Although Nvidia’s recently released fiscal fourth-quarter operating results and fiscal 2027 guidance demonstrate why it’s the cream of the crop in the artificial intelligence<\/a> arena, its highly anticipated operating results also resulted in a $630 billion warning that reverberated throughout Wall Street.<\/p>\n Image source: Getty Images.<\/p>\n Nvidia once again shows why it’s the backbone of the AI revolution<\/p>\n Shortly after regular trading hours ended on Feb. 25, Nvidia unveiled another gem of a quarter (its fiscal year ended on Jan. 25, 2026). It delivered record quarterly sales ($68.1 billion), is pacing nearly $250 billion in annual run rate revenue from its Data Center segment, and generated a generally accepted accounting principles (GAAP<\/a>) gross margin of 75% for the quarter. <\/p>\n Tracking close to a quarter-trillion in Data Center sales affirms that Nvidia’s graphics processing units (GPUs) remain the clear top choice<\/a> in AI-accelerated data centers. External competitors, such as Advanced Micro Devices, are playing catch-up and haven’t come particularly close to rivaling the compute capabilities of Nvidia’s Hopper, Blackwell, and Blackwell Ultra chips.<\/p>\n What’s arguably even more important than Nvidia’s breakneck sales growth is the bounce-back that’s been observed in its GAAP gross margin.<\/p>\n NVDA Gross Profit Margin (Quarterly)<\/a> data by YCharts<\/a>.<\/p>\n CEO Jensen Huang is overseeing the aggressive rollout of a new GPU annually, and is counting on increasingly efficient chips to maintain its pricing premium. The company guiding for a GAAP gross margin of 74.9% (+\/- 50 basis points) for the fiscal first quarter of 2027 suggests this premium is intact.<\/p>\n Additionally, the CUDA software platform is flying under the radar<\/a> as a critical cog responsible for Nvidia’s overwhelming success. CUDA is the toolkit developers use when maximizing the compute capabilities of their Nvidia hardware, including the building and training of large language models. Not only is CUDA keeping buyers loyal to Nvidia’s ecosystem of products and services, but it’s extending and expanding the functionality of prior-generation GPUs.<\/p>\n This report shows why Nvidia is the AI infrastructure company that Wall Street’s most influential companies want to partner with.<\/p>\n Image source: Nvidia.<\/p>\n Nvidia’s $630 billion warning for Wall Street shouldn’t be swept under the rug<\/p>\n Nvidia crushing the consensus quarterly revenue and profit forecast of Wall Street analysts has become nearly as certain as the sun rising in the East. Nevertheless, the subsequent trading activity in Nvidia stock following its earnings release tells a different story<\/a>.<\/p>\n Mere minutes after Nvidia unveiled another blowout quarter, its shares touched $203.10 in after-hours trading. Just shy of 48 hours later, when the closing bell tolled on Feb. 27, Nvidia shares were at $177.19. This after-hours peak on Feb. 25 to closing price on Feb. 27 represents a $630 billion loss in market value.<\/p>\n More importantly, it appears to signal what I’ve been cautioning about for some time: investors’ AI expectations are simply too lofty to be met<\/a>.<\/p>\n Three decades ago, the advent and proliferation of the internet began changing the growth trajectory of corporate America forever. Although this technology was adopted with open arms, it would take more than half a decade before businesses understood how to optimize it to boost sales and profits. The dot-com bubble, which saw the S&P 500 and Nasdaq Composite lose 49% and 78% of their value, respectively, came about because investors grossly overestimated how quickly companies would optimize the internet.<\/p>\n Today’s Change<\/p>\n (1.13%) $2.07<\/p>\n Current Price<\/p>\n $184.71<\/p>\n Key Data Points<\/p>\n Market Cap<\/p>\n $4.5T<\/p>\n Day’s Range<\/p>\n $182.01 – $186.42<\/p>\n 52wk Range<\/p>\n $86.62 – $212.19<\/p>\n Volume<\/p>\n 12K<\/p>\n Avg Vol<\/p>\n 177M<\/p>\n Gross Margin<\/p>\n 71.07%<\/p>\n Dividend Yield<\/p>\n 0.02%<\/p>\n The argument can be made that we’re witnessing these same miscalculations today with the AI revolution. Nvidia’s operating results very clearly show there’s no issue with AI adoption. However, businesses aren’t particularly close to optimizing AI solutions — and likely won’t be for many years to come. This implies that no earnings beat will be sufficient to satisfy the lofty expectations of investors.<\/p>\n It’s also unlikely that Nvidia will be able to sustain a virtual monopoly of GPUs in AI-accelerated data centers. While it’s true the company has no clear competitors in terms of GPU compute capabilities, Nvidia is still at risk of losing valuable data center real estate<\/a>.<\/p>\n For example, some of its leading end users by net sales (i.e., select members of the “Magnificent Seven<\/a>“) are internally developing GPUs and AI solutions for their data centers. While internally developed hardware takes a clear backseat on the compute front, it’s notably cheaper and not backlogged. From a cost-efficiency standpoint, internally developed chips may end up occupying space that Nvidia had hoped to secure.<\/p>\n Lastly, Nvidia’s valuation may be giving investors reason to be skeptical<\/a>. While Nvidia’s forward price-to-earnings (P\/E) ratio appears downright cheap, its trailing-12-month price-to-sales (P\/S) ratio<\/a> says otherwise. Though its P\/S ratio has dropped to slightly over 20 as its revenue has expanded, this is still historically elevated.<\/p>\n Nvidia’s $630 billion warning makes clear that AI expectations are unrealistic and the probability of an AI bubble-bursting event is higher than investors realize.<\/p>\n","protected":false},"excerpt":{"rendered":"No trend has been more responsible for powering the Dow Jones Industrial Average, S&P 500, and Nasdaq Composite…\n","protected":false},"author":2,"featured_media":333377,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[345,343,344,85,46,125],"class_list":{"0":"post-333376","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-il","12":"tag-israel","13":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/333376","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=333376"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/333376\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/333377"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=333376"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=333376"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=333376"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"A](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2026\/03\/1773227529_520_.jpeg\"\/)
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<\/a><\/p>\n![\"The](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2026\/03\/1773227530_579_.jpeg\"\/)
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