The setback in the AI business, triggered by a series of disappointing quarterly results in the recent past, turned into a bloodbath for the major technology companies.
What began with Tesla And Google has now gained momentum, with sell-offs spreading to all major cloud computing and semiconductor stocks, led by IntelThe chipmaker suspended its dividend on Thursday and announced 15,000 job cuts, leading to today’s 27% drop – the worst in a single day since Decades.
The mood worsened after the Financial Times received a recent letter from the hedge fund Elliott Management on Friday According to reports to inform investors that NVIDIA and the entire megacap technology sector lived in a “bubble situation” in which artificial intelligence was “overvalued.”
Although Nvidia may have lost more than 20% since its June high, Bear market territorythose losses only wipe out about two months of gains. The stock is still well above the levels seen throughout most of May and has more than doubled since January, suggesting valuations may be stretched, as Elliott warned.
Nvidia, whose shares traded roughly in line with the 2.7% decline, Nasdaqdeclined to comment Assets to the report. The asset manager was not available.
The worsening economic outlook hasn’t helped Nvidia and its competitors in the chip industry either, with a growing belief that monetary policy is too restrictive, with the interbank interest rate set overnight by the Federal Reserve. last fixed at 5.33%, around 230 basis points above June Consumer Price Indexwhich measures the inflation rate.
Amazon and Tesla want to produce their own AI training chips
Symptomatic of a new trend of selling in times of strength, chipmaker Arm Holdings reported on Wednesday a 39% profit in quarterly sales, only to lose a quarter of its value this week alone. Growth forecasts had only met analysts’ expectations – a sign that the market has overtaken itself.
Essentially, little has changed for Nvidia. Its AI training and inference chips are still in demand because they are unmatched at processing the terabytes of data required for generative AI. In fact, they might be too good. CEO Jensen Huang is struggling to keep up with demand, prompting tech companies to invest in their own microchips as a kind of Plan B.
Elon Musk said last week that Tesla’s insatiable demand for Huang’s H100 processors for its future data center in Austin means the automaker Double about 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 when Nvidia can’t.
Similar Amazon CEO Andy Jassy said he is also funding his own chips.
“We have a close partnership with Nvidia,” Jassy told investors on Thursday“But we heard loud and clear from investors that they value better value for money. That’s why we invested in our own custom silicon chips: Trainium for training and Inferentia for inference.”