AI

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Across
  1. 5. (The process of a trained AI model executing its programming to make predictions or decisions on new, unseen data.)
  2. 8. (The initial text input, instruction, or context provided by a user to guide an AI's generated response.)
  3. 9. (A phenomenon where an AI model confidently generates outputs that are factually incorrect or unsupported by its training data.)
  4. 10. (The mathematical representation of data, like words or images, as vectors in a multi-dimensional space to capture semantic meaning.)
  5. 12. (A set of defined rules or step-by-step instructions given to an AI to help it learn, calculate, or solve problems.)
Down
  1. 1. (The internal variables and weights that an AI model adjusts during its training process to fine-tune its performance.)
  2. 2. (An AI system's ability to process, understand, and generate information using multiple types of data, such as text, images, and audio.)
  3. 3. (The simulation of human intelligence processes by machines, especially computer systems.)
  4. 4. (The smallest unit of data, such as a syllable, word, or character, that a language model processes and analyzes.)
  5. 6. (A software application designed to mimic human conversation through text or voice interactions.)
  6. 7. (The process of identifying, analyzing, and removing errors or "bugs" from an AI model's code, data, or training process.)
  7. 11. (Systematic errors or unfair prejudices in an AI's outputs caused by skewed or unrepresentative training data.)