3 Reasons to Buy Nvidia Stock Like There’s No Tomorrow

Any conversation about artificial intelligence (AI) would, of necessity, include Nvidia (NASDAQ: NVDA). The company pioneered the graphics processing units (GPUs) that underpin many of the world’s most advanced AI models and continues to innovate at a breakneck pace.

At the company’s GPU Technology Conference (GTC), which kicked off on Sunday in San Jose, California, Nvidia unveiled several startling developments on Monday that suggest the AI revolution is only just beginning. What came out of the conference bolsters the argument for investing in this company. Here are three reasons to buy Nvidia stock like there is no tomorrow.

Image source: Getty Images.

1. Nvidia unveiled the next “must-have” AI processor

When ChatGPT burst on the scene in late 2022, the race to adopt generative AI was on. The potential to leverage these next-generation AI models to boost productivity had businesses scrambling to figure out how best to profit from these developments in AI. The processor that enabled these advances was Nvidia’s H100 Tensor Core GPU, which could train large language models (LLMs) up to 30 times faster than its previous generation of AI chips. Now, those processors are so last year.

On Monday, Nvidia unveiled the Blackwell platform “to power a new era of computing.” The Blackwell B200 Tensor Core GPU is the “world’s most powerful chip” for AI, according to CEO Jensen Huang. The processor is packed with 208 billion transistors (up from 80 billion in the H100), delivering five times the performance. The architecture combines two tightly integrated GPUs that act in concert with each other. The Blackwell GPU can scale up to 10 trillion parameters. For context, GPT-3, the LLM behind ChatGPT, had just 175 billion parameters.

Furthermore, the GB200 Grace Blackwell Superchip combines two B200 chips, a Grace CPU, and an NVLink high-speed interconnect, which makes all the parts act in concert. The AI-centric processor offers up to 30 times the performance of its predecessor while reducing energy consumption by up to 25 times.

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