I still very vividly remember the beginning days of ML when it was called "big data". We just need to collect all the data and then the ML can learn and find pa

I still very vividly remember the beginning days of ML when it was called "big data". We just need to collect all the data and then the ML can learn and find patterns "that is improbable for humans to [find] because of the sheer dimensions of connectivity of the graph." Now we are over that point and we are not anymore just collecting anything. We going to reduce the number of the data points in the first place like we have done before "big data" was a thing. Because with edge computing we don't have the resources to do real big data anymore and we have to think what its worth and what to get rid of.