As someone that is familiar with using nvidia-smi to track util, what are some commands people use to track the SM efficiency? The end of the article had some references, but no examples of what to use explicitly.
At what point is google liable for the increased rate of accidents from features like this? Surely they have some data that can estimate users getting in accidents while using gmaps.
Hey Jeremy, it seems like you could calculate exactly how much a model learns in a single step by calculating the loss for a batch a second time (with no_grad) after the loss is calculated the first time and gradients are updated. This seems like it could produce interesting outputs when graphing the difference of first and second losses at the batch or observation/question level.
I wanted to do this but never figured out where I could get access to the data. I think with setting up the inputs correctly to handle 0-5 heroes chosen per team it could work. Once you have a model you just need to rank remaining heroes by the expected win probability if they are included with the team. If you have a way to get data I would be interested.