Why OpenAI's solution to AI hallucinations would kill ChatGPT tomorrow
6 hours ago
- #AI Hallucinations
- #OpenAI Research
- #Language Models
- OpenAI's research paper explains why large language models (LLMs) like ChatGPT hallucinate, stating falsehoods confidently.
- Hallucinations are mathematically inevitable due to the way LLMs predict words based on probabilities, leading to error accumulation.
- Even with perfect training data, hallucinations persist because distinguishing valid from invalid responses is inherently difficult.
- Less frequent facts in training data increase hallucination likelihood (e.g., 20% of rare birthdays were incorrect in tests).
- Post-training efforts (e.g., human feedback) fail because AI benchmarks penalize uncertainty, incentivizing guessing over honest 'I don't know' responses.
- OpenAI proposes AI confidence thresholds to reduce hallucinations, but users may reject systems that frequently express uncertainty.
- Uncertainty-aware models require more computation, raising costs, making them viable only in high-stakes domains (e.g., healthcare, finance).
- Consumer AI prioritizes fast, confident answers due to user expectations, benchmark designs, and cost constraints, perpetuating hallucinations.