The author, an ML developer, transitioned from a MacBook Pro with an M1 chip to an x86-based laptop running Linux. The decision was driven by the need for native support for NVIDIA CUDA, which remains the standard for most research ML projects and is not supported by Apple Silicon.
Technical limitations in the macOS ecosystem, such as Docker running via virtualization rather than natively, hindered development workflows. Issues included difficulties with network configuration, lack of direct access to hardware interfaces, and the absence of native support for file systems like ext4, which are standard in Linux environments.
The author noted that while Apple Silicon is efficient, it lacks the flexibility of x86 hardware for testing low-level code and specific CPU instructions. Furthermore, the inability to upgrade components like SSDs in MacBooks prompted a search for more versatile hardware that allows for better control over the computing environment.
Modern x86 processors from Intel and AMD have significantly narrowed the battery life gap with Apple Silicon. Under light workloads, many current laptops consume between 5 and 8 watts, providing approximately 7 to 9 hours of operation away from a power source, which the author considers sufficient for most professional needs.
The transition to Linux was facilitated by the use of AI tools, which simplified system configuration, driver installation, and troubleshooting. The author ultimately chose the ASUS ROG Flow Z13 as a replacement, opting for a setup that allows for dual-booting Windows to maintain access to necessary proprietary software.
