Think of an AI PC as a supercharged personal computer, tailor-made with the right hardware and software to handle AI and machine learning tasks like a pro. It’s all about giving those number-crunching, data-sifting AI and machine learning tasks the power boost they need.
These tasks cover a wide spectrum of workloads including generative AI programs like Stable Diffusion, clever chatbots powered by local language models, comprehensive data analysis, training of AI models, and running intricate simulations and sophisticated AI-driven applications.
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Along with power processors (CPUs) and graphics cards (GPUs) to give the systems multitasking might, and ample RAM and swift storage options, these PCs boast something new: an NPU, or neural processing unit, designed to turbocharge AI tasks.
Intel and Microsoft have also come together to define what an AI PC is, and in addition to needing a CPU, GPU, and NPU, these PCs will also have a physical Microsoft Copilot key on the keyboard, and be able to run Copilot locally.
And, as we’ll see when we come onto the measure of the power and performance of an NPU, this has performance requirements that right now are hard to meet.
The goal is to create systems that are quicker at executing AI tasks, more energy-efficient, and eliminate the need to send data — especially sensitive data — to cloud-based AI servers for processing. This approach ensures that systems can operate independently of an internet connection, and enhance security by retaining the data locally.