The hallucination effect and AI
IBM defines AI hallucinations as 'a phenomenon wherein a large language model (LLM)—often a generative AI chatbot or computer vision tool—perceives patterns or objects that are nonexistent or imperceptible to human observers, creating outputs that are nonsensical or altogether inaccurate.'.
The 'CIOB Artificial Intelligence (AI) Playbook 2024', glossary of terms, published by the Chartered Institute of Building (CIOB) describes similalry where tools are ' unable to identify if the phrases they generate make sense or are accurate. This can sometimes lead to inaccurate results, also known as ‘hallucination’ effects, where large language models generate plausible sounding but inaccurate text. Hallucinations can also result from biases in training datasets or the model’s lack of access to up- to-date information.'
See generative AI, large language models and the long expanding list of AI tools for building planning, design, construction and management.
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