AI traditionally refers to an artificial creation of human-like intelligence (through computer science tools and techniques) that can learn, reason, plan, perceive, or process natural language. It is an internet-enabled technology. Another way of putting it (per Amazon) is “the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem-solving, and pattern recognition.”
These are sequences of instructions developed by programmers to instruct computers in new tasks, including solving problems. Instead of programming the computer every step of the way, the instructions allow the computer to “learn” from the data that have been inputted.
The basic process of machine learning is to give training data to a learning algorithm. This algorithm can generate a new set of rules based on inferences from the data. The more data available to train the algorithm, the more it learns.
This refers to the layered networks that machine learning creates, roughly simulating the neural networks in the human brain.
*Definitions drawn from a Policy Paper from the Internet Society entitled “Artificial Intelligence and Machine Learning (April 18, 2017)
A microapp is a small, modular, reusable AI application that is designed to address a single, recurring business decision (or set of related decisions) for the purpose of optimizing outcomes. In a microapp architecture, the user interacts with functionality that runs inside an application container. Each microapp can function by itself or be combined with other microapps to create a more complex program. When a complex program invokes a microapp, it will carry out its specific task. A2Go definition.