What is AI? Can you make a clear distinction between AI and non-AI systems?

The definition of artificial intelligence (AI) is elusive, and there is no clear red line but a continuum of features characterising what we think of as AI. OECD countries have reached a consensus on a definition of an “AI System,” a machine-based system that infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.

Different AI systems vary in their levels of autonomy and adaptiveness after deployment. The definition encompasses techniques such as machine learning and knowledge-based approaches and application areas such as computer vision, natural language processing, speech recognition, intelligent decision support systems, and intelligent robotic systems. Input is used both during development and after deployment, and input can take the form of knowledge, rules, code, or data.

An AI model is a core component of an AI system used to make inferences from inputs to produce outputs and can be developed manually or automatically based on machine and human inputs/data.

Machine learning is a set of techniques that allows machines to improve their performance and usually generate models in an automated manner through exposure to training data, which can help identify patterns and regularities rather than through explicit instructions from a human.

Source: OECD.ai






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