AI Hallucination Root Cause
AI Hallucinations need to be eliminated if AI is to succeed as a trusted way to deploy commercial solutions.  AI hallucination management can achieve security with filters.  Using independent, continuously operating state machine filters provides secure management of LLM large language model AI output.  AI filters implement multiple independent state control operations inside the AI model to make output responsive to reality.
 
AI uses access to natural language compilations of information to achieve useful computer processing.  AI represents pattern recognition efforts to process mountains of information collected from a variety of sources.  Just as the human brain committed to concrete thinking has difficulty with concrete information processing in a manner that is connected to reality, so also, AI makes hallucinations from time to time.
 
LLM AI tends to depart from reality from time to time producing errors - hallucinations.  Hallucinations are stimulated by processing of concrete content without holding content congruent with reality, without using reason to come to conclusions.
Concrete information, fixed information, one thing at a time sorting for pattern recognition, does not prioritize responsiveness to reality.  With AI being unable to use reality as the foundation for answers to prompts, AI is forced instead to rely on the pattern recognition that has been such a powerful tool.  Before progressing further, before further investment in pattern recognition, we need tools that can shape prompt answers as responsive to reality.
 
The rate of AI hallucination occurrence is sometimes concerning.  The time consumed identifying and eliminating hallucinations developed by AI is also concerning.  This custom  consultation presents a description of a framework that manages a group of continuously operating independent state machines to address AI control.