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Explainable artificial intelligence (XAI) is the ability to understand and explain the reasoning behind AI decisions or predictions. XAI aims to improve trust, transparency, and accountability of AI systems, and to overcome the "black box" problem of machine learning.
Learn about artificial intelligence (AI), the field of computer science that develops and studies methods and software that enable machines to perceive and act in their environment. Explore the major goals, techniques, applications, and challenges of AI, as well as its origins and development over time.
Learn about the history, applications, and challenges of generative AI, which is AI capable of creating text, images, videos, or other data using generative models. Explore examples of generative AI systems, such as chatbots, text-to-image models, and transformer networks.
AGI stands for artificial general intelligence, a type of AI that matches or surpasses human capabilities across a wide range of cognitive tasks. Learn about the characteristics, tests, and challenges of AGI, as well as the related concepts of strong AI, weak AI, and AI-complete problems.
OpenAI is an American company that develops artificial intelligence (AI) with the goal of creating "safe and beneficial" general AI. It is known for its language models, text-to-image and text-to-video models, and its partnership with Microsoft.
Learn how AI is used in various fields such as internet and e-commerce, language translation, facial recognition, games, agriculture, and cyber security. Explore the examples, challenges, and benefits of AI applications with Wikipedia.
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