1.
A subset of AI where systems learn patterns from data and improve over time without being explicitly programmed.
2.
A computational model inspired by the human brain, used in deep learning to recognize complex patterns in data.
3.
The dataset used to teach an AI model how to perform a task, such as identifying images or generating text.
4.
The field of AI focused on enabling machines to understand, interpret, and respond to human language.
5.
The use of AI to perform tasks without human intervention, often in repetitive or data-heavy environments.
6.
moral considerations surrounding the development and use of AI, especially regarding fairness, privacy, and accountability.
7.
A term describing AI systems whose internal decision-making processes are not easily understood or explained.
8.
A theoretical form of AI that can perform any intellectual task a human can, as opposed to narrow AI, which is specialized.
