Show HN: NerfWatch() – Track AI degradation with daily tests and community votes

AI Digest

NerfWatch()通过每日测试与社区投票监测AI模型退化，对比自身历史表现并收集用户反馈，当前数据不足依赖捐赠维持运营。

NerfWatch() tracks AI model degradation via daily tests and community votes, comparing models to their own baseline and relying on donations for operational costs.

Key points

• 每日测试对比模型自身首周表现，避免外部干扰 Daily tests compare models to their own first-week baseline
• 社区投票与测试数据结合判断模型退化程度 Community votes validate degradation metrics from tests
• 当前模型测试数据不足，投票参与度偏低 Insufficient data and votes for current models
• 项目依赖捐赠维持API调用费用，无公司背书 Relies on donations for API costs with no corporate ties
• 提供退化预警邮件通知，仅在结论变更时触发 Alerts only trigger when degradation verdict changes

Takeaway: AI模型透明化监测工具，需更多用户参与验证有效性。 / A transparency tool for AI model monitoring requiring broader user participation.

Why it matters 创新性结合技术测试与用户感知，为AI模型评估提供多维视角。