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PUBLISHER: IDC | PRODUCT CODE: 1457870

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PUBLISHER: IDC | PRODUCT CODE: 1457870

Understanding and Mitigating Large Language Model Hallucinations

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PAGES: 9 Pages
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This IDC Market Perspective analyzes the sources and various mitigation techniques and solutions for large language model (LLM) hallucinations, such as when using GenAI. Hallucinations where the model returns incorrect or misleading results in response to a prompt, and IDC expects that as more businesses adopt GenAI, those businesses will be faced with more and more significant hallucination issues that they are looking to technology vendors to solve. The increasing adoption of LLMs has resulted in an increase in the number of hallucinations that businesses are being forced to deal with that erode trust in the technology and in the responses it provides. Even with the disclaimers, the increasing importance of this technology and the vulnerability it causes for businesses are forcing researchers and technology suppliers to respond. Until we have a viable technology solution, businesses and technology suppliers will have to rely on a combination of sets of solutions for addressing the hallucination issue with model training and behavior, the underlying data and data sets, the engagement point between people and model, and model-specific issues."As almost every business is adopting GenAI and other LLMs, hallucinations are a real problem for businesses that can have significant impacts," said Alan Webber, program vice president, Digital Platform Ecosystems at IDC. "It is critical for technology suppliers to address the hallucination issue if they want and expect to maintain trust with their customers."

Product Code: US51964924

Executive Snapshot

New Market Developments and Dynamics

  • Types of LLM Hallucinations
  • Causes of LLM Hallucinations
    • Model Training Issues
    • Data Issues
  • Ways to Mitigate LLM Hallucinations
    • Model Training and Behavior-Focused Mitigation
    • Data-Focused Mitigation
    • People-Focused Mitigation Efforts
    • Model-Orientated Mitigation Efforts
      • LLM Self-Refinement
      • Employing RAG as a Mitigation Tool
  • Interesting Vendor Efforts to Mitigate LLM Hallucinations

Advice for the Technology Supplier

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  • Related Research
  • Synopsis
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