AI has been the buzzword on everyone's lips for the last few years, ever since generative AI took off with the launch of ChatGPT. Over time, generative AI models have matured and are now much more capable, but a trend we've been noticing lately is local compute. Because data is precious, and no one wants to share it with big corporations to train their models.
Therefore, having powerful hardware to run these models and AI features natively is the need of the hour. Consider Apple Intelligence—it only runs on the iPhone 15 Pro and Mac/iPads with M series chipsets. Similarly, only the Pixel 8 Pro from Google gets the top-end Gemini features. With this context in mind, it's manufacturers like Intel who are bridging the gap in the personal computing space on the other end of the spectrum.
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Think about it—having AI features on smartphones is exciting, but it is still a niche. To reach a wider user base, it is only possible through enterprise-grade use cases. The real benefits of AI will only be realised when a large segment of the working population uses it daily. And this will only happen when capable hardware becomes accessible to them. This is where brands like Intel come in—making competent hardware accessible, and enabling “on-device” AI compute.
It's simple, really. We've grown up hearing about CPUs (central processing units) and GPUs (graphics processing units), but now there's a third component that has recently made its way into chipsets: the NPU, short for Neural Processing Unit. This ensures that machine learning and light AI tasks are handled locally on the system instead of first sending the data to online servers. We have increasingly seen how NPUs can power local features on smartphones. Now, with a renewed focus on PCs, we will gradually see on-device AI features more commonly on AI PCs by brands like Intel.
At the recently concluded Computex in
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