The AI PC market has evolved rapidly since the first generation of AI PCs debuted a few months ago.

Microsoft and Qualcomm’s Snapdragon X Elite spearheaded the second generation. While impressive, these products didn’t cater to three key sectors: workstation-class machines, gaming PCs, and PCs for professional creators. They were adequate for most users but lacked the performance needed by those who create, build, and play the most demanding games or develop AI solutions.

AMD recently announced it would address this gap by introducing a class of PCs with the graphics and processing power that creators demand.

These machines are equipped with discrete graphics cards and the power required for high-performance tasks while still offering the benefits of AI without significantly draining battery life. The only missing piece is desktop PCs, which await support from Microsoft. The issue isn’t hardware but Microsoft’s decision not to support these configurations yet.

Let’s explore AMD’s approach to addressing these market gaps and conclude with a look at my Product of the Week, the Asus ProArt Studiobook 16, which caught my eye at the AMD event.

Whenever a new platform like AI emerges, the initial challenge is a lack of applications.

Microsoft’s AI PC launch targeted users with two new applications: Recall and Cocreator. Microsoft should have initially focused on developers. As Steve Ballmer famously emphasized, “Developers, developers, developers.”

However, Microsoft’s first product was aimed at users, not developers, neglecting workstation-class laptops with GPUs and all desktops. Many professionals prefer desktops for their raw power.

This not only limited the capabilities of those building for AI, but Recall was poorly presented. Although it kept data securely on the local PC — unusual for Microsoft, a leading cloud vendor — it was perceived as a security risk, forcing Microsoft to retract it.

A significant frustration was the lack of a Copilot+ solution for high-performance PCs and workstations, despite high-end discrete GPUs outperforming NPUs. Ironically, Nvidia’s GPU technology powers the generative AI behind OpenAI’s ChatGPT, which Microsoft uses.

AMD Steps In

AMD’s launch addresses this shortfall. Notably, most announced laptops featuring Nvidia graphics cards and an NPU at 50 TOPS bridged the gap left by Microsoft.

These laptops are impressive powerhouses that promise all-day battery life and a weight of around four pounds, making them exceptionally light and long-lasting for their class. Asus showcased the strongest lineup, with many models featuring 16-inch displays and several offering 4K OLED screens with high color accuracy, ideal for gaming, imaging, and performance akin to portable workstations.

It’s a pity AMD didn’t include an NPU in a desktop configuration, which would have set them apart. However, since Microsoft only needs to enable desktop GPUs, AMD’s choice is understandable. Still, this would have created an extremely sustainable setup, as digital assistants need to run almost constantly.

While desktops and workstations don’t need battery life, they consume a lot of power. An NPU instead of a high-performance GPU would offer a low-power alternative.

This strategy is a solid competitive practice, especially in an emerging market. Rather than directly competing with first-to-market rivals, AMD is targeting areas where competitors aren’t yet established and where they have performance disadvantages.

During the event, AMD also announced its acquisition of Silo AI, the largest private AI lab in Europe. Currently, few know how to successfully deploy AI solutions, with most AI projects failing. Silo AI has successfully deployed AI in over 200 accounts and boasts 125 highly skilled AI professionals (PhDs).

This acquisition provides AMD with two critical advantages.

First, it enables them to assist their end-user customers in successfully deploying AI with AMD technology. Second, it gives AMD valuable insights into where current technologies are failing on both servers and desktops, allowing them to better focus their development efforts.

While Nvidia currently leads in AI, being first comes with the risk of making uncorrected mistakes. AMD, although behind, can use insights from Silo AI to avoid these pitfalls. While AMD might not surpass Nvidia, it could become a strong number two in a market that is far from saturated.

Ultimately, AMD’s move will likely accelerate overall AI adoption. A stronger competitor can help sharpen Nvidia’s focus, potentially benefiting both companies.

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