Learn about the term ‘corpus’ used by AI researchers when training debater AI systems. Expand your knowledge for the IBM Artificial Intelligence Fundamentals certification exam.
Table of Contents
Question
What term do AI researchers use to describe the collection of text and data they use to train a debater AI system?
A. Corpus
B. Collation
C. Library
D. Compilation
Answer
A. Corpus
Explanation
AI researchers call it a corpus. It’s a collection of learned materials, such as text from newspapers, books, and journals, to train a debater AI system.
In the field of artificial intelligence, particularly in natural language processing (NLP), the term “corpus” (plural: corpora) refers to a large and structured collection of text and data used for training AI systems, such as debater AI. A corpus is a carefully curated set of written or spoken material that serves as a representative sample of a specific language, domain, or topic.
AI researchers use corpora to train and test their AI models, enabling them to understand and generate human-like text, engage in debates, and perform various language-related tasks. The corpus provides the AI system with a wealth of information, including vocabulary, grammar, syntax, and semantic relationships, which the model can learn from and use to generate coherent and contextually relevant responses.
The other options mentioned in the question are not typically used in the context of AI training:
- Collation: The act of comparing, analyzing, and organizing textual information or data.
- Library: A collection of resources, such as books, journals, or software, that can be accessed for research or reference purposes.
- Compilation: The process of converting source code into executable code in computer programming.
In summary, AI researchers use the term “corpus” to describe the collection of text and data they use to train debater AI systems and other language-based AI models.
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