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AI Hallucination Quiz

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Questions and Answers

How is AI hallucination different from human hallucination?

AI hallucination is always accurate, while human hallucination is not

AI hallucination always contains random falsehoods, while human hallucination does not

AI hallucination is associated with unjustified responses or beliefs, while human hallucination is associated with false percepts (correct)

AI hallucination is always associated with false percepts, while human hallucination is not

What is an AI hallucination?

A response generated by an AI which is always justified

A response generated by an AI which always aligns with human psychology

A response generated by an AI containing false or misleading information presented as fact (correct)

A response generated by an AI containing only true information

When did AI hallucination gain prominence?

After the decline of chatbots based on large language models (LLMs)

Before the development of large language models (LLMs)

During the early days of artificial intelligence research

During the AI spring, alongside the rollout of widely used chatbots based on large language models (LLMs) (correct)

What was a common complaint about chatbots based on large language models (LLMs)?

<p>They often seemed to pointlessly embed plausible-sounding random falsehoods within their generated content</p> Signup and view all the answers

What percentage of the time were chatbots estimated to hallucinate?

<p>27%</p> Signup and view all the answers

Study Notes

AI Hallucination vs Human Hallucination

AI hallucination refers to the generation of false or inaccurate information by artificial intelligence systems, whereas human hallucination involves perceiving or sensing things that are not present in the environment.

AI Hallucination

AI hallucination occurs when AI systems, such as chatbots or language models, provide information that is not based on any evidence or training data.

History of AI Hallucination

AI hallucination gained prominence with the development of large language models (LLMs) and their increased use in chatbots and other applications.

Limitations of Chatbots

A common complaint about chatbots based on LLMs is that they often provide inaccurate or irrelevant information.
It is estimated that chatbots hallucinate around 10-30% of the time, depending on the context and quality of the model.

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Description

Test your knowledge of AI hallucinations and how they can generate false or misleading information. Explore the concept of confabulation and its potential impact on AI responses and outputs.