Thomas Alsop
Research expert covering the global hardware industry
AI chips - statistics & facts
As a pioneering force in artificial intelligence (AI), Nvidia leads an AI chips revolution that has swept across the technology landscape. The AI chips market, valued at 53.7 billion U.S. dollars in 2023, is set to grow by over 30 percent in 2024, jumping to more than 71 billion U.S. dollars. Advanced semiconductor chips are crucial in our digital lives, powering everything from smartphones and laptops to industrial and automotive applications. Such has been the growth in AI adoption in 2024 that AI chips have become one of the hottest commodities on the market.
Nvidia’s rise to the top
A number of the leading tech firms are involved in the development of AI chips, most notably Nvidia. Nvidia’s chips are being used to train and run various large language models, including the one developed by OpenAI. ChatGPT was trained using thousands of Nvidia graphics processing units (GPUs), linked together in an advanced AI supercomputing data center belonging to Microsoft. By recognizing the trend early, Nvidia is one of the biggest winners of the AI boom. The chipmaker became a member of an exclusive club of tech companies valued at over three trillion U.S. dollars, joining Microsoft and Apple in this feat in June 2024.Beyond Nvidia
The favored chips for AI applications have been GPUs due to their ability to perform millions of mathematical operations in parallel, with AMD and Intel also being notable players in this space in addition to Nvidia. As well as traditional semiconductor firms, larger tech firms like Microsoft, Amazon, and Google are also looking to innovate in the AI chips space. In the case of Google, it has produced the Tensor Processing Unit, or TPU, an application-specific integrated circuit, or ASIC, developed specifically for AI activities. Moving forward, firms that can combine software and infrastructure packages with specialized in-house chips are set to prevail as the custom chip trend continues.AI chip use cases continue to grow
AI technologies and tasks require specialized AI chips that are more powerful, more efficient, and optimized for advanced machine learning algorithms. Image recognition, recommendation engines, natural language processing, and autonomous vehicles are just some of the use cases that these chips support. AI chips will also find their way into an increasing number of consumer devices, such as smartphones, laptops, and wearables. In addition to this, they will also be used in multiple enterprise markets, such as robotics and sensors, fueling even further growth as their use cases extend and deepen.
