AI AI AI

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Across
  1. 2. Making predictions without any task-specific training data.
  2. 3. The process of adapting a pre-trained model to a specific task.
  3. 7. Grouping similar data points together without predefined categories.
  4. 12. A measurable property or characteristic of data used in training AI models.
  5. 13. The time delay before an AI system produces a result.
  6. 14. Assigning categories or labels to data using AI models.
  7. 15. Text-to-Speech, converting written text into spoken words using AI.
  8. 17. A mathematical representation of a problem, trained on data to make predictions or decisions.
  9. 19. Splitting text into smaller units like words or subwords for processing.
  10. 20. Assessing the performance of an AI model.
  11. 22. AI systems capable of processing and understanding multiple types of data (e.g., text and images).
  12. 23. A piece of text, such as a word or subword, used in language processing.
  13. 24. Input given to an AI model to generate a response or output.
Down
  1. 1. When a model performs well on training data but poorly on new, unseen data.
  2. 4. A measure used to evaluate the success of a model, like accuracy or precision.
  3. 5. A sequence of steps for processing data or training models in AI workflows.
  4. 6. A numerical representation of words or data for use in AI models.
  5. 8. A type of neural network architecture that powers many LLMs.
  6. 9. A computing system inspired by the human brain, used in deep learning.
  7. 10. Automatic Speech Recognition, converting spoken language into text.
  8. 11. A set of rules or steps used by computers to solve problems or perform tasks.
  9. 16. Reducing words to their base or root form for NLP tasks.
  10. 18. A mechanism in AI models that helps focus on the most relevant parts of input.
  11. 21. A mathematical object used to represent data or features in AI.