turbo_wombat
Joined 1 year ago
Joined 1 year ago
Though, past a certain point of complexity, performance aside, assembly might be more readable than BASIC because BASIC relied on line numbers for jumping around, whereas assemblers offered named labels.
Yes, of course the model with custom kernels is faster, whether it's written by a human or an AI.
Generally, PyTorch inference is meant to be used during the training process, and when running metrics, not when deploying. When deployed, you should export to ONNX, and then compile the ONNX to the native format of the device.
If you aren't familiar with the pipeline for ML deployment, this is the equivalent of comparing interpreted code to compiled code.
AMD no longer has a fab. TSMC dominates the global market and basically has no competition.
In the event that Taiwan is invaded, the US would suddenly have a huge problem getting access to any kind of high end chips, be they CPUs or GPUs. This would be a major problem economically and militarily for the US.
Some caveats: Due to the chip act, TSMC does now have fabs Arizona, though I'm not sure what their capacity is. TI, and some others building lower end components also have fabs I believe. For x86, high end ARM, and GPU's, virtually all of that is manufactured by TSMC right now, mostly in Taiwan.
This is simple supply and demand. If you restrict the labor supply, the value of labor increases.
The same thing was observed after the Black Death, which killed off 30 to 50% of Europe's population. There were labor shortages, which increased the bargaining power of labor, and increased wages.
It's really funny US companies suddenly start pretending they don't believe in supply and demand when it comes to labor.