The idea is to avoid people assigning bias: I.E. If something is said to be Mk 1 and Mk 2 people are likely to desire the Mk 2 despite having no practical basis for that.
The whole point of refreshing the hardware fleet from Mk 1 to Mk 2 is that it has a practical basis that they will benefit from.
> Big Basin can train models that are 30 percent larger because of the availability of greater arithmetic throughput and a memory size increase from 12 GB to 16 GB. In tests with popular image classification models like ResNet-50, we were able to reach almost 100 percent improvement in throughput compared with Big Sur
Mk 2 is better than the Mk 1 in several important ways. They're not creating Mk 2 for no reason!
> Big Basin can train models that are 30 percent larger because of the availability of greater arithmetic throughput and a memory size increase from 12 GB to 16 GB. In tests with popular image classification models like ResNet-50, we were able to reach almost 100 percent improvement in throughput compared with Big Sur
Mk 2 is better than the Mk 1 in several important ways. They're not creating Mk 2 for no reason!