“As Moore’s Law slows while computing demand continues to skyrocket, companies may accelerate every workload possible to drive future improvement in performance, TCO, and energy efficiency,” Colette Kress, EVP & CFO of Nvidia, said in the earnings call. “At the same time, companies have started to build the next generation of modern data centers, what we refer to as AI factories, purpose-built to refine raw data and produce valuable intelligence in the era of generative AI.”
AI breaking barriers across verticals
The growth in data center operations during the fourth quarter was attributed to the training and inference of generative AI and large language models, spanning a diverse array of industries, use cases, and regions.
At the earnings call, Nvidia noted that AI is expanding across various sectors and solutions, with the field of large-language models flourishing. Companies like Recursion Pharmaceuticals and Generate:Biomedicines are developing foundation models for biology, indicating AI’s broad adoption in industries including automotive, healthcare, and financial services.
“Almost 80 vehicle manufacturers across global OEMs, new energy vehicles, trucking, robotaxi, and tier 1 suppliers are using NVIDIA’s AI infrastructure to train LLMs and other AI models for automated driving and AI cockpit applications,” Kress said.
Nvidia’s suite of AI solutions — spanning text generation, chatbots, and even protein prediction — empower businesses to develop tailored AI solutions for automating their operations, according to Thomas George, president of Cybermedia Group and CMR.
“Forging strategic alliances with tech titans such as Google, Microsoft, and Amazon have also bolstered Nvidia’s standing as a frontrunner in AI technology,” George added. “The ubiquitous integration of Nvidia’s GPUs, exemplified by groundbreaking initiatives like ChatGPT, has driven growth in the company’s AI revenue streams and enriched its business portfolio with diversified offerings.”
