Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals, including humans. A system that perceives its environment and takes actions that maximize its chance of achieving its goals.
DDS is a networking middleware that simplifies complex network programming. It implements a publish-subscribe pattern for sending and receiving data, events, and commands among the nodes. Nodes that produce information (publishers) create “topics” (e.g., temperature, location, pressure) and publish “samples.” DDS delivers the samples to subscribers that declare an interest in that topic. DDS handles transfer chores: message addressing, data marshaling and de-marshaling (so subscribers can be on different platforms from the publisher), delivery, flow control, retries, etc. Any node can be a publisher, subscriber, or both simultaneously. The DDS publish-subscribe model virtually eliminates complex network programming for distributed applications. DDS supports mechanisms that go beyond the basic publish-subscribe model. The key benefit is that applications that use DDS for their communications are decoupled. Little design time needs to be spent on handling their mutual interactions. In particular, the applications never need information about the other participating applications, including their existence or locations. DDS transparently handles message delivery without requiring intervention from the user applications
Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.