Artificial Intelligence Vocabulary

2. A model architecture primarily used in NLP that understands context in sequences (e.g., ChatGPT is built on one).
4. The capacity of an AI to act independently or make choices.
6. Vision, AI’s ability to interpret and process visual information from the world.
8. The ability to understand and explain how an AI system makes decisions.
12. Configuration settings used to control the learning process in machine learning models.
13. A set of rules or instructions given to an AI system to help it learn or solve problems.
16. Adversarial Networks, Two neural networks competing against each other to improve the quality of generated data.
18. A training technique for neural networks where the model adjusts weights to reduce error.
19. Simplified rules or strategies used to solve complex problems efficiently.

1. Learning, A type of learning where an agent learns to make decisions by receiving rewards or penalties.
3. A hypothetical point when AI surpasses human intelligence, possibly leading to unpredictable outcomes.
5. Techniques to prevent overfitting in models.
7. When a model produces unfair results due to prejudiced training data.
9. When a model learns training data too well, including noise, and performs poorly on new data.
10. Network, A series of algorithms that mimic the way the human brain processes data.
11. Language Processing, The field of AI that focuses on the interaction between computers and human language.
14. Learning, Reusing a pre-trained model on a new, related task.
15. Descent, An optimization method used to minimize the error in AI models.
17. Moral considerations around how AI is used and its societal impacts.