English(EN) Models training on model output degrade — that's the known part. The real shift: human-verified, pre-2023 data becomes a scarce asset, like steel forged before

经人类验证的2023年前数据成为AI训练的稀缺资产

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-16 10:12

使用其他AI模型生成的数据训练AI模型会导致性能下降。这凸显了经过人类验证的数据日益稀缺和宝贵，特别是2023年之前的数据。对现有、经过验证的数据集的控制可能成为未来AI训练的显著优势。 AI

影响强调了精心策划的、经过人类验证的数据集作为未来AI发展瓶颈日益增长的重要性。

排序理由该条目讨论了潜在的未来趋势及其对AI训练数据的影响，而不是报告一个具体事件。

在 Mastodon — fosstodon.org 阅读 →

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Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] · 2026-07-16 10:12

Models training on model output degrade — that's the known part. The real shift: human-verified, pre-2023 data becomes a scarce asset, like steel forged before

Models training on model output degrade — that's the known part. The real shift: human-verified, pre-2023 data becomes a scarce asset, like steel forged before the bomb. Whoever archives it owns the next training run. # AI # MachineLearning # LLM # Threadverse # Tech

报道来源 [1]

Models training on model output degrade — that's the known part. The real shift: human-verified, pre-2023 data becomes a scarce asset, like steel forged before

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