It’s probably not escaped your notice that Artificial Intelligence is undergoing something of a PR push. With the key computing and smartphone players all ramping up their adoption and integration of AI-powered tools on their devices, it’s hard to navigate exactly what the benefits will be in amongst the high levels hype, praise, and peril that have accompanied the tech’s arrival.
First up, the hardware. The Surface series has evolved gradually over the years to form two distinctive product lines. The Surface Laptop is a conventional, handsome machine with a metal casing, thin-edged bezels, and a Snapdragon X Elite processor at its hard. There’s a haptic touchpad for more depth and variety of interaction with the screen, a full HD webcam, and a dedicated Copilot key to the right of the space bar.Available in two screen sizes, 13.
In practice, that Copilot key simply brings up the dialogue box to access the AI, which you can simply treat as a glorified search bar. The company walked back some of the original functionality when it was pointed out that the proposed ‘Recall’ tool, which tracks user activity as a way of building up a profile of likes, dislikes and work patterns, could be a complete gift for hackers.It all comes down to use case.
While a lot of this computation happens in the cloud , Microsoft says the Snapdragon chip’s inbuilt NPU can do some of the AI heavy lifting on the laptop itself. The need for connectivity to drive AI-led creativity is not necessarily a dealbreaker, but it’s an inconvenience – just ask any designer or musician how they feel about cloud-based applications suites and libraries.
All this points to a dystopian future office scenario where AIs are set to aggressively schedule meetings with each other and compete at ruthlessly paring documents down to a handful of bullet points. It’s not a universal panacea, let alone a herald of a golden age of creativity. As a form of smarter search, AI in its current form has some validity, although whether that will ever outweigh the environmental cost of training and maintaining the vast datasets remains to be seen.