Nvidia AI outlook resets after Meta Platforms, Microsoft update plans
Nvidia shares sold off sharply this spring, fueled by increased worry that spending on artificial intelligence infrastructure, such as Nvidia’s semiconductor chips, was peaking.
The argument was that hyperscalers operating massive cloud data centers were overbuilding capacity and double-ordering chips, setting the stage for a demand reckoning that would cause Nvidia’s sales of increasingly faster and pricier graphic processing units, or GPUs, like its latest Blackwell lineup, to swoon.
However, hyperscalers appear comfortable with their spending and are ready to increase it further.
On July 30, Microsoft, along with Meta Platforms, parent of Facebook and Instagram, offered capital expenditure guidance and comments on their AI buildout, reinforcing the idea that Nvidia’s best days aren’t behind it.
Mark Zuckerberg talked about superintelligence and the upcoming Prometheus and Hyperion data centers. Larger data centers suggest even more demand for AI-optimized network infrastructure, including Nvidia’s GPUs.
Why AI chatbots and agentic AI are driving record Nvidia sales
The launch of OpenAI’s ChatGPT in late 2022 was an eye-opener. The large language model’s ability to crunch and parse data more efficiently than traditional search led to it becoming the fastest app to reach one million users, kicking off a firestorm of chatbot research and development.
Recognizing that its long-time dominance in traditional search might be at risk, Google quickly responded with Gemini, a chatbot easily accessible for free on Google’s home page.
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Microsoft poured billions of dollars into a partnership deal with OpenAI to leverage ChatGPT, and eventually integrated its CoPilot AI throughout its popular Office 365 platform.
Meta Platforms launched an open-source chatbot, Llama, and Amazon invested billions of dollars into Anthropic, which rolled out the Claude chatbot.
Eventually, enterprises got in on the act, too, developing their own AI programs to support their businesses’ specific needs.
Banks use agentic AI, or AI agents that can assist or replace traditional workers, to hedge portfolio and loan risks. Manufacturers are using it to improve quality. Retailers are experimenting with AI in supply chains. And health care companies are investigating its use in drug development and treatment.
AI boom creates pick-and-shovel AI economy
The pick-and-shovel sellers of semiconductor chips, memory, and servers have powered all the activity behind the scenes.
Companies such as Super Micro have seen sales of liquid-cooled server racks surge, while memory companies like Micron have rolled out bigger and faster DRAM solutions suited to AI.
However, Nvidia has been the biggest beneficiary by far of the surge in spending to build out and upgrade existing data centers.
Nvidia’s latest Blackwell GPUs can cost $30,000 to $40,000 each, and fully equipped server racks can fetch millions. When coupled with Nvidia’s CUDA software, these GPUs are faster and better suited to crunching massive workloads associated with AI than CPUs traditionally powering servers in data centers.