Thomas Alsop
Research expert covering the global hardware industry
Processors - statistics & facts
In the rapidly evolving landscape of technology, the race to develop the most powerful and efficient processor chips is intense. Central processing units (CPUs), the traditional workhorses of computing, are now sharing the stage with graphics processing units (GPUs) and neural processing units (NPUs). With advanced chips helping to power our digital world, the growing demand for artificial intelligence (AI) and accelerated computing applications has meant that processor designers are now some of the most lucrative businesses in the tech world.
Processors to power AI
One of the most common and well-known processor types is the CPU, responsible for processing and executing instructions in notebooks, desktops, and servers. Intel and AMD are the leading CPU companies globally, a market that Intel has managed to maintain a healthy lead in. Revealed in December 2023, Intel's Core Ultra processors feature AI enhancements with an advanced NPU for AI acceleration. Similarly, AMD’s Zen 5 Ryzen processors, unveiled in June 2024, boast higher performance and efficiency, integrating advanced AI capabilities through the help of an NPU. Both companies are now vying to be the dominant force in supplying chips for next-generation AI PCs, regarded as the new era in computing.GPUs are optimized for training AI and deep learning models
The GPU, or graphics card, is a silicon-based microprocessor that specializes in accelerating the creation and rendering of images, videos, and animations. Leading GPU companies include Intel, Nvidia, and AMD, producing dedicated GPUs that can perform fast calculations while freeing the CPU to perform other tasks. GPUs began as specialized chips, developed to accelerate specific 3D rendering tasks. Today, GPUs have evolved to become more general-purpose processors, working in parallel to other computer components to handle a growing range of applications, including gaming and machine learning tasks. The most notable recent example is the use of GPUs in the training and running of generative AI applications such as ChatGPT.The brains behind many chips
Beyond the traditional semiconductor firms, many other companies rely on the processor architecture technology licensed by Arm Holdings, the British chip designer. The company has positioned itself as a leader in the design of chips for AI, capitalizing on the AI market hype that many semiconductor companies are looking to chip in to. Examples of products using Arm-based processors include Qualcomm Snapdragon chips found in devices from the major Android device manufacturers, as well as the Apple A17 Pro chip found in the iPhone 15 Pro and Pro Max.Efficiency and power to enable future technologies
Processors are the heart of modern computing, driving innovation and performance, especially in AI applications. As technology advances, processors will evolve to deliver greater efficiency and power. Understanding their role in AI is crucial for navigating the digital landscape, ensuring we remain at the forefront of technological progress.
