Iterative (adj.), Doing something again and again, usually to improve it. In the video, this describes the "iterative approach" of reinforcement learning where the program repeats steps to find the best result., Inherent (adj.), Existing as a natural or basic part of something. (e.g., "None of these techniques are inherently smarter than any other."), Paradigm (n.), A typical example or pattern of something; a model. (In the context of the different learning "paradigms" like supervised vs. unsupervised.), Parameter (n.), A limit or rule that controls how something should be done. In AI, computer scientists adjust parameters to improve accuracy., Simulate (v.), To create a model of a real situation or process, often to test outcomes without doing it in real life., Enigmatic (adj.), Mysterious and difficult to understand. The video refers to the "enigmatic decisions" AI makes when its reasoning isn't clear to humans., Diagnostic (adj.), Used to help identify a disease or medical condition. (e.g., "features of diagnostic significance."), Incorporate (v.), To include something as part of a larger group or system., Intervention (n.), Action taken to improve a situation or change the outcome. The video mentions some AI methods require less "human intervention.", Analyze (v.), To examine something in detail, typically in order to explain and interpret it., Implement (v.), To start using a plan, system, or strategy., Optimal (adj.), Best or most favorable. In the video, reinforcement learning helps create an "optimal treatment plan.", Array (n.), An impressive display or range of a particular type of thing. (e.g., "a unique array of rules and strategies."), Transparent (adj.), In this context, easy to perceive or detect; clear and easy to understand (referring to "making machine learning more transparent")..

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