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2. Explainable artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Explainable_artificial...

   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.

3. Artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence

   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.

4. OpenAI Codex - Wikipedia

   en.wikipedia.org/wiki/OpenAI_Codex

   OpenAI Codex is an artificial intelligence model that parses natural language and generates code in response. It powers GitHub Copilot, a programming autocompletion tool, and is based on OpenAI's GPT-3 model, fine-tuned for use in programming applications.

5. Ethics of artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Ethics_of_artificial...

   Learn about the ethical challenges and principles of AI, such as machine ethics, robot ethics, algorithmic biases, and existential risks. Explore the topics, applications, and examples of AI ethics from various perspectives and sources.

6. Generative artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Generative_artificial...

   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.

7. Symbolic artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Symbolic_artificial...

   Learn about the history, methods, and applications of symbolic AI, a paradigm of AI research based on high-level symbolic representations and logic. Explore the challenges, successes, and limitations of symbolic AI and its relation to other approaches.