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A series of mathematical operations and rules used to solve a problem or analyze a set of data. It's like a flowchart, with step-by-step instructions for the questions to ask, but it's written in math and programming code.

An artificial intelligence technology that uses mathematical algorithms to create predictive models. An algorithm is used to analyze data fields and "learn" from that data using the patterns within them to create the models. These models are then used to make predictions or informed decisions about the new data.

A type of machine learning that can determine whether or not its predictions are accurate. It also uses algorithms to analyze data, but it does so on a larger scale than machine learning.

Deep learning will use artificial neural networks, which consist of multiple layers of algorithms. Each layer looks at the incoming data, performs its own specialized analysis, and produces an output that the other layers can understand. This output is then passed to the next layer, where a different algorithm does its own parsing, and so on.

An automated software program designed to perform a specific task. Think of it as a robot without a body. Early robots were relatively simple, handling repetitive and voluminous tasks with relatively straightforward algorithmic logic. An example of this is the web trackers that search engines use to automatically discover and index web content.

It is part of a new, cutting-edge category that goes beyond basic automation. Rather than repeatedly performing a specific task with little or no variation (like robots), autonomous systems bring intelligence to machines so they can adapt to changing environments to achieve a desired goal.

Using artificial intelligence and other technologies to simulate human activity and make decisions, often while interacting directly with humans through text or even speech. Examples include bots that can book dinners, or chatbots

Predictive models are validated against known data, benchmarked against specific performance metrics for specific business scenarios, and then adjusted as needed. This learning and validation process is called bالتدريب. Through periodic retraining, machine learning models are improved over time.