All three major US indexes hovered near the flat line Wednesday afternoon, with Alphabet’s impressive earnings fueling optimism for Big Tech despite signs of slowing economic growth.
The S&P 500 and Nasdaq dipped slightly and the Dow was reading about the flat line.
Alphabet’s (+4.2%) cloud growth fueled optimism ahead of Meta (+0.2%), Microsoft (+0.6%) and Amazon’s (+1.4%) results.
However, chipmakers struggled, with AMD dropping over 10% on underwhelming revenue guidance, while Super Micro Computer plunged over 32% following its auditor’s unexpected resignation.
Economic data showed that GDP growth slowed to an annualised 2.8% in Q3, below forecasts, alongside a robust labor market, tempering Fed rate cut hopes and keeping investors on edge as more key earnings reports approach.
We heard from Tesla last week, Alphabet this week, and Meta and Microsoft after the close yesterday. By the end of the day today, we will have heard from Apple and Amazon.
That will be six of the biggest spenders on AI infrastructure. So, what's the state of the technology revolution?
Sundar Pichai (CEO of Alphabet) says it's still the "early days of a what is a powerful new technology."
Nvidia CEO, Jensen Huang, said in May of last year that the transition from general purpose computing to accelerated computing would require a "$1 trillion retooling" of the world's datacenters.
These six companies are on pace to spend about $200 billion this year. Next year they will spend more. And the next year they will spend more.
Wall Street started scrutinising the heavy capex commitment of these companies last quarter. They wanted to see a return on investment. In these earnings calls, of the two biggest hyperscalers (i.e. those providing the AI compute services to external customers) both made it clear that this spending isn't a bet on the future, rather it's fulfilling "real demand."
That "real demand," as Sundar Pichai put it, is revenue derived from "inferencing" not model training.
They aren’t spending tens of billions of dollars to build out computing capacity just to resell it to startups training models that might never become viable businesses.
Instead, the demand is driven by established enterprises implementing AI models to transform their data into business value and efficiencies. This is real generative AI adoption. These tech giants know enterprise demand for inference will only increase, and they know AI model adoption is just beginning to scale globally.
That’s why they’re confident in spending whatever it takes. The prohibitive cost of building this infrastructure further fortifies their market dominance.
At Microsoft, this business is already on a $10 billion revenue run rate—the fastest new business in company history to reach that mark.
As we've discussed over the past year, this is a new industrial revolution and we should expect it to grow the economic and stock market pie. In an era that has already brought us multi-trillion dollar companies, more are coming.
