According to ZDNET, Mac computers have evolved from being somewhat overlooked professional machines into key players in the race for artificial intelligence (AI) innovation. The integration of local AI capabilities has made Macs equipped with Apple Silicon processors surprisingly appealing. Apple's processors may even be more influential than its newly launched Apple Intelligence software. In 2018, one user had nearly given up on ever seeing Macs benefit from significant updates. They used Windows and Linux for some projects but relied on Macs for daily tasks. They feared they might have to move everything to other platforms, a process they found unappealing. At the time, the Mac ecosystem lacked the power and flexibility needed for intensive users. It would have been hard to imagine that Mac minis would soon become highly sought-after for high-performance AI tasks. Everything changed with the release of the Apple Silicon M1 processor in 2020. Apple Silicon is a system-on-a-chip (SoC), meaning that all essential components—such as the processor, graphics processor, and memory—are built on a single silicon chip. This design addresses many issues that affect traditional PCs, such as heat management, modularity limitations, and high component costs. However, this shift required some adjustment for experienced users who valued the ability to upgrade memory or replace graphics cards. Despite this, grouping everything on a single chip has made the Mac a powerful platform for AI. Apple Silicon chips integrate multiple processors, each with a specific role. The CPU handles basic computing tasks, while Apple CPUs also include extensions for high-precision mathematical calculations. The GPU is ideal for data-heavy workloads, and most intensive graphics calculations require large-scale array processing. Interestingly, AI also requires similar processing power, which is why GPUs are so in demand. Apple's Neural Engine is a specialized chip designed to handle AI tasks efficiently, using minimal power for functions like voice recognition or image classification. Users can run complex AI workloads on the first M1 Apple Silicon Macs from 2020. One user's four-year-old Mac Studio M1 currently handles important AI tasks in their personal lab, or a brand new 32 GB Mac mini M6 can be purchased for just over 2000 euros. As these devices become more powerful, running AI workloads locally offers additional benefits, such as avoiding concerns about data privacy or extra costs for using AI services. Sixteen months ago, the user upgraded their 64 GB Mac Studio M1 Max to a 128 GB Mac Studio M4 Max, which is now their everyday computer. Last month, Apple introduced the M5 Max and M5 Ultra chips for the Mac mini and Mac Studio. However, their older Mac Studio still performs so well that they see no need to upgrade it. If someone had predicted in 2018 that Apple would offer small, powerful Macs that remain relevant without frequent upgrades, they might have found it hard to believe. Apple has significantly increased the pace of updates for its screenless Mac models, nearly matching the speed of iPhone updates. This is largely due to the fact that Macs and iPhones both use Apple's internally developed processor technology. Apple has greater control over its own architecture, making updates more practical and easier to implement. The growing demand for AI has also played a role. The user does not believe Apple could have predicted the AI boom as early as 2020. However, the company designed a high-performance processor tailored for tasks related to graphics, which happen to align well with many AI requirements. This places Apple's new proprietary architecture in a strong position, far ahead of the Intel-based systems it previously used. It is ironic that Apple Intelligence has been a disappointment, but the company's processors, originally designed for different tasks, are nearly perfect for AI. Apple's hardware has made a strong impact in the AI world, while its AI software has had little effect on users' projects—but the user does not mind.