But, if we want to classify between a male and female photograph, it is not so simple. We know the extremes very well. But, the demarcation is not so clear. Such classification is naturally error prone. In such a case, we have to work on a better training near this hazy line of demarcation — perhaps providing more data that is near that line.
A predictive model is designed to be run again and again so that the relationship identified in the training set can be utilized to make predictions based on new data that is fed into the model. Therefore the data is selected primarily based on how available it will be to run through models in the future. In many modern day contexts this often means predictive models are restricted to only use data that…
… have a more commonsense understanding of the world around them than any AI application ever built. An AI application starts with a blank slate before learning from patterns in the data it analyzes, while b… have a more commonsense understanding of the world around them than any AI application ever built. An AI application starts with a blank slate before learning from patterns in the data it analyzes, while babies start off with a genetic head start and a brain structure that allows them to learn much more than data and patterns.