AI is the future. I’m sure of that too, because I’ve heard every company in the tech sector tell me it’s true. We need AI. This is the foundation of every future technological innovation.
If you can’t sense the sarcasm, let me explain. AI is everywhere, and that’s no surprise. There are new technology trends every year, but this latest AI explosion feels different. Since the switch and ChatGPT was introduced to the world, there has been an AI frenzy, with some of the biggest and richest companies in the world competing to be at the top of the AI stack.
Unlike the trends we have seen before, AI has been applied to everything. This catapulted Nvidia into a trillion-dollar company with a dedicated AI accelerator. It’s at the heart of Windows now, according to Microsoft, with the new Copilot feature. And you can’t interact with the search box without the AI stepping in to try to help (the jury is still out on whether it actually helps).
Software is one thing, but the biggest clue that AI is a big deal is the hardware, and that’s what I want to focus on here. More and more we are seeing dedicated AI processors in consumer devices. Apple has been doing this for years with its M series processors, and both Intel and AMD are now building AI accelerators with their mobile processors. This seems like such a big deal that Microsoft saw fit to include a dedicated AI processor in its latest flagship Surface Laptop Studio 2.
It’s just a high-level brand. If you turn to companies like Lenovo, Dell, and HP, you can dig into marketing points about speeding up AI tasks with next-generation components thanks to dedicated AI processors. And what tasks can you speed up? Yes, the background is blurred.
Let me step back for a moment. Most of the AI processing is not done on your device. When you use a service like ChatGPT or Bing Chat, you’re leveraging the power of data centers hundreds or thousands of miles away to do the actual computing. Nothing happens to your device. Microsoft’s Copilot, which is an important feature for the Surface Laptop Studio 2 and Windows 11, doesn’t use a dedicated AI processor. It uses the cloud.
On your real device, the only things your AI processor can do right now are Windows Studio Effects: blurred backgrounds, auto-framing features, and features that adjust your eyes to make it look like you’re looking at the camera. That’s why you need a dedicated AI processor. Better background blur.
Big brands promise there will be more uses for these AI accelerators in the future, but we haven’t seen any consumer apps or features that actually take advantage of AI accelerators. All the cool things you can do with AI — image creation, generative AI in Photoshop, and more — all happen in the cloud. You can do it on any PC, no AI accelerator required.
We’re definitely seeing the cart before the horse here. As a tech reporter, it’s easy to be cynical about AI given how consistently it’s talked about, but I believe dedicated AI accelerators will be an important feature for PCs to have in the future. But that happens in the future. Currently, companies like AMD and Intel are trying to sell hardware to customers who don’t need it. When someone who makes a living in technology is confused about how to leverage consumer AI accelerators, you know there’s a problem.
We need applications that can actually use these AI accelerators, and they don’t exist right now. There have been several attempts to build frameworks for developers to build their own AI-powered applications. However, this has been an AI-dominated year, and when the best that companies marketing AI accelerators can come up with is a blurry background, it’s important to ask whether everyone really needs this hardware in their PC. Maybe later, yes, but definitely not now.
You may have noticed that I didn’t include Nvidia in this discussion. The current AI kingpin own working to build custom AI features, combining software and hardware together. On consumer PCs, you not only get Nvidia Broadcast — which has better webcam effects than Windows Studio Effects, as well as AI features for your microphone and speakers — but also Deep Learning Super Sampling (DLSS). From improvements to better anti-aliasing to more realistic ray tracing, Nvidia is using AI accelerators in its graphics cards. You need the hardware to unlock features, not just better background blur.
To date, we haven’t seen the same push from companies building AI accelerators into PC hardware. This isn’t true on mobile devices — you can see Apple’s Neural Engine at work in everything from voice recognition to AR apps on the iPhone — but PCs haven’t been part of that transition.
We’re building the future of AI on PC, but it’s not there yet. For now, you don’t need to buy a new laptop for the AI accelerator. Once we see what this hardware can do, then we can discuss the purpose of this processor.