The AI Chip Race: NVIDIA’s Surging Success and Potential Challenges

Overview of recent AI market movements

Last week, NVIDIA became the third-most valuable company in the U.S., surpassing Amazon and Alphabet. However, its stock had its worst day since October 2023 this week, with shares plunging as much as 8.6%. The market cap dropped from $1.83 trillion on Feb 13th to $1.67 trillion (Quartz news, 2024).

Despite the ups and downs and the rapid evolution in an AI world, AI hardware production has become a highly competitive market. NVIDIA, leading the race in AI chip development, making it one of the most valuable companies with a lot of potential. 

AI technology is advancing rapidly and  a key factor driving this shift is the use of GPUs (Graphics processing units) in AI chips. GPUs, originally designed for tasks like computer graphics and image processing, excel at handling numerous computations per unit of energy consumed.

NVIDIA, a company initially known for gaming GPUs, has become a significant player in AI chips, especially for training Large Language Models (LLMs) in AI neural networks. This raises questions about NVIDIA’s dominance in AI chip production and whether competition among tech giants is just beginning. However, as the landscape evolves, NVIDIA may face challenges such as increasing competition, the need to innovate to maintain its edge, and navigating regulatory and ethical considerations surrounding AI technology.

We are gonna discuss why NVIDIA is leading the AI chips production, whether this competition between tech giants are just starting and what future challenges might NVIDIA face ahead

Three Reasons why NVIDIA is just getting started

  1. Dominance in the GPU market: NVIDIA holds a major market share of 92% in data centre GPUs, compared to AMD’s (Advanced Micro Devices) mere possession of 3% market share based on the data provided by IoT analytics.
  1. Comprehensive ecosystem for developers: NVIDIA is committed to advance the AI ecosystem by investing $30 billion in a unit focused on helping companies create custom AI chips (NVIDIA blog, 2024). One example of NVIDIA’s leadership in the industry is the widespread adoption of CUDA software layer by AI developers.
  2. Heavy investment in competitive advantage: NVIDIA heavily invests in its research and development, dedicating to drive innovation and maintain its position at the forefront of cutting edge technologies.

Three Factors that could pose challenges for NVIDIA

  1. Biggest clients are becoming biggest competitors: NVIDIA’s largest clients, such as Meta, Microsoft, Google and Amazon are also investing heavily in developing their own GPUs. For example, Amazon’s AWS Trainium and Google TPU are posing a direct threat to NVIDIA.
  1. Evolving AI technologies: As AI technology advances, there may be a shift towards smaller, specialised models that require less computing power, rather than larger, general-purpose ones. Moreover, as AI becomes increasingly integrated into smartphones, the demand for certain types of AI hardware could change in the future. 
  1. GPUs price fluctuations: The price of GPUs has risen due to higher demand driven by factors related to Covid-19 and the growing use of AI applications. However, there is a possibility that prices could eventually decrease over the long term, in line with Moore’s Law. 


The recent market movements surrounding NVIDIA underscore the dynamic nature of the AI hardware market. The industry is witnessing a surge in competition and innovation as companies strive to capitalise on the growing demand for AI chips and technologies.

The AI hardware market is poised for continued growth and innovation. Companies that can adapt to the changing landscape and invest in cutting-edge technologies will be well-positioned to capitalise on the opportunities presented by the AI revolution.

AI is undeniably becoming a major trend where all tech giants are eager to dominate and reshape this dynamic landscape that is filled with opportunities and challenges. 

In today’s world that is rapidly changing, understanding AI and its applications is essential. If you are keen to explore the potential of AI technology and its use cases, CFTE has been dedicated to developing the AI in Finance Academy, empowering professionals with the essential skills to thrive in today’s fast-evolving AI in the finance industry.  

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