[a16z Crypto: AI-Based Judgment Mechanisms Could Address Prediction Market Scalability Bottlenecks] Odaily Planet Daily reports that a16z Crypto published an article titled 'What to do when prediction markets fail,' which points out that the biggest challenge faced by prediction markets is not 'pricing the future,' but determining what actually happened. Similar issues frequently arise in small-scale events, where incorrect or non-transparent settlement mechanisms can undermine market trust, liquidity, and the accuracy of price signals. Industry experts suggest introducing large language models (LLMs) as adjudicators for prediction markets, including measures such as committing rules on-chain, resisting manipulation, enhancing transparency, and improving neutrality. For instance, during contract creation, specific LLM models, timestamps, and judgment prompts could be encrypted and recorded on the blockchain. This would allow traders to understand the complete decision-making mechanism in advance. Fixed model weights would prevent easy tampering, reducing the risk of fraud. Settlement mechanisms would be open, auditable, and free from arbitrary human rulings. AI judgment mechanisms could significantly improve the efficiency and scalability of prediction market settlements while ensuring transparency and fairness.