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  "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
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      "text": "Artificial intelligence (AI): a broad discipline with the goal of creating intelligent machines, as opposed to the natural intelligence that is demonstrated by humans and animals.\n\nArtificial general intelligence (AGI): a term used to describe future machines that could match and then exceed the full range of human cognitive ability across all economically valuable tasks.\n\nAI Safety: a field that studies and attempts to mitigate the catastrophic risks which future AI could pose to humanity.\n\nMachine learning (ML): a subset of AI that often uses statistical techniques to give machines the ability to \"learn\" from data without being explicitly given the instructions for how to do so. This process is known as \"training\" a \"model\" using a learning \"algorithm\" that progressively improves model performance on a specific task.\n\nReinforcement learning (RL): an area of ML in which software agents learn goal-oriented behavior by trial and error in an environment that provides rewards or penalties in response to their actions (called a \"policy\") towards achieving that goal.\n\nDeep learning (DL): an area of ML that attempts to mimic the activity in layers of neurons in the brain to learn how to recognise complex patterns in data. The \"deep\" refers to the large number of layers of neurons in contemporary models that help to learn rich representations of data to achieve better performance gains.",
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