LLM Hallucination Seems Like a Big Problem, Not a Mere Speedbump
11 days ago
- #AI
- #Hallucination
- #LLM
- LLMs like GPT-5 and Gemini 2.5 Flash frequently hallucinate nonexistent sources when asked for specific citations.
- Despite claims of reduced hallucinations, synthetic benchmarks fail to capture real-world frequency, and many examples of GPT-5 hallucinations exist.
- LLMs often insist their hallucinated sources are real, misleading users who lack skepticism.
- The need for constant human verification undermines the efficiency and value proposition of LLMs.
- LLMs do not think or reason; they are sophisticated next-character prediction engines.
- The hype around LLMs ignores their profound limitations, creating a dangerous bubble in both media and markets.
- Marketing around LLMs is misleading, as they construct responses based on scoring patterns rather than truth.
- In professional domains, verifying LLM outputs often takes longer than doing the work independently.
- Limited research shows engineers are slower when using LLMs, contradicting claims of efficiency.
- The Gell-Mann amnesia effect explains societal over-trust in LLMs despite evident flaws.