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Quick answer · 4 min
Artificial intelligence refers to machine-based systems that infer from inputs how to produce outputs such as predictions, content, recommendations, or decisions. It is a broad field, not one model or product.
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AI is decades old. Recent attention follows advances in learning methods, computing, data, investment, and systems that can generate useful text, images, audio, and code.
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Machine learning is a branch of AI in which a model’s behavior is fitted from data, examples, or feedback instead of specifying every rule by hand.
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An AI model is a computational structure whose parameters encode patterns fitted during training. Given an input, it produces an estimate, classification, ranking, or generated continuation.
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Generative AI creates text, images, audio, video, code, or other content by producing likely structures learned during training and conditioned by current input.
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During training, a system adjusts model parameters using data, objectives, and feedback. During inference, the trained model receives a new input and produces an output.
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A prompt is text, an image, audio, code, or other input supplied to a generative system. It can state a task, context, constraints, examples, and desired format.
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Context includes the current prompt and may include system instructions, earlier messages, uploaded material, retrieved passages, tool results, metadata, or state supplied to the model.
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Retrieval finds relevant material from a database, document set, search system, or tool and places it in the task context. Grounding means constraining or supporting an output with specified evidence or environment.
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Language models represent and manipulate relationships well enough to answer, translate, and reason in many tasks. That functional success is real.
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Foundation
Generative AI produces likely continuations from patterns in data and the context it receives. That process can create fluent, relevant, genuinely useful output.
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Do not paste passwords, secret keys, private records, confidential work, protected health or financial data, child data, or another person’s information unless the exact use is authorized and protected.
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Deepfakes use AI to create or modify image, audio, or video so someone appears to say or do something. Synthetic media can be deceptive, disclosed, artistic, or assistive.
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AI behavior reflects data selection, labels, objectives, model design, thresholds, deployment, institutions, and feedback. Some measurable disparities can be reduced.
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Write the claim precisely: capability, product version, population, comparison, date, and condition. Then find the original source and inspect method, scope, uncertainty, incentives, and contrary evidence.
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An AI agent is commonly understood as a system that pursues a goal across multiple steps, maintains state, and may choose or use tools to observe or change an environment.
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A chatbot may answer one turn without pursuing a goal or acting. An agent-like system continues across steps, maintains state, and may choose tools or actions.
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An open model may release weights, code, architecture, data information, or documentation so others can inspect, run, modify, or redistribute some parts.
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AI can automate or accelerate parts of work, and some roles may shrink, grow, or change. A job also contains relationships, exceptions, responsibility, physical work, and organizational context.
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Artificial general intelligence usually means AI with broad, adaptable competence across many domains rather than one narrow task. There is no agreed test, threshold, architecture, or timeline.
