{"id":389114,"date":"2026-03-17T05:57:07","date_gmt":"2026-03-17T05:57:07","guid":{"rendered":"https:\/\/www.europesays.com\/ie\/389114\/"},"modified":"2026-03-17T05:57:07","modified_gmt":"2026-03-17T05:57:07","slug":"nvidia-ceo-jensen-huang-seemingly-realises-that-google-microsoft-and-meta-are-set-to-eat-the-companys-lunch","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ie\/389114\/","title":{"rendered":"Nvidia CEO Jensen Huang seemingly ‘realises’ that Google, Microsoft and Meta are set to eat the company’s lunch |"},"content":{"rendered":"

\"NvidiaNvidia’s dominance in AI hardware is facing a significant challenge as customers seek cheaper, purpose-built inference chips. Major tech companies like Google, Microsoft, and Meta are developing their own alternatives, directly competing with Nvidia’s established GPU dominance. This shift signals the end of Jensen Huang’s ‘one chip fits all’ era. Jensen Huang built Nvidia into a $4.5 trillion empire on a deceptively simple premise: one chip, every workload, everywhere. For years, it worked spectacularly\u2014CUDA locked in developers, GPUs became the default backbone of the AI boom, and rivals barely registered. Nvidia commanded over 90% of the AI accelerator market, posted 75% gross margins, and watched its stock climb to heights that made it the most valuable company on the planet. But the AI hardware market is shifting in ways that Nvidia can no longer afford to ignore, and Huang’s decision to unveil a brand new inference-focused chip at next week’s GTC developer conference\u2014the first product from December’s $20 billion Groq acquisition\u2014is the clearest signal yet that even he knows the old playbook has limits.The trigger is hard to miss. Customers are quietly shopping elsewhere, billions in market value are evaporating in single sessions, and the companies that once queued up to buy Nvidia’s GPUs are now building serious alternatives of their own. Google<\/a>, Microsoft, Amazon, and Meta have all announced purpose-built AI chips in recent months\u2014each one explicitly benchmarked against Nvidia, and each one pitched as meaningfully cheaper to run at scale. <\/p>\n

Huang’s ‘one chip fits all’ era is quietly coming to an end<\/b><\/p>\n

The core of Nvidia’s dominance has always been CUDA\u2014its proprietary software ecosystem that ties developers to its hardware. But as AI workloads shift increasingly toward inference, the economics are turning against Nvidia. Bank of America analysts estimate inference will account for 75% of AI data center spending by 2030, up from around 50% last year. Purpose-built chips from Google, Microsoft, Amazon, and now Meta are specifically designed for exactly that\u2014and they’re significantly cheaper to run at scale.Google’s Ironwood TPU, for instance, reportedly delivers a total cost of ownership roughly 30-44% lower than Nvidia’s equivalent GB200 Blackwell server. Microsoft’s newly announced Maia 200, built on TSMC’s 3nm process, claims 30% better performance per dollar than its previous generation\u2014and explicitly benchmarks itself as outperforming Nvidia’s seventh-generation TPU on FP8 tasks. Meta, meanwhile, revealed four new in-house MTIA chips this week alone, with a new generation shipping roughly every six months.<\/p>\n

Nvidia lost $250 billion in a single session when Meta’s TPU talks surfaced<\/b><\/p>\n

The market is already pricing in the shift. When reports emerged that Meta\u2014one of Nvidia’s biggest customers, planning up to $72 billion in AI infrastructure spending this year\u2014was exploring Google’s TPUs for its data centers, Nvidia stock dropped over 6% in a single session, erasing around $250 billion in market value. Alphabet climbed 4%. Broadcom, which manufactures Google’s chips, jumped 11%.Nvidia’s public response was unusually defensive. “Nvidia is a generation ahead of the industry\u2014it’s the only platform that runs every AI model and does it everywhere computing is done,” the company posted on X. That’s technically true. But “runs every model” increasingly matters less than “runs the right models cheaply.”<\/p>\n

The new chip landscape increasingly favors purpose-built alternatives<\/b><\/p>\n

The FT notes that Groq’s LPU\u2014now being absorbed into Nvidia’s product line\u2014uses SRAM rather than the expensive high-bandwidth memory that powers Nvidia’s flagship chips. HBM is increasingly in short supply, with SK Hynix and Micron struggling to keep up with demand. A Groq-derived chip sidesteps that bottleneck entirely.<\/p>\n

India\u2019s AI Rise Gets Global Push As UN Chief Praises Leadership, Nvidia CEO Predicts Job Surge<\/p>\n

Still, Nvidia isn’t done. SemiAnalysis maintains that Google, Amazon, and Nvidia will all “sell lots of chips” in the future\u2014the market is growing fast enough for multiple winners. But pricing power, once Nvidia’s greatest strength, is clearly under threat. And Jensen Huang, by finally acknowledging that inference needs its own dedicated hardware, has effectively confirmed what rivals have been arguing for years.<\/p>\n","protected":false},"excerpt":{"rendered":"Nvidia’s dominance in AI hardware is facing a significant challenge as customers seek cheaper, purpose-built inference chips. Major…\n","protected":false},"author":2,"featured_media":389115,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[261],"tags":[291,10509,289,290,18,823,122610,177694,19,17,3573,1722,177692,305,177693,292,82],"class_list":{"0":"post-389114","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-ai-chips","10":"tag-artificial-intelligence","11":"tag-artificialintelligence","12":"tag-eire","13":"tag-google","14":"tag-google-tpus","15":"tag-groq-acquisition","16":"tag-ie","17":"tag-ireland","18":"tag-jensen-huang","19":"tag-meta","20":"tag-meta-ai-infrastructure","21":"tag-microsoft","22":"tag-microsoft-maia-200","23":"tag-nvidia","24":"tag-technology"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@ie\/116242982183176947","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/389114","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/comments?post=389114"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/389114\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/389115"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=389114"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=389114"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=389114"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}