The long -term investment is crucial for sustainable yields on the stock market, as it smooths out short -term volatility and allows the fundamental value of the company to SLA. Technical giant Nvidia (NASDAQ: NVDA) was on the forehead generative artificial intelligence (A) growth. But how does Hype inevitably fade and new opportunities such as robotics and cars that can be driven are potentially occupied in the sun, how will Nvidia react?
With approximately 88% of revenue ($ 30.8 billion) from its data segment, Nvidia is very excessively exposed to the market for generative AI hardware. This insufficient diversification puts a technological giant in a dangerous position, especially since clients continue to lose money on their AI projects and new low rival costs such as a Chinese deep shareholder to question the long -term profit potential in the industry.
The growing popularity of custom chips also allows key AI clients like Openi to bypass Nvidia and designs their own hardware through partnerships with Fab Companies like Taiwanese semiconductor product.
But while the generative AI now dominates Nvidia’s storytelling, it was not always the case. The company has a history of focus switching to deal with emerging trends. Recently, as a fiscal 2022, a video game and a crypto mining hardware (NVIDIA Game segment) represented about 46% of the total sales ($ 12.46 billion) compared to only 9.4% today because growth is associated with AI -om overshadowed these former key options.
The fast business transformation of Nvidia emphasizes the versatility of its fundamental technology, graphic unit for processing (GPU), a type of computer chip that uses parallel processing to perform multiple calculations at the same time. And over the next 10 years, investors should expect GPUs to continue finding a new purpose, even if demand associated with generative AI slows down. Robotics and autonomous vehicles look promising.
According to analysts at McKinsey & Company, autonomous ride could create $ 300 billion up to $ 400 billion in revenue by 2035, because car manufacturers use technology for technology for software as a service (Saas). And just like the generative AI, cars that run independently must quickly and accurately process large amounts of data, which make this industry a potential gold mine for Nvidia and its GPU leading in the industry.
Tesla It is a good example of a potential ladder of possibilities. Despite not offered by the famous generative AI major language model (LLM), the car manufacturer is one of the key customers of NVIDIA. It accumulates tens of thousands of GPU to build its dojo supercompute, which is designed as a brain behind its platform full of self-employment (FSD).
