cpbotha, 5 months ago

Charl's log, Earth date Thursday 2023-12-14:

• Trying to live the single-(usbc)-cable-dream at work as well by going through my old thinkpad dock: mac to dock via usbc, dock to Delly U2713HM DisplayPort. However, DP to DP connection from dock to old Dell U2713HM display only sometimes flickers on and often not. usbc to DP from dock is solid. DP-DP cable is extremely sus. Work has ordered new DP-DP cable and I'm crossing my fingers. Singel cable life is fun.
• Again discovered how unbelievably badly macOS renders fonts on resolutions that Apple believes to be too low, in this case my Dell Ultrasharp 27" at 2560x1440 aka QHD at work. Microsoft and Windows do an absolutely great job on exactly the same hardware, and fonts look great.
• BTW, although macOS does marginally better on my 32" 4K Dell IPS display at home, here Windows even further increases its font rendering dominance with fractional scaling and cleartype.
• As is often the case with Apple, there is a (paid) third-party software tool that works around their attempts to improve matters, namely BetterDisplay: https://github.com/waydabber/BetterDisplay
• As I wrote in my notes some years ago when this became apparent, this is just the company's philosophy. They want to control all the hardware. They will begrudgingly let you use some third party displays, but they pick their battles to look good. In this case, it does feel quite user-hostile.
• Ran into a M1-specific bug in the ruff vscode extension, where the arm64 extension build bundles the x86_64 ruff binary. Worked-around, and then reported at https://github.com/astral-sh/ruff-vscode/issues/364
• Finally got around to write the quickstart for org-roam-similarity. Enthusiasts will hopefully be able to get it going! https://github.com/cpbotha/org-roam-similarity
• I've been looking at Apple's MLX machine learning / array framework for Apple Silicon https://github.com/ml-explore/mlx as well as at CoreML because I'm curious whether this will give me faster Jina AI embeddings inference on the M1 than I'm currently getting with the PyTorch MPS backend, which is muuuuuch slower on this M1 Pro 10C / 16C GPU / 16C neural than PyTorch CUDA on my oooold GeForce RTX2070 with 8GB.

#lifelog #apple #usbc #pytorch #orgroam