Artificial Intelligence Overview

Artificial Intelligence (AI) is the simulation of human intelligence processes by computers, especially computer systems that are designed to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making.

Machine learning is a type of AI that enables computers to learn from data without being explicitly programmed. It involves training algorithms on large datasets to identify patterns and make predictions.

Artificial General Intelligence (AGI) refers to a hypothetical type of AI that possesses human-level intelligence and can perform any intellectual task a human can.

Narrow AI, also known as Weak AI, is designed to perform a specific task, such as playing chess, recognizing faces, or translating languages. It excels at its designated task but lacks the general intelligence of humans.

Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers to process complex data. It is inspired by the structure and function of the human brain.

Natural Language Processing (NLP) is a branch of AI that focuses on the interaction between computers and human language. It involves understanding, interpreting, and generating human language.

Computer vision enables computers to "see" and interpret images and videos, similar to how humans do. It is used in applications such as face recognition, object detection, and self-driving cars.

Algorithmic bias occurs when an AI system's decisions or predictions reflect and perpetuate existing biases present in the data it was trained on. This can lead to unfair or discriminatory outcomes.

A challenge in AI development where the training data reflects biases present in the real world, leading to unfair or discriminatory outcomes.

The ability of an AI system to perform well on unseen data, not just the data it was trained on.

The use of AI to create new and original art forms like music or visual art.

A branch of AI focused on enabling computers to 'see' and understand images.

A type of software testing that focuses on evaluating the functionality of the software without looking at the internal structure or code.

The purpose of this testing is to make sure that new code changes don't negatively impact the existing functionality of the software.

A software development process that outlines the steps and activities involved in building software, from initial planning to deployment and maintenance.

A document outlining the testing strategy and scope, including the objectives, test cases, resources, and schedule for testing.

A type of software testing that focuses on simulating real-world user scenarios. It involves creating and executing test cases that mimic how users would interact with the software.

A collection of test cases designed to test a specific aspect or feature of the software.

A type of software testing that assesses the software's security vulnerabilities. It involves identifying and exploiting potential weaknesses to ensure the software is secure.

The process of identifying and removing defects or bugs in software. It involves analyzing error reports, debugging code, and fixing the root cause of the issue.

A methodology that emphasizes testing throughout the entire software development process, rather than waiting until the end. It involves continuous integration and continuous delivery (CI/CD), and aims to deliver software quickly and efficiently.

A type of testing that evaluates the software's compliance with industry standards, regulations, and legal requirements. It ensures that the software meets the specific criteria defined by these standards.

A tool that helps manage and track software defects or bugs throughout the development process. It allows developers to track the status of bugs, assign them to specific teams, and monitor their resolution.

A type of performance testing that evaluates the software's ability to handle heavy load or traffic. It simulates real-world conditions to identify performance bottlenecks and ensure the software can handle the expected load.

A set of best practices and frameworks for IT service management.

The network of interconnected devices on the Internet.

A common misconception that DevOps practices only apply to web-based companies.

A software development approach where operations are closely integrated with development.

The practice of merging operations into development, eliminating separate teams.