Nvidia (NVDA) has expanded its offerings in its Gaming platform, providing a boost to its revenues. However, what drove Nvidia’s stock to new highs was its breakthrough in the Data Center segment.
Nvidia converted its Pascal GPUs into general purpose cards that can boost a server’s processing speed and support the deep learning efforts of cloud companies. This helped the company expand its data center offerings to cloud, enterprise, HPC (high-performance computing), and GRID graphics virtualization. The company also launched DGX-1, the world’s first AI supercomputer, which was well-received in the HPC market.
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Nvidia’s (NVDA) Data Center segment’s revenues rose 145% YoY (year-over-year) to $830 million in fiscal 2017. The segment’s revenue growth has accelerated with every passing quarter, growing 63%, 110%, 193%, and 205% YoY in fiscal 1Q17, 2Q17, 3Q17, and 4Q17, respectively. Strong demand in the education, automotive, and energy markets doubled Nvidia’s GRID graphics virtualization revenues.
Overall growth in NVDA’s Data Center segment was driven by the increasing adoption of GPUs by cloud service providers like Microsoft (MSFT), Facebook (FB), and Google (GOOG) for their deep learning initiatives. The next growth spurt would come with the adoption of GPUs by enterprises in the fields of healthcare, transportation, finance, and retail.
Goldman Sachs analyst Toshiya Hari stated that Nvidia is already a leader in deep learning, owning an ~90% share in the deep learning chip market. Intel (INTC) is trying to enter the AI market, but it is behind Nvidia in terms of technology.
Nvidia’s DGX-1 has been well-received by tech companies and governments worldwide, including the following applications:
Nvidia is looking to accelerate its Data Center segment’s growth in fiscal 2018 by rolling out AI software-as-a-service, which is currently in its nascent stage. The company’s DGX-1 AI supercomputer is powering Microsoft’s GPU-accelerated Microsoft Cognitive Toolkit available on the cloud and on site.
Nvidia has also undertaken several initiatives to boost AI adoption. We’ll look into this in the next part.