Will AI PC deliver AI to everyone?
The emerging landscape of AI PCs is set to transform how we work with our devices whether PC or laptop. There are both positives and negatives around this new technology and before embarking on an adoption program, it’s important to know the facts.What is an AI PC?
AI PC’s feature a dedicated Neural Processing Unit (NPU) within the System on Chip (SoC) which handles AI applications, experiences and the technology that runs computational power, whether it’s language models, focused tasks, security or privacy. One of its greatest benefits is that it offers low latency and enables greater personalization which meets the growing need for more autonomy.
AI PC is a new variant of edge computing, where computation is done near the data source or near the end user, instead of depending only on the cloud. That mixed approach binds the strength of the cloud for intensive tasks and the speed and privacy advantages of local processing. AI PCs demonstrate this by using local hardware such as GPU’s and NPUs for AI tasks, hence lowering latency, saving bandwidth and improving data security by reducing the amount of sensitive data that is sent to the cloud. The overall effect is a better user experience, supporting a variety of real time analytics and AI development.Analyst assessment
Given that 2024 has been marked by industry commentators as the year of the AI PC, it is interesting to look at the landscape through the lens of analysts. Gartner, for example, predicts that 54.4 million AI PCs will be shipped this year, while IDC states 50 million and Canalys uses a slightly different measure but believes 1 in 5 shipments will be AI PC. Looking ahead to 2025, Gartner estimates that 43% of all AI PC shipments will be AI PC, but both IDC and Canalys forecast that by 2027, the figure will have risen to 60%. This spells a definite market shift in the direction of AI PCs.AI PC chipset progress
AI PC evolution has been dependent on bringing the hardware and processor together to support AI applications at the PC level and an early example of this system on chip approach was on the iPhone with the A11 bionic processor. Now, with the introduction of chiplets like the Intel Ultra Core processor, we have seen a new design of CPU to suit varied purposes. Instead of the traditional block CPU, we now have a tile-based CPU which allows one file to be allocated to the GPU – the compute tile for the processor – and the SoC – which includes the NPU – to support the AI engine. Chip manufacturers are now developing and releasing their solutions allowing AI PCs to become a realistic prospect for users.Importance of combining CPU, GPU and NPU
Modern computing tasks require many different computational capabilities that are best met by the combination of CPU, GPU and NPU. The CPU is the central processing unit, a general purpose processor designed for sequential processing, which runs the operating system and the conventional apps we all like to use on our laptops. The GPU is the graphics processing unit, originally created for graphics rendering. This is equally effective at parallel computations, ideal for the type of matrix and vector operations that are essential for AI and deep learning. The NPU is the neural processing unit, a specialized processor developed specifically for AI tasks.
