Title: Is it just traditional ML?<p>Traditional ML would do a lot of feature extraction and engineering -- from a very specific problem space --before throwing the training compute at it. I think there are good pattern detection, prediction, and anomaly detection models that come out of this.<p>What happens if we just scrape all data (say metrics like weather, flights, population stats, gps locations, web pages clicks, deep space network observations, and kindergarten grades) and if it were possible to build a model with enough weights for all this diverse data ...<p>What kind of use case might such a ... Large DATA model ...open up?
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