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Huang’\u0131n istifas\u0131, yakla\u015f\u0131k 4 trilyon dolarl\u0131k piyasa de\u011ferine sahip Nvidia a\u00e7\u0131s\u0131ndan kritik bir d\u00f6neme denk geldi.<\/p>\n
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Uzun y\u0131llar boyunca \u00f6zellikle bilgisayar oyuncular\u0131na y\u00f6nelik ekran kartlar\u0131yla tan\u0131nan \u015firket, grafik i\u015flemcilerinin ayn\u0131 anda \u00e7ok say\u0131da hesaplama yapabilme kapasitesi sayesinde yapay zeka sekt\u00f6r\u00fcn\u00fcn en \u00f6nemli donan\u0131m tedarik\u00e7isine d\u00f6n\u00fc\u015ft\u00fc.<\/p>\n
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Nvidia’n\u0131n geli\u015ftirdi\u011fi grafik i\u015flem birimleri (GPU), b\u00fcy\u00fck dil modellerinin e\u011fitilmesinden veri merkezlerinin i\u015fletilmesine kadar pek \u00e7ok alanda kullan\u0131l\u0131yor.<\/p>\n
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Yapay zeka alan\u0131ndaki yat\u0131r\u0131mlar\u0131n h\u0131zla b\u00fcy\u00fcmesi, \u015firketi d\u00fcnyan\u0131n en de\u011ferli kurulu\u015flar\u0131ndan biri haline getirirken Huang’\u0131 da teknoloji sekt\u00f6r\u00fcn\u00fcn en etkili isimleri aras\u0131na ta\u015f\u0131d\u0131.<\/p>\n
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Tayvan ve G\u00fcney Kore gibi \u00fclkelerde hayranlar\u0131n\u0131n yo\u011fun ilgisiyle kar\u015f\u0131la\u015fan Huang, \u015firket etkinliklerinde yapt\u0131\u011f\u0131 a\u00e7\u0131klamalarla teknoloji hisselerinin fiyatlar\u0131n\u0131 etkileyebilen bir y\u00f6neticiye d\u00f6n\u00fc\u015fm\u00fc\u015ft\u00fc.<\/p>\n
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Ancak Huang’\u0131n rol\u00fc yaln\u0131zca Nvidia’n\u0131n teknolojik geli\u015fimine y\u00f6n vermekle s\u0131n\u0131rl\u0131 de\u011fildi.<\/p>\n
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\u015eirket, son y\u0131llarda elde etti\u011fi y\u00fcksek nakit ak\u0131\u015f\u0131n\u0131 bulut bili\u015fim sa\u011flay\u0131c\u0131lar\u0131na, \u00e7ip tedarik\u00e7ilerine ve b\u00fcy\u00fck yapay zeka laboratuvarlar\u0131na yat\u0131r\u0131m yapmak i\u00e7in de kulland\u0131.<\/p>\n
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Bu yat\u0131r\u0131mlar, Nvidia’n\u0131n hem donan\u0131m sa\u011flay\u0131c\u0131s\u0131 hem de sekt\u00f6r\u00fcn finansal destek\u00e7ilerinden biri haline gelmesini sa\u011flad\u0131.<\/p>\n
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ANAL\u0130STLER: ASIL R\u0130SK TEKNOLOJ\u0130 DE\u011e\u0130L, Y\u00d6NET\u0130M<\/strong><\/p>\n \u00a0<\/p>\n Yat\u0131r\u0131mc\u0131lar, Huang’\u0131n ayr\u0131lmas\u0131n\u0131n Nvidia’n\u0131n teknoloji geli\u015ftirme takviminden \u00e7ok, \u015firketin karma\u015f\u0131k i\u015f ortakl\u0131klar\u0131n\u0131 y\u00f6netme kapasitesini etkileyebilece\u011finden endi\u015fe ediyor.<\/p>\n \u00a0<\/p>\n ClearBridge Investments portf\u00f6y y\u00f6neticisi Michael Feldman, Nvidia’n\u0131n \u00f6n\u00fcm\u00fczdeki birka\u00e7 y\u0131la ili\u015fkin teknoloji yol haritas\u0131n\u0131n b\u00fcy\u00fck \u00f6l\u00e7\u00fcde belirlenmi\u015f oldu\u011funu s\u00f6yledi.<\/p>\n \u00a0<\/p>\n Feldman’a g\u00f6re as\u0131l risk, bu planlar\u0131n hayata ge\u00e7irilmesi ve farkl\u0131 \u015firketler aras\u0131ndaki koordinasyonun s\u00fcrd\u00fcr\u00fclebilmesinde ortaya \u00e7\u0131k\u0131yor.<\/p>\n \u00a0<\/p>\n Huang’\u0131n son derece karma\u015f\u0131k bir sistemin temel koordinat\u00f6r\u00fc oldu\u011funu belirten Feldman, tedarik ve \u00fcretim darbo\u011fazlar\u0131n\u0131n ya\u015fand\u0131\u011f\u0131 bir sekt\u00f6rde bu koordinasyon becerisinin ba\u015fl\u0131 ba\u015f\u0131na rekabet avantaj\u0131 olu\u015fturdu\u011funu vurgulad\u0131.<\/p>\n \u00a0<\/p>\n \u00d6te yandan teknoloji devlerinin yapay zeka altyap\u0131s\u0131na y\u00f6nelik harcamalar\u0131n\u0131 h\u0131zla art\u0131rmas\u0131 ve bor\u00e7lanman\u0131n y\u00fckselmesi, yat\u0131r\u0131mlar\u0131n ne \u00f6l\u00e7\u00fcde k\u00e2ra d\u00f6n\u00fc\u015fece\u011fine ili\u015fkin tart\u0131\u015fmalar\u0131 da beraberinde getiriyor.<\/p>\n \u00a0<\/p>\n Huang’\u0131n ayr\u0131lmas\u0131, yapay zeka sekt\u00f6r\u00fcne y\u00f6nelik yat\u0131r\u0131mc\u0131 g\u00fcveninin zaten k\u0131r\u0131lgan oldu\u011fu bir d\u00f6nemde yeni bir belirsizlik yaratt\u0131.<\/p>\n<\/div>\n