What is Machine Learning?

Machine learning is perhaps the principal technology behind two emerging domains: data science and artificial intelligence. The rise of machine learning is coming about through the availability of data and computation, but machine learning methdologies are fundamentally dependent on models. The emergence of machine learning is closely tied to the emergence of widely available data. Large amounts of data and high interconnection bandwidth mean that we receive much of our information about the world around us through computers. Economists try to measure productivity, one of the ways we can become more productive is by becoming more efficient. For example, moving from gathering food to settled agriculture. In the modern era one approach to becoming more efficient is automation of processes like manufacturing production lines. The manufacturing process is decomposed into a series of mechanical or manual processes each of which is applied sequentially. Manufacturing processes consist of production lines and robotic automation. Logistics can also be decomposed into the supply chain processes. Whether it's manufacturing or logistics, efficiency can be improved by automating components of the processes to improve the flow of goods. An interesting challenge for modern society is the management of both the flow of goods and the flow of information. The flow of information is also highly automated. Processing of data is decomposed into stages in computer code. In these processing pipelines, manufacturing, logistics or data management, the overall pipeline normally also requires human intervention from an operator. These interventions can create bottlenecks and slow the process of automation. Machine learning is the key technology in automating these manual stages. The human interventions that were easy to replicate with technology have already been replaced. The components that still require human intervention are the knottier problems. Often they represent components that are difficult, or impossible, to decompose into stages which could then be further automated. In that sense these components are process-atoms. In manufacturing or logistics settings these atoms involve the sort of flexible manual skills that we cannot replicate with current robotic technology.