Where will Nvidia shares be in ten years?
Long-term investment is key to sustainable returns in the stock market as it smooths out short-term volatility and brightens the core value of the company. High-tech giant nvidia (NASDAQ: NVDA) I’m on the front line Generated Artificial Intelligence (AI) Growth. But how will Nvidia respond as the hype will inevitably disappear and new opportunities like robotics and self-driving cars could turn in the sun?
NVIDIA is extremely overexposed to the AI hardware market that generates approximately 88% ($30.8 billion) of revenue from the data center segment. This underestimation is a high-tech one, especially as clients continue to lose money on new, low-cost rivals like AI projects and China’s deep seas, causing shareholders to question the industry’s long-term profit potential. They put the giant in a dangerous position.
With the growing popularity of custom chips, major AI clients such as OpenAI can also bypass Nvidia and design their own hardware through partnerships with fab companies. Taiwan Semiconductor Manufacturing.
But generative AI now rules the Nvidia narrative, but it hasn’t always been like this. The company has a history of changing its focus to tackle new trends. In recent years, video games and cryptomining hardware (NVIDIA’s gaming segment) have been around 46% of total sales (12.46 billion) as AI-related growth overshadowed these once important opportunities. It was the dollar).
Nvidia’s rapid business transformation highlights the versatility of its core technology. Graphic Processing Unit (GPU), a type of computer chip that uses parallel processing to perform multiple calculations simultaneously. And over the next decade, investors should expect to continue to find new uses even as demand related to GPU-generated AI slows down. Robotics and self-driving cars look promising.
Autonomous driving could generate revenues of between $300 billion and $400 billion by 2035, according to analysts at McKinsey & Company. Software as a Service (SaaS). And like generative AI, self-driving cars need to process large amounts of data quickly and accurately, making the industry a potential gold mine for NVIDIA and its industry-leading GPUs.
Tesla It’s a good example of the potential scale of opportunities. Despite not offering the well-known Generated AI Leading Language Model (LLM), the automaker is one of Nvidia’s major customers. It builds a Dojo supercomputer designed to accumulate tens of thousands of GPUs and become the brain behind its fully automated driving (FSD) platform.
