AI Hallucination

Symptoms:

AI models, including the ones used in AI Cockpit, can occasionally generate information that appears factual but is incorrect or unrelated to the task's context. This is commonly referred to as "hallucination."

Cause:

Hallucinations in AI models occur because they are designed to predict the next most likely word or phrase in a sequence based on patterns learned from their training data. They do not possess a true understanding or awareness of the real world. When the provided context is insufficient or ambiguous, the model may "fill in the gaps" with information that is statistically plausible but factually incorrect.

Recommendations:

The best way to mitigate AI hallucinations is to provide as much context as possible. The more information the model has, the better it can understand the task and generate an accurate and relevant response.

• Be Specific: Provide clear and detailed instructions.
• Provide Examples: If possible, give examples of what you expect.
• Context is Key: Use context mentions, code snippets, and other references to provide rich context.

By providing comprehensive context, you can significantly reduce the likelihood of the AI hallucinating and ensure that the responses you receive are more accurate and helpful.