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The "context window" of a model is most similar to which concept?
A
Long-term memory
B
Short-term working memory
C
Neural embedding space
D
Batch processing unit
Explanation:
The context window in AI models refers to the amount of text or tokens that a model can process and "remember" during a single inference or generation. This is most similar to short-term working memory because:
Short-term working memory in humans is temporary storage that holds a limited amount of information for immediate processing
Similarly, a model's context window temporarily holds recent inputs and outputs during a conversation or task
Both have capacity limitations and are used for immediate processing rather than long-term storage
Information outside the context window is "forgotten" by the model, just like how information fades from short-term memory
Why other options are incorrect:
Long-term memory refers to permanent storage, while context window is temporary
Neural embedding space is about vector representations, not memory capacity
Batch processing unit relates to computational processing, not memory functionality
The context window determines how much contextual information a model can maintain for coherent responses, making it analogous to short-term working memory in cognitive systems.