{"id":2842,"date":"2024-04-25T20:43:17","date_gmt":"2024-04-25T20:43:17","guid":{"rendered":"https:\/\/www.xadv.eu\/?p=2842"},"modified":"2024-05-12T13:36:17","modified_gmt":"2024-05-12T13:36:17","slug":"a-generative-ai-es-machine-learning-integralasa-a-telecom-halozatokba","status":"publish","type":"post","link":"https:\/\/www.xadv.eu\/hu\/2024\/04\/25\/a-generative-ai-es-machine-learning-integralasa-a-telecom-halozatokba\/","title":{"rendered":"Generative AI \u00e9s Machine Learning az 5G H\u00e1l\u00f3zatokban."},"content":{"rendered":"<div data-elementor-type=\"wp-post\" data-elementor-id=\"2842\" class=\"elementor elementor-2842\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-69db88ba elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"69db88ba\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1d5dbd97\" data-id=\"1d5dbd97\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4aca9df0 elementor-widget elementor-widget-text-editor\" data-id=\"4aca9df0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.20.0 - 26-03-2024 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><!-- wp:paragraph --><\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p>Az \u00faj gener\u00e1ci\u00f3s telekom h\u00e1l\u00f3zatok eszk\u00f6zeinek \u00f6sszehangol\u00e1sa \u00e9s ir\u00e1ny\u00edt\u00e1sa kiemelked\u0151en fontos a z\u00f6kken\u0151mentes m\u0171k\u00f6d\u00e9s, az optim\u00e1lis min\u0151s\u00e9g \u00e9s \u00fcgyf\u00e9l\u00e9lm\u00e9ny biztos\u00edt\u00e1s\u00e1ban. A technol\u00f3gia folyamatos fejl\u0151d\u00e9s\u00e9vel a generat\u00edv mesters\u00e9ges intelligencia (AI), a g\u00e9pi tanul\u00e1s (ML) \u00e9s az ezeken alapul\u00f3 funkci\u00f3k alkalmaz\u00e1sa a t\u00e1vk\u00f6zl\u00e9si h\u00e1l\u00f3zatok automatiz\u00e1l\u00e1s\u00e1nak \u00e1talak\u00edt\u00e1s\u00e1ban nagy lehet\u0151s\u00e9geket hordoz.<\/p>\n<p>\u00a0<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:heading {\"level\":4} --><\/p>\n<h4 class=\"wp-block-heading\"><strong>Generative AI a H\u00e1l\u00f3zat Automatiz\u00e1l\u00e1sban<\/strong><\/h4>\n<p><!-- \/wp:heading --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Adatvez\u00e9relt H\u00e1l\u00f3zat Automatiz\u00e1l\u00e1s.<\/strong> A h\u00e1l\u00f3zat ir\u00e1ny\u00edt\u00e1sban a generat\u00edv AI algoritmusokat \u00e9s modelleket haszn\u00e1lva automatiz\u00e1lja az \u00f6sszetett d\u00f6nt\u00e9shozatali folyamatokat, \u00e9s jav\u00edtja a h\u00e1l\u00f3zat min\u0151s\u00e9gi jellemz\u0151it az\u00e1ltal, hogy val\u00f3s id\u0151ben el\u0151rejelzi az esteleges felmer\u00fcl\u0151 h\u00e1l\u00f3zati probl\u00e9m\u00e1kat \u00e9s a meghat\u00e1rozott felt\u00e9telek alapj\u00e1n adopt\u00e1lhatja a h\u00e1l\u00f3zat m\u0171k\u00f6d\u00e9s\u00e9t a v\u00e1ltoz\u00f3 k\u00f6r\u00fclm\u00e9nyekhez. Az ML adatot gy\u0171jt \u00e9s elemez, majd algoritmusokkal p\u00e1ros\u00edtva az AI lehet\u0151v\u00e9 teszi a rendszer sz\u00e1m\u00e1ra, hogy tanuljon a begy\u0171jt\u00f6tt adatokb\u00f3l. A generat\u00edv AI hat\u00e9kony eszk\u00f6z\u00f6zt biztos\u00edt a h\u00e1l\u00f3zat \u00fczemeltet\u0151k sz\u00e1m\u00e1ra az er\u0151forr\u00e1sok eloszt\u00e1s\u00e1nak optimaliz\u00e1l\u00e1s\u00e1hoz, ez\u00e1ltal a h\u00e1l\u00f3zat hat\u00e9konys\u00e1g\u00e1nak jav\u00edt\u00e1s\u00e1hoz \u00e9s magasabb szint\u0171 szolg\u00e1ltat\u00e1sny\u00fajt\u00e1s\u00e1hoz.<\/p>\n<p>\u00a0<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:heading {\"level\":4} --><\/p>\n<h4 class=\"wp-block-heading\"><strong>Generative AI a H\u00e1l\u00f3zat Optimaliz\u00e1l\u00e1sban<\/strong><\/h4>\n<p><!-- \/wp:heading --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Automatikus h\u00e1l\u00f3zatoptimaliz\u00e1l\u00e1s.<\/strong> Az AI \u00e9s ML algoritmusok nagymennyis\u00e9g\u0171 h\u00e1l\u00f3zati adatot gy\u0171jtenek \u00e9s forgalmi mint\u00e1kat, felhaszn\u00e1l\u00f3i viselked\u00e9st \u00e9s performance mutat\u00f3kat elemeznek. Az elemz\u00e9s \u00e1ltal azonos\u00edthat\u00f3ak a sz\u0171k keresztmetszetek, el\u0151re jelezhet\u0151k a h\u00e1l\u00f3zat performance ingadoz\u00e1sai, ami m\u00f3dos\u00edt\u00e1st gener\u00e1lhat a h\u00e1l\u00f3zati er\u0151forr\u00e1sok optimaliz\u00e1l\u00e1s\u00e1ra, ezzel jav\u00edtva a h\u00e1l\u00f3zat hat\u00e9konys\u00e1g\u00e1t \u00e9s a szolg\u00e1ltat\u00e1s min\u0151s\u00e9g\u00e9t.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Val\u00f3s idej\u0171 h\u00e1l\u00f3zat adapt\u00e1ci\u00f3:<\/strong> A h\u00e1l\u00f3zati min\u0151s\u00e9g folyamatos figyel\u00e9s\u00e9vel a generat\u00edv AI dinamikusan m\u00f3dos\u00edthatja a h\u00e1l\u00f3zati konfigur\u00e1ci\u00f3kat \u00e9s \u00e1tir\u00e1ny\u00edthatja a forgalmat a torl\u00f3d\u00e1sok elker\u00fcl\u00e9se \u00e9rdek\u00e9ben, \u00edgy biztos\u00edtva a felhaszn\u00e1l\u00f3i \u00e9lm\u00e9nyt. Az ML algoritmusok tanulhatnak ezekb\u0151l az adapt\u00edv d\u00f6nt\u00e9sekb\u0151l, \u00e9s alkalmazva azokat jav\u00edthatj\u00e1k a h\u00e1l\u00f3zatmin\u0151s\u00e9get.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Rendelleness\u00e9gek \u00e9szlel\u00e9se:<\/strong> Az AI \u00e9s ML alap\u00fa proakt\u00edv optimaliz\u00e1l\u00e1s jav\u00edthatja a h\u00e1l\u00f3zati performance-t \u00e9s a felhaszn\u00e1l\u00f3i \u00e9lm\u00e9nyt. A RAN intelligens vez\u00e9rl\u0151 (RIC) t\u00f6bb konfigur\u00e1ci\u00f3s \u00e9s optimaliz\u00e1l\u00e1si m\u0171veletet kezel p\u00e1rhuzamosan. Ahhoz hogy elker\u00fclje az esetleges konfliktusokat ezen parancsok alatt vagy ut\u00e1n konfliktus ontrol funkci\u00f3t alkalmaz. A h\u00e1l\u00f3zat jelleg\u00e9b\u0151l ad\u00f3d\u00f3an azonban tov\u00e1bbra is el\u0151fordulhatnak meghib\u00e1sod\u00e1sok. Az AI alap\u00fa abnormalit\u00e1s \u00e9szlel\u00e9si funkci\u00f3 az alkalmazott ML modellek \u00e1ltal k\u00e9pes \u00e9szlelni, ha egy performance mutat\u00f3 vagy esem\u00e9ny az el\u0151re meghat\u00e1rozott tartom\u00e1nyon vagy hat\u00e1r\u00e9rt\u00e9keken k\u00edv\u00fcl esik. A funkci\u00f3 ezeket az esem\u00e9nyeket jelenti \u00e9s a h\u00e1l\u00f3zati SMO azonnali korrekci\u00f3s int\u00e9zked\u00e9seket hajt v\u00e9gre.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Predikt\u00edv Maintanace<\/strong>. Az AI \u00e1ltal vez\u00e9relt \u00e9s ML modelleken alapul\u00f3 predikt\u00edv maintanace k\u00e9pes azonos\u00edtani a lehets\u00e9ges h\u00e1l\u00f3zati hib\u00e1kat vagy teljes\u00edtm\u00e9nyroml\u00e1st, miel\u0151tt azok bek\u00f6vetkezn\u00e9nek. A h\u00e1l\u00f3zati adatok folyamatos figyel\u00e9s\u00e9vel az anom\u00e1li\u00e1k \u00e9szlel\u00e9se \u00e1ltal az \u00fczemeltet\u0151k proakt\u00edvan kezelhetik a probl\u00e9m\u00e1kat, cs\u00f6kkentve a h\u00e1l\u00f3zat le\u00e1ll\u00e1sokat, ez\u00e1ltal jav\u00edthatj\u00e1k a h\u00e1l\u00f3zat megb\u00edzhat\u00f3s\u00e1g\u00e1t.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:heading {\"level\":4} --><\/p>\n<h4 class=\"wp-block-heading\"><strong>\u00a0<\/strong><\/h4>\n<h4 class=\"wp-block-heading\"><strong>Generative AI Felhaszn\u00e1l\u00f3kra gyakorolt hat\u00e1s<\/strong>a<\/h4>\n<p><!-- \/wp:heading --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Felhaszn\u00e1l\u00f3i \u00e9lm\u00e9ny:<\/strong> Az generat\u00edv AI \u00e1ltal t\u00e1mogatott h\u00e1l\u00f3zati ir\u00e1ny\u00edt\u00e1s jobb min\u0151s\u00e9get, nagyobb adatsebess\u00e9get \u00e9s alacsonyabb k\u00e9sleltet\u00e9st biztos\u00edt az \u00fcgyfeleknek. A felhaszn\u00e1l\u00f3k a h\u00e1l\u00f3zati er\u0151forr\u00e1sok val\u00f3s idej\u0171 optimaliz\u00e1l\u00e1s\u00e1val m\u00e9g a cs\u00facsforgalmi id\u0151szakokban is magas min\u0151s\u00e9g\u0171 szolg\u00e1ltat\u00e1st \u00e9lvezhetnek.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Szem\u00e9lyre szabott szolg\u00e1ltat\u00e1sok.<\/strong> A generat\u00edv AI elemzi a felhaszn\u00e1l\u00f3i viselked\u00e9st \u00e9s figyelembe veszi a preferenci\u00e1kat, lehet\u0151v\u00e9 t\u00e9ve a h\u00e1l\u00f3zat \u00fczemeltet\u0151k sz\u00e1m\u00e1ra, hogy szem\u00e9lyre szabott szolg\u00e1ltat\u00e1sokat k\u00edn\u00e1ljanak. Az egy\u00e9ni ig\u00e9nyek meg\u00e9rt\u00e9s\u00e9vel a szolg\u00e1ltat\u00f3k c\u00e9lzott tartalmat, egyedi prom\u00f3ci\u00f3kat ny\u00fajthatnak, n\u00f6velve ezzel az \u00fcgyf\u00e9lel\u00e9gedetts\u00e9get.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Proakt\u00edv probl\u00e9mamegold\u00e1s:<\/strong> Az AI \u00e1ltal m\u0171k\u00f6dtetett h\u00e1l\u00f3zatok automatikusan \u00e9szlelik \u00e9s megoldj\u00e1k az esetleges felhaszn\u00e1l\u00f3i probl\u00e9m\u00e1kat, p\u00e9ld\u00e1ul a h\u00edv\u00e1s blokkol\u00e1st vagy a h\u00edv\u00e1s megszak\u00edt\u00e1sokat. Az \u00f6ngy\u00f3gy\u00edt\u00f3 (self-healing) mechanizmusok \u00e9s az intelligens hibaelh\u00e1r\u00edt\u00e1s r\u00e9v\u00e9n az \u00fcgyf\u00e9lpanaszok cs\u00f6kkenthet\u0151k, ami magasabb \u00fcgyf\u00e9l el\u00e9gedetts\u00e9ghez vezet.<\/p>\n<p>\u00a0<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:heading {\"level\":4} --><\/p>\n<h4 class=\"wp-block-heading\"><strong>Generative AI Szolg\u00e1ltat\u00f3kra gyakorolt hat\u00e1sa<\/strong><\/h4>\n<p><!-- \/wp:heading --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>K\u00f6lts\u00e9goptimaliz\u00e1l\u00e1s<\/strong> A mesters\u00e9ges intelligencia \u00e1ltal vez\u00e9relt h\u00e1l\u00f3zati ir\u00e1ny\u00edt\u00e1s optimaliz\u00e1lhatja az er\u0151forr\u00e1sok eloszt\u00e1s\u00e1t, minimaliz\u00e1lva a sz\u00fcks\u00e9gtelen infrastruktur\u00e1lis beruh\u00e1z\u00e1sokat \u00e9s cs\u00f6kkentve az \u00fczemeltet\u00e9si k\u00f6lts\u00e9geket. A h\u00e1l\u00f3zati konfigur\u00e1ci\u00f3k ig\u00e9ny szerinti dinamikus be\u00e1ll\u00edt\u00e1s\u00e1val a szolg\u00e1ltat\u00f3k nagyobb k\u00f6lts\u00e9ghat\u00e9konys\u00e1got \u00e9rhetnek el.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>\u00daj bev\u00e9teli lehet\u0151s\u00e9gek<\/strong>. A generat\u00edv AI nagymennyis\u00e9g\u0171 adat elemz\u00e9s\u00e9re val\u00f3 k\u00e9pess\u00e9g\u00e9vel a h\u00e1l\u00f3zat \u00fczemeltet\u0151k \u00faj bev\u00e9teli forr\u00e1sokat azonos\u00edthatnak. Az AI alap\u00fa elemz\u00e9s betekint\u00e9st ad a felhaszn\u00e1l\u00f3i viselked\u00e9sbe, a szolg\u00e1ltat\u00e1s haszn\u00e1lati mint\u00e1kba lehet\u0151v\u00e9 t\u00e9ve az \u00fczemeltet\u0151k sz\u00e1m\u00e1ra, hogy c\u00e9lzott marketing kamp\u00e1nyokat \u00e9s szolg\u00e1ltat\u00e1si aj\u00e1nlatokat ny\u00fajtsanak.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><strong>Sk\u00e1l\u00e1zhat\u00f3s\u00e1g \u00e9s j\u00f6v\u0151re val\u00f3 felk\u00e9sz\u00fclts\u00e9g.<\/strong> A generat\u00edv AI \u00e9s az ML alkalmaz\u00e1s\u00e1val a h\u00e1l\u00f3zat \u00fczemeltet\u0151k agilis \u00e9s m\u00e9retezhet\u0151 infrastrukt\u00far\u00e1kat \u00e9p\u00edthetnek ki, amelyek alkalmazkodhatnak a j\u00f6v\u0151beli technol\u00f3giai fejl\u0151d\u00e9shez. Ez a j\u00f6v\u0151biztos megk\u00f6zel\u00edt\u00e9s lehet\u0151v\u00e9 teszi az \u00fczemeltet\u0151k sz\u00e1m\u00e1ra, hogy a versenyt\u00e1rsak el\u00e9 ker\u00fcljenek \u00e9s kiel\u00e9g\u00edts\u00e9k a v\u00e1s\u00e1rl\u00f3i ig\u00e9nyeket.<\/p>\n<p>\u00a0<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:heading {\"level\":4} --><\/p>\n<h4 class=\"wp-block-heading\"><strong>\u00d6sszegz\u00e9s<\/strong><\/h4>\n<p><!-- \/wp:heading --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p>Az 5G NR \u00faj megold\u00e1sokat k\u00edn\u00e1l a nagyobb adatsebess\u00e9g, az alacsonyabb k\u00e9sleltet\u00e9s \u00e9s a massive IoT ter\u00e9n. Ezek az \u00fajdons\u00e1gok viszont kih\u00edv\u00e1sokkal \u00e9s neh\u00e9zs\u00e9gekkel is j\u00e1rnak.A h\u00e1l\u00f3zat\u00fczemeltet\u0151ket azonban t\u00e1mogathatj\u00e1k ezeknek a neh\u00e9zs\u00e9geknek a lek\u00fczd\u00e9s\u00e9t a generat\u00edv mesters\u00e9ges intelligencia, a g\u00e9pi tanul\u00e1s \u00e9s az ezeken alapul\u00f3 technol\u00f3gi\u00e1k integr\u00e1l\u00e1sa.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p>Az intelligens h\u00e1l\u00f3zati ir\u00e1ny\u00edt\u00e1s \u00e9s fel\u00fcgyeleti automatiz\u00e1l\u00e1s r\u00e9v\u00e9n az \u00fczemeltet\u0151k hat\u00e9konyan optimaliz\u00e1lhatj\u00e1k a h\u00e1l\u00f3zati er\u0151forr\u00e1sokat, dinamikusan alkalmazkodhatnak a v\u00e1ltoz\u00f3 k\u00f6r\u00fclm\u00e9nyekhez, \u00e9s z\u00f6kken\u0151mentes kapcsol\u00f3d\u00e1st biztos\u00edthatnak a v\u00e9gfelhaszn\u00e1l\u00f3k sz\u00e1m\u00e1ra.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p>Az AI-alap\u00fa automatiz\u00e1l\u00e1s l\u00e9tfontoss\u00e1g\u00fa szerepet fog j\u00e1tszani az 5G h\u00e1l\u00f3zatok \u00f6sszetetts\u00e9g\u00e9nek kezel\u00e9s\u00e9ben, lehet\u0151v\u00e9 t\u00e9ve az \u00fczemeltet\u0151k sz\u00e1m\u00e1ra, hogy hat\u00e9konyan kezelj\u00e9k a hatalmas mennyis\u00e9g\u0171 adatot, optimaliz\u00e1lj\u00e1k a h\u00e1l\u00f3zati kapacit\u00e1st, \u00e9s kiv\u00e1l\u00f3 h\u00e1l\u00f3zati teljes\u00edtm\u00e9nyt ny\u00fajtsanak. Ez pedig utat nyit az olyan \u00e1talakul\u00f3 haszn\u00e1lati eseteknek, mint az okos v\u00e1rosok, az auton\u00f3m j\u00e1rm\u0171vek, a virtu\u00e1lis val\u00f3s\u00e1g (VR).<\/p>\n<p><!-- \/wp:paragraph --><\/p>\n<p><!-- wp:paragraph --><\/p>\n<p>A t\u00e1vk\u00f6zl\u00e9si ipar folyamatosan fejl\u0151d\u00e9s\u00e9vel elengedhetetlen, hogy a h\u00e1l\u00f3zat \u00fczemeltet\u0151k alkalmazz\u00e1k a generat\u00edv AI \u00e9s a g\u00e9pi tanul\u00e1son alapul\u00f3 technol\u00f3gi\u00e1kat. Ezzel nemcsak az 5G kih\u00edv\u00e1sait tudj\u00e1k enyh\u00edteni, hanem a versenyt\u00e1rsak el\u0151tt j\u00e1rva k\u00f6nyebben felelhetnek meg az \u00fcgyfelek ig\u00e9nyeinek.<\/p>\n<p><!-- \/wp:paragraph --><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Az \u00faj gener\u00e1ci\u00f3s telekom h\u00e1l\u00f3zatok eszk\u00f6zeinek \u00f6sszehangol\u00e1sa \u00e9s ir\u00e1ny\u00edt\u00e1sa kiemelked\u0151en fontos a z\u00f6kken\u0151mentes m\u0171k\u00f6d\u00e9s, az optim\u00e1lis min\u0151s\u00e9g \u00e9s \u00fcgyf\u00e9l\u00e9lm\u00e9ny biztos\u00edt\u00e1s\u00e1ban. A technol\u00f3gia folyamatos fejl\u0151d\u00e9s\u00e9vel a generat\u00edv mesters\u00e9ges intelligencia (AI), a g\u00e9pi tanul\u00e1s (ML) \u00e9s az ezeken alapul\u00f3 funkci\u00f3k alkalmaz\u00e1sa a t\u00e1vk\u00f6zl\u00e9si h\u00e1l\u00f3zatok automatiz\u00e1l\u00e1s\u00e1nak \u00e1talak\u00edt\u00e1s\u00e1ban nagy lehet\u0151s\u00e9geket hordoz. Generative AI a H\u00e1l\u00f3zat Automatiz\u00e1l\u00e1sban Adatvez\u00e9relt H\u00e1l\u00f3zat Automatiz\u00e1l\u00e1s. &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/www.xadv.eu\/hu\/2024\/04\/25\/a-generative-ai-es-machine-learning-integralasa-a-telecom-halozatokba\/\"> <span class=\"screen-reader-text\">Generative AI \u00e9s Machine Learning az 5G H\u00e1l\u00f3zatokban.<\/span> Read More &raquo;<\/a><\/p>","protected":false},"author":1,"featured_media":2621,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","footnotes":""},"categories":[21,91,22,90,92],"tags":[],"class_list":["post-2842","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-5g","category-ai-in-telecom","category-cloud-ran","category-edge-computing","category-tco-strategies"],"_links":{"self":[{"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/posts\/2842","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/comments?post=2842"}],"version-history":[{"count":7,"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/posts\/2842\/revisions"}],"predecessor-version":[{"id":2853,"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/posts\/2842\/revisions\/2853"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/media\/2621"}],"wp:attachment":[{"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/media?parent=2842"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/categories?post=2842"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.xadv.eu\/hu\/wp-json\/wp\/v2\/tags?post=2842"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}