One of the eventual applications of new AI/ML intelligence models has to be interfacing with markets and the general study of economics.
When you watch Michael Cafarella talk about this type of analysis, you sort of get a picture of what it's going to be like trying to fine-tune economic systems with new kinds of data, and new sophisticated neural networks. Starting out with some basics in macroeconomics and price index activity, Cafarella introduces what's called the ‘hedonic’ price index. It's basically an index that counts the quality of products into its formulas.
He identifies more criteria for better economic analysis – frequency, for one, and more granular product categorization.He points out that government offices have been assessing quality for some goods for a long time, but not for others. For example, there may be more rudimentary or non-AI analysis of microprocessors, especially given the massive chip shortage for which the current administration authorized $52 billion in domestic production support.