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The unwinding of the AI trade, triggered by a recent run of disappointing quarterly earnings, has turned into a bloodbath for Big Tech.\u00a0<\/p>\n
What began with Tesla<\/a> and Google<\/a> has now gathered steam with sell-offs spreading across all major cloud computing and semiconductor stocks, led by Intel<\/a>. The chipmaker suspended its dividend on Thursday and pledged to cut 15,000 jobs, leading to today\u2019s 27% drop\u2014its worst for a single day in\u00a0decades<\/a>.<\/p>\n Sentiment worsened after the\u00a0Financial Times<\/em>\u00a0obtained on Friday a recent letter from hedge fund Elliott Management\u00a0reportedly<\/a>\u00a0telling investors that Nvidia<\/a> and the entire megacap tech sector was living in \u201cbubble land\u201d with artificial intelligence \u201coverhyped\u201d.\u00a0<\/p>\n Although Nvidia may have lost more than 20% from its high in June, putting it in\u00a0bear market territory<\/a>, its those losses only wipe out roughly two months of gains. It is still trading well above levels seen during most of May and has more than doubled in price since January, an indication that valuations may have become overextended, as Elliott warned.\u00a0<\/p>\n Nvidia, whose shares traded roughly in line with the 2.7% drop in the Nasdaq<\/a>, declined to comment to\u00a0Fortune\u00a0<\/em>on the report. The asset manager couldn\u2019t be reached.<\/p>\n A darkening economic outlook hasn\u2019t helped Nvidia or its peers in the chip industry either. Belief is mounting that monetary policy is overly restrictive with the overnight interbank lending rate set by the Federal Reserve\u00a0last fixed<\/a>\u00a0at 5.33%, some 230 basis points above the June\u00a0consumer price index<\/a>, which measures the rate of inflation.<\/p>\n Symptomatic of a new trend to sell into strength, chip designer Arm Holdings reported on Wednesday a\u00a039% gain<\/a>\u00a0in quarterly revenue, only to see it lose a quarter of its value this week alone. Growth forecasts had only met analyst expectations\u2014a sign that the market got ahead of itself.<\/p>\n Fundamentally, little has changed for Nvidia. Its AI training and inference chips are still coveted for their unparalleled ability to crunch the terabytes of data needed to power generative AI. In fact they might even be too good. CEO Jensen Huang is struggling to keep up with the pace of demand, prompting tech companies to invest in their own microchips as a kind of Plan B.\u00a0<\/p>\n Elon Musk said last week that Tesla\u2019s voracious demand for Huang\u2019s H100 processors to power its upcoming data center in Austin means the carmaker will\u00a0double down<\/a>\u00a0on its investment in its Dojo chip. Optimized for training neural networks based on video data rather than text, Tesla hopes its proprietary design will solve autonomous driving if Nvidia cannot.\u00a0<\/p>\n Similarly Amazon<\/a> CEO Andy Jassy said he was also funding his own chips.<\/p>\n \u201cWe have a deep partnership with Nvidia,\u201d Jassy told investors on\u00a0Thursday<\/a>. \u201cBut we\u2019ve heard loud and clear from investors that they relish better price performance. It\u2019s why we\u2019ve invested in our own custom silicon in Trainium for training and Inferentia for inference.\u201d<\/p>\n<\/div>\nAmazon and Tesla look to make their own AI training chips<\/h2>\n