{"id":116932,"date":"2026-01-06T14:16:08","date_gmt":"2026-01-06T14:16:08","guid":{"rendered":"https:\/\/ekamu.net\/?p=116932"},"modified":"2026-01-06T14:16:08","modified_gmt":"2026-01-06T14:16:08","slug":"nvidiadan-otonom-araclar-icin-yeni-donem-alpamayo-tanitildi","status":"publish","type":"post","link":"https:\/\/ekamu.net\/index.php\/2026\/01\/06\/nvidiadan-otonom-araclar-icin-yeni-donem-alpamayo-tanitildi\/","title":{"rendered":"Nvidia\u2019dan otonom ara\u00e7lar i\u00e7in yeni d\u00f6nem: Alpamayo tan\u0131t\u0131ld\u0131"},"content":{"rendered":"

\n

<\/span> <\/figure>\n<\/p>\n

CES 2026<\/strong> sahnesinde Nvidia<\/strong>, otonom s\u00fcr\u00fc\u015f<\/strong> teknolojisine odaklanan Alpamayo<\/strong> adl\u0131 yeni a\u00e7\u0131k kaynakl\u0131 yapay zeka ailesini duyurdu. Alpamayo, yapay zeka modelleri, sim\u00fclasyon ara\u00e7lar\u0131 ve veri setlerinden olu\u015fan kapsaml\u0131 bir ekosistem sunarak otonom ara\u00e7lar\u0131n ve fiziksel robotlar\u0131n karma\u015f\u0131k ger\u00e7ek d\u00fcnya senaryolar\u0131n\u0131 insan benzeri bir muhakeme ile de\u011ferlendirmesini hedefliyor.<\/p>\n

Nvidia CEO\u2019su Jensen Huang, tan\u0131t\u0131m s\u0131ras\u0131nda yapt\u0131\u011f\u0131 a\u00e7\u0131klamada, fiziksel yapay zeka i\u00e7in d\u00f6n\u00fcm noktas\u0131na gelindi\u011fini vurgulad\u0131. Huang\u2019a g\u00f6re Alpamayo, makinelerin art\u0131k yaln\u0131zca alg\u0131lay\u0131p tepki vermekle kalmay\u0131p, neden-sonu\u00e7 ili\u015fkisi kurarak karar alabildi\u011fi bir d\u00f6nemin ba\u015flang\u0131c\u0131n\u0131 temsil ediyor. Bu yakla\u015f\u0131m sayesinde otonom ara\u00e7lar, daha \u00f6nce hi\u00e7 kar\u015f\u0131la\u015fmad\u0131klar\u0131 nadir ve karma\u015f\u0131k durumlarda bile g\u00fcvenli s\u00fcr\u00fc\u015f kararlar\u0131 \u00fcretebiliyor.<\/p>\n

Alpamayo 1 ile insan benzeri muhakeme<\/b><\/p>\n

Bu yeni yapay zeka ailesinin merkezinde yer alan Alpamayo 1, 10 milyar parametreli<\/strong> bir \u201cchain-of-thought\u201d yani ad\u0131m ad\u0131m d\u00fc\u015f\u00fcnme temelli g\u00f6rsel-dil-eylem<\/strong> (VLA) modeli olarak konumlan\u0131yor. Model, sens\u00f6rlerden gelen verileri yaln\u0131zca yorumlamakla yetinmiyor, ayn\u0131 zamanda bu veriler \u00fczerinden farkl\u0131 senaryolar\u0131 analiz ederek<\/strong> en g\u00fcvenli hareket plan\u0131n\u0131 olu\u015fturuyor. Hemen altta bir \u00f6rnek video da yer almakta:<\/p>\n

Nvidia Otomotiv Ba\u015fkan Yard\u0131mc\u0131s\u0131 Ali Kani, Alpamayo 1\u2019in \u00e7al\u0131\u015fma mant\u0131\u011f\u0131n\u0131, problemleri par\u00e7alara ay\u0131rarak her olas\u0131l\u0131\u011f\u0131 de\u011ferlendiren<\/strong> ve ard\u0131ndan en g\u00fcvenli yolu se\u00e7en<\/strong> bir muhakeme s\u00fcreci olarak tan\u0131ml\u0131yor. \u00d6rne\u011fin, yo\u011fun bir kav\u015fakta trafik lambalar\u0131n\u0131n \u00e7al\u0131\u015fmad\u0131\u011f\u0131 bir senaryoda, sistem daha \u00f6nce benzer bir durumla kar\u015f\u0131la\u015fmam\u0131\u015f olsa bile mant\u0131kl\u0131 ve g\u00fcvenli bir s\u00fcr\u00fc\u015f karar\u0131 verebiliyor.<\/p>\n

Jensen Huang ise bu yakla\u015f\u0131m\u0131, Alpamayo\u2019nun yaln\u0131zca direksiyon, fren ve gaz gibi fiziksel kontrol mekanizmalar\u0131n\u0131 y\u00f6netmedi\u011fini, ayn\u0131 zamanda hangi karar\u0131 neden ald\u0131\u011f\u0131n\u0131 a\u00e7\u0131klayabildi\u011fini<\/strong> vurgulayarak \u00f6zetliyor. Sistem, se\u00e7ti\u011fi eylemi, bu eyleme g\u00f6t\u00fcren gerek\u00e7eleri ve izleyece\u011fi rotay\u0131 \u015feffaf bi\u00e7imde ortaya koyabiliyor. Bu, d\u00fczenleyici kurumlar i\u00e7in \u00e7ok \u00f6nemli bir detay.<\/p>\n

2026\u2019n\u0131n ilk \u00e7eyre\u011finde Mercedes-Benz CLA\u2019ya geliyor<\/b><\/p>\n

Bu yeni mimari, s\u00fcr\u00fcc\u00fc destek ve otonom s\u00fcr\u00fc\u015f \u00f6zellikleriyle 2026\u2019n\u0131n ilk \u00e7eyre\u011finde<\/strong> Mercedes-Benz CLA<\/strong> modellerinde yollara \u00e7\u0131kacak. Dedi\u011fimiz gibi Nvidia, Alpamayo ile birlikte agresif bir a\u00e7\u0131k kaynak stratejisi izliyor. Bu yakla\u015f\u0131m, Tesla<\/strong>\u2019n\u0131n tamamen kapal\u0131 tuttu\u011fu Full Self-Driving <\/strong>(FSD) yaz\u0131l\u0131m\u0131na kar\u015f\u0131 Nvidia\u2019y\u0131 otonom s\u00fcr\u00fc\u015fte adeta bir \u201cotonominin Android\u2019i<\/strong>\u201d konumuna ta\u015f\u0131may\u0131 hedefliyor.<\/p>\n

Huang\u2019\u0131n a\u00e7\u0131klamas\u0131na g\u00f6re 2025 model Mercedes-Benz CLA, Nvidia\u2019n\u0131n yeni otonom s\u00fcr\u00fc\u015f y\u0131\u011f\u0131n\u0131na ve Alpamayo\u2019nun muhakeme yeteneklerine sahip ilk seri \u00fcretim ara\u00e7 olacak. Ara\u00e7lar\u0131n ABD\u2019de 2026\u2019n\u0131n ilk \u00e7eyre\u011finde, Avrupa\u2019da ikinci \u00e7eyrekte, Asya\u2019da ise y\u0131l\u0131n ilerleyen d\u00f6nemlerinde<\/strong> sat\u0131\u015fa sunulmas\u0131 planlan\u0131yor. Sistem resmi olarak SAE Seviye 2++<\/strong> olarak konumland\u0131r\u0131l\u0131yor. Bu, Tesla\u2019n\u0131n FSD\u2019sine benzer \u015fekilde s\u00fcr\u00fcc\u00fcn\u00fcn s\u00fcrekli dikkatini gerektiren bir yap\u0131 anlam\u0131na geliyor.<\/p>\n

Yeni CLA\u2019daki otonom s\u00fcr\u00fc\u015f altyap\u0131s\u0131, 10 kamera, 5 radar ve 12 ultrasonik sens\u00f6r<\/strong> olmak \u00fczere toplam 30 sens\u00f6rden olu\u015fan kapsaml\u0131 bir alg\u0131lama paketi \u00fczerine kurulu. Yani LiDAR yok. Bu sistemlerin e\u011fitimi ve sim\u00fclasyonu ise Nvidia\u2019n\u0131n Blackwell\u2019in halefi olan Vera Rubin platformu taraf\u0131ndan destekleniyor. Alt\u0131 \u00e7ipli bu yeni yapay zek\u00e2 platformu, Nvidia\u2019ya g\u00f6re halihaz\u0131rda tam \u00fcretim a\u015famas\u0131na ge\u00e7mi\u015f durumda. Veri merkezi odakl\u0131 olsa da Rubin GPU\u2019lar ve Vera CPU\u2019lar, gelecekte ara\u00e7lara gelecek Alpamayo s\u00fcr\u00fcmlerinin e\u011fitiminde kritik rol oynayacak.<\/p>\n

A\u00e7\u0131k kaynak olarak yay\u0131nland\u0131<\/b><\/p>\n

<\/span> <\/figure>\n<\/p>\n

Alpamayo 1\u2019in temel kodu Hugging Face \u00fczerinden a\u00e7\u0131k kaynak olarak eri\u015fime a\u00e7\u0131lm\u0131\u015f durumda. Bu sayede geli\u015ftiriciler, modeli daha k\u00fc\u00e7\u00fck ve h\u0131zl\u0131 s\u00fcr\u00fcmler h\u00e2line getirerek ara\u00e7 geli\u015ftirme s\u00fcre\u00e7lerine uyarlayabiliyor. Ayn\u0131 zamanda Alpamayo, daha basit s\u00fcr\u00fc\u015f sistemlerinin e\u011fitilmesinde temel model olarak da kullan\u0131labiliyor. Hatta video verilerini otomatik etiketleyen sistemler ve s\u00fcr\u00fc\u015f kararlar\u0131n\u0131 analiz eden de\u011ferlendirme ara\u00e7lar\u0131 gibi ek \u00e7\u00f6z\u00fcmlerin geli\u015ftirilmesine olanak tan\u0131yor.<\/p>\n

Hem ger\u00e7ek hem de sentetik<\/b><\/p>\n

Nvidia, Alpamayo ekosistemini Cosmos <\/strong>ad\u0131 verilen \u00fcretken d\u00fcnya modelleriyle de destekliyor. Cosmos, fiziksel ortamlar\u0131n dijital temsillerini olu\u015fturarak otonom sistemlerin gelecekteki durumlar\u0131 tahmin etmesini ve buna g\u00f6re aksiyon almas\u0131n\u0131 sa\u011fl\u0131yor. Geli\u015ftiriciler, Cosmos arac\u0131l\u0131\u011f\u0131yla sentetik s\u00fcr\u00fc\u015f verileri \u00fcretebiliyor ve bu verileri ger\u00e7ek d\u00fcnya verileriyle birle\u015ftirerek Alpamayo tabanl\u0131 uygulamalar\u0131 e\u011fitip test edebiliyor.<\/p>\n

Buna ek olarak Nvidia, Alpamayo\u2019nun kullan\u0131ma sunulmas\u0131yla birlikte 1.700 saatin \u00fczerinde s\u00fcr\u00fc\u015f verisi i\u00e7eren a\u00e7\u0131k bir veri seti de payla\u015ft\u0131. Farkl\u0131 co\u011frafyalar ve \u00e7evresel ko\u015fullarda toplanan bu veriler, nadir ve karma\u015f\u0131k ger\u00e7ek d\u00fcnya senaryolar\u0131n\u0131 kapsamas\u0131yla dikkat \u00e7ekiyor.<\/p>\n

\u015eirket, otonom s\u00fcr\u00fc\u015f sistemlerinin do\u011frulanmas\u0131 i\u00e7in AlpaSim <\/strong>adl\u0131 a\u00e7\u0131k kaynakl\u0131 bir sim\u00fclasyon platformunu da tan\u0131tt\u0131. GitHub \u00fczerinden eri\u015filebilen AlpaSim, sens\u00f6rlerden trafik ak\u0131\u015f\u0131na kadar ger\u00e7ek d\u00fcnyadaki s\u00fcr\u00fc\u015f ko\u015fullar\u0131n\u0131 dijital ortamda yeniden olu\u015fturarak, geli\u015ftiricilerin sistemlerini risk almadan ve b\u00fcy\u00fck \u00f6l\u00e7ekte test etmesine imkan tan\u0131yor.<\/p>\n

Sekt\u00f6rde dengeleri de\u011fi\u015ftirebilir mi?<\/b><\/p>\n

Alpamayo\u2019nun karar gerek\u00e7elerini \u00fcretebilmesi, reg\u00fclasyon taraf\u0131nda \u00f6nemli bir g\u00fcven unsuru olarak g\u00f6r\u00fcl\u00fcyor. A\u00e7\u0131k kaynak yakla\u015f\u0131m\u0131 ise start-up\u2019lardan geleneksel otomobil \u00fcreticilerine kadar geni\u015f bir ekosistemin Nvidia\u2019n\u0131n CUDA tabanl\u0131 altyap\u0131s\u0131na ba\u011flanmas\u0131n\u0131 sa\u011fl\u0131yor.<\/p>\n

Tesla CEO\u2019su Elon Musk, Alpamayo ile ilgili de\u011ferlendirmesinde, nadir senaryolar\u0131n \u00e7\u00f6z\u00fcm\u00fcn\u00fcn i\u015fin en zor k\u0131sm\u0131 oldu\u011funu kabul ederken bu alandaki rekabetten endi\u015fe duymad\u0131\u011f\u0131n\u0131 ifade etti\u011fini aktard\u0131. Musk, Tesla\u2019n\u0131n de FSD ile zaten ayn\u0131 \u015feyi yapt\u0131\u011f\u0131n\u0131n alt\u0131n\u0131 \u00e7izdi.<\/p>\n\n

https:\/\/www.youtube.com\/embed\/aF9kLMl-W_A<\/span><\/p>\n

Kaynak :\u00a0https:\/\/www.donanimhaber.com\/nvidia-dan-otonom-araclar-icin-yeni-donem-alpamayo-tanitildi–200517<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

CES 2026 sahnesinde Nvidia, otonom s\u00fcr\u00fc\u015f teknolojisine odaklanan Alpamayo adl\u0131 yeni a\u00e7\u0131k kaynakl\u0131 yapay zeka ailesini duyurdu. Alpamayo, yapay zeka modelleri, sim\u00fclasyon ara\u00e7lar\u0131 ve veri setlerinden olu\u015fan kapsaml\u0131 bir ekosistem sunarak otonom …<\/p>\n","protected":false},"author":1,"featured_media":116933,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[6986,256,284,641,639],"class_list":["post-116932","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-teknoloji","tag-alpamayo","tag-arac","tag-nvidia","tag-sistem","tag-veri"],"_links":{"self":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/116932","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/comments?post=116932"}],"version-history":[{"count":1,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/116932\/revisions"}],"predecessor-version":[{"id":116936,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/116932\/revisions\/116936"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/media\/116933"}],"wp:attachment":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/media?parent=116932"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/categories?post=116932"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/tags?post=116932"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}