In the earnings season that is now wrapping up, technology companies delivered a clear message regarding artificial intelligence (AI) spending. The five hyperscalers — Microsoft, Amazon, Alphabet, Meta Platforms, and Oracle — all either reaffirmed or boosted their capital expenditure plans for the year, pushing their combined planned outlay north of $700 billion.
The scope of that infrastructure spending is being driven by two interlocking forces: Insatiable demand for additional compute capacity as AI training and inference workloads explode, and a sharp rise in memory component prices that has made every new data center rack more expensive.
Missed Nvidia in 2009? This Rare Signal Is Flashing Again. In 2009, a “Double Down” signal flashed for a little-known chipmaker called Nvidia. For the first time in years, that same “Total Conviction” signal is flashing for a company 1/100th the size of Nvidia. Continue »
While most investors will be watching Nvidia‘s (NASDAQ: NVDA) fiscal 2027 second-quarter earnings report on Aug. 26, I’ll have my eyes on Micron Technology (NASDAQ: MU).
What is Wall Street expecting for Nvidia’s Q2 earnings?
Wall Street analysts expect Nvidia to post roughly $92.1 billion in revenue and earnings per share (EPS) of $2.09 for the second quarter. That would amount to 97% revenue growth and nearly a doubling of profits year over year.
I see several factors that make a considerable earnings beat plausible. First, research analyst Vivek Arya from Bank of America notes that the four major cloud infrastructure platforms — Azure, AWS, Google Cloud, and Oracle Cloud — boast a combined backlog of $2.3 trillion. It’s no secret that the hyperscalers remain capacity-constrained. Given this ongoing compute bottleneck, it’s highly likely that demand for Nvidia’s latest GPU and CPU platforms will remain robust. Moreover, Nvidia’s management previously guided for gross margins to hold near 75%, underscoring the company’s ability to maintain its pricing power.
How Nvidia’s momentum flows directly to Micron
The impact of a strong performance from Nvidia shouldn’t stop at that company’s own stock price. Micron occupies a strategic position in the same AI chip supply chain. Nvidia’s accelerators incorporate high bandwidth memory (HBM) stacks, and Micron is one of only three manufacturers qualified to supply Nvidia with these platforms. Micron’s South Korean rivals, SK Hynix and Samsung, are the other two major high-end memory producers.
This means that every GPU that Nvidia ships requires a corresponding volume of advanced memory products. Because HBM production is increasingly being allocated to customers under multiyear agreements, any confirmation of accelerated GPU demand from Nvidia effectively tightens memory supply even further.
