GPU Prowess
Nvidia has been a frontrunner in the AI race as it looks to leverage the widespread adoption of generative AI. The company is a market leader in graphic processing units (GPU), the high-performance chips used primarily in gaming systems until recently. Now, GPUs are in the spotlight for another reason – they power the most advanced data centers and artificial intelligence systems.
The company recently launched the next-generation Grace Hopper super chip — the first chip to feature the latest HBM3e memory — as it works to significantly expand its presence in the server market. At the same time, some of the top cloud service providers are deploying Nvidia’s DGX H100 AI infrastructure.
Record Results
In the second quarter of 2024, revenues more than doubled to $13.5 billion, far exceeding the market’s projections and reflecting strong growth in the core Data Center division. A 22% increase in the Gaming segment also contributed to the top-line growth. That translated into a multi-fold growth in adjusted earnings to $2.70 per share, which also came in above estimates. The company has an exceptionally good track record of delivering better-than-expected quarterly profit.
From Nvidia’s Q2 2024 earnings call:
“Going forward, the best way to invest in a data center is to divert the capital investment from general purpose computing and focus it on generative AI and accelerated computing. Generative AI provides a new way of generating productivity, a new way of generating new services to offer to your customers, and accelerated computing helps you save money and save power. And the number of applications is, well tons, lots of developers, lots of applications, lots of libraries.”
Road Ahead
The tech firm is probably headed for an even bigger quarter in terms of sales and profitability – the management expects third-quarter revenues to rise to a record high of $16 billion and sees a gross margin of about 71.5%.
Nvidia and Google have joined hands to power the Google Cloud platform with the former’s advanced GPUs to enhance all AI applications. The move is aimed at meeting the surge in computing requirements for training and inference, driven by the widespread adoption of generative AI and large language models.
NVDA closed the last session notably higher and the uptrend continued in the after-hours. The stock was trading up 1% on Wednesday morning, after gaining 10% since mid-August. The current price is sharply higher than the long-term average.