{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T23:31:06Z","timestamp":1768433466402,"version":"3.49.0"},"reference-count":34,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T00:00:00Z","timestamp":1707177600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"National Funds","doi-asserted-by":"publisher","award":["UIDB\/50014\/2020"],"award-info":[{"award-number":["UIDB\/50014\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"National Funds","doi-asserted-by":"publisher","award":["SFRH\/BD\/145119\/2019"],"award-info":[{"award-number":["SFRH\/BD\/145119\/2019"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Atoms"],"abstract":"<jats:p>Extreme learning machines explore nonlinear random projections to perform computing tasks on high-dimensional output spaces. Since training only occurs at the output layer, the approach has the potential to speed up the training process and the capacity to turn any physical system into a computing platform. Yet, requiring strong nonlinear dynamics, optical solutions operating at fast processing rates and low power can be hard to achieve with conventional nonlinear optical materials. In this context, this manuscript explores the possibility of using atomic gases in near-resonant conditions to implement an optical extreme learning machine leveraging their enhanced nonlinear optical properties. Our results suggest that these systems have the potential not only to work as an optical extreme learning machine but also to perform these computations at the few-photon level, paving opportunities for energy-efficient computing solutions.<\/jats:p>","DOI":"10.3390\/atoms12020010","type":"journal-article","created":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T03:22:31Z","timestamp":1707189751000},"page":"10","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Optical Extreme Learning Machines with Atomic Vapors"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8467-4357","authenticated-orcid":false,"given":"Nuno A.","family":"Silva","sequence":"first","affiliation":[{"name":"Center for Applied Photonics, Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"Departamento de F\u00edsica e Astronomia, Faculdade de Ci\u00eancias da Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"}]},{"given":"Vicente","family":"Rocha","sequence":"additional","affiliation":[{"name":"Center for Applied Photonics, Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"Departamento de F\u00edsica e Astronomia, Faculdade de Ci\u00eancias da Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"}]},{"given":"Tiago D.","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Center for Applied Photonics, Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"Departamento de F\u00edsica e Astronomia, Faculdade de Ci\u00eancias da Universidade do Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","article-title":"Deep learning in neural networks: An overview","volume":"61","author":"Schmidhuber","year":"2015","journal-title":"Neural Netw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.neunet.2019.03.005","article-title":"Recent advances in physical reservoir computing: A review","volume":"115","author":"Tanaka","year":"2019","journal-title":"Neural Netw."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"20190061","DOI":"10.1098\/rsta.2019.0061","article-title":"The future of computing beyond Moore\u2019s Law","volume":"378","author":"Shalf","year":"2020","journal-title":"Philos. 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