigned. We then introduce new bidimensional plots, called readiness-vs-generality charts, where we see that higher TRLs are achievable for low-generality technologies focusing on narrow or specific abilities, while high TRLs are still out of reach for more general capabilities. In an incremental way, this edition builds on the first report on the topic by updating the assessment of the original set of AI technologies and complementing it with an analysis of new AI technologies. We include numerous examples of AI technologies in a variety of fields and show their readiness-vs-generality charts, serving as a base for a broader discussion of AI technologies. Finally, we use the dynamics of several AI technologies at different generality levels and moments of time to forecast some short-term and mid-term trends for AI.

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Publicatiedatum: 2022

Institutionele auteur(s): Gemeenschappelijk Centrum voor onderzoek ( Europese Commissie )

Persoonlijke auteurs: Martinez-Plumed, Fernando ;  Caballero, Fernando ;  Castellano-Falcon, David ;  Fernandez-Llorca, David ;  Gomez, Emilia ;  Hupont-Torres, Isabelle ;  Merino, Luis ;  Monserrat, Carlos ;  Hernandez-Orallo, Jose

Thema's Informatietechnologie en telecommunicatie

Onderwerp: biometrie , digitale eengemaakte markt , digitale inhoud , kunstmatige intelligentie , machinaal leren , onderzoeksverslag , optisch herkennen van tekens , technologische verandering

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ISSN

1831-9424

ISBN

978-92-76-52328-4

DOI

10.2760/495140

Catalogusnummer

KJ-NA-31066-EN-N

ISSN

1831-9424

ISBN

978-92-76-52328-4

DOI

10.2760/495140

Catalogusnummer

KJ-NA-31066-EN-N

Released on EU Publications: 2022-05-13

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Maintenance EN. Houd er rekening mee dat deze website deze week enkele updates ondergaat. Bijgevolg kunnen gebruikers instabiliteit en beperkte functionaliteit ervaren. Onze excuses voor het ongemak.. ("Google vertaald" uit het Engels origineel) Web Content Display (Global) ×. Publication Detail Actions Portlet. Toegankelijkheidshulpmiddelen. Toevoegen aan "Mijn publicaties" Automatische kennisgeving aanmaken. Permanente link. Metagegevens in RDF-formaat (Opent een nieuw venster) (Opent een nieuw venster) Embedden. More. Cancel. custom-survey-notification. Klik hier om uw feedback te geven. Publication Detail Portlet. Home. Download. Order. AI watch, Revisiting technology readiness levels for relevant artificial intelligence technologies. AI watch, Revisiting technology readiness levels for relevant artificial intelligence technologies. Metagegevens publicatie. Artificial intelligence (AI) offers the potential to transform our lives in radical ways. However, we lack the tools to determine which achievements will be attained in the near future. Also, we usually underestimate which various technologies in AI are capable of today. Certainly, the translation from scientific papers and benchmark performance to products is faster in AI than in other. non-digital sectors. However, it is often the case that research breakthroughs do not directly translate to a technology that is ready to use in real-world environments. This report constitutes the second edition of a study proposing an example-based methodology to categorise and assess several AI technologies, by mapping them onto Technology Readiness Levels (TRL) (e.g., maturity and availability levels). We first interpret the nine TRLs in the context of AI and identify different categories in AI to which they can be assigned. We then introduce new bidimensional plots, called readiness-vs-generality charts, where we see that higher TRLs are achievable for low-generality technologies focusing on narrow or specific abilities, while high TRLs are still out of reach for more general capabilities. In an incremental way, this edition builds on the first report on the topic by updating the assessment of the original set of AI technologies and complementing it with an analysis of new AI technologies. We include numerous examples of AI technologies in a variety of fields and show their readiness-vs-generality charts, serving as a base for a broader discussion of AI technologies. Finally, we use the dynamics of several AI technologies at different generality levels and moments of time to forecast some short-term and mid-term trends for AI. Meer informatie. Minder informatie. Citeerwijze. Downloads en andere talen. Close. Beschikbare talen en formaten. Download. X. Beschikbare talen en formaten. Engels (en) pdf. Publicatiegegevens. Gerelateerde publicaties. Publicatiedatum: 2022. Institutionele auteur(s): Gemeenschappelijk Centrum voor onderzoek ( Europese Commissie ) Persoonlijke auteurs: Martinez-Plumed, Fernando ;  Caballero, Fernando ;  Castellano-Falcon, David ;  Fernandez-Llorca, David ;  Gomez, Emilia ;  Hupont-Torres, Isabelle ;  Merino, Luis ;  Monserrat, Carlos ;  Hernandez-Orallo, Jose. Thema's Informatietechnologie en telecommunicatie. Onderwerp: biometrie , digitale eengemaakte markt , digitale inhoud , kunstmatige intelligentie , machinaal leren , onderzoeksverslag , optisch herkennen van tekens , technologische verandering. PDF. ISSN. 1831-9424. ISBN. 978-92-76-52328-4. DOI. 10.2760/495140. Catalogusnummer. KJ-NA-31066-EN-N. ISSN. 1831-9424. ISBN. 978-92-76-52328-4. DOI. 10.2760/495140. Catalogusnummer. KJ-NA-31066-EN-N. Released on EU Publications: 2022-05-13. Meer informatie. Minder informatie. Alle uitgaven in deze reeks. Pop up window annotations. Did you know that you can annotate your document and share your annotations? Publication Viewer. Documentviewer. Open webversie in een afzonderlijk venster. Terug naar de resultatenlijst. Publication Details Links Portlet.