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English(EN) Most enterprise # AI projects don't stall because the model is wrong. They stall because the database can't meet production requirements. pgEdge CEO David Mitch

AI项目失败源于数据库限制，而非模型

作者 PulseAugur 编辑部 · [1 个来源] ·

企业AI项目频繁失败并非由于模型不准确，而是因为现有数据库无法满足代理式系统的需求。这些系统需要实时数据检索、操作启动和跨系统推理，而传统数据基础设施往往缺乏这些能力。pgEdge首席执行官David Mitchell强调了这一挑战，并指出需要能够支持这些复杂、动态AI操作的数据库。 AI

影响 强调了强大的数据库基础设施对于在企业环境中成功部署和扩展代理式AI系统至关重要。

排序理由 该集群包含一篇由首席执行官发表的关于行业常见挑战的观点文章。

在 Mastodon — fosstodon.org 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI项目失败源于数据库限制，而非模型

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该集群包含一篇由首席执行官发表的关于行业常见挑战的观点文章。
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报道来源 [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    大多数企业级AI项目并非因模型错误而停滞。它们停滞是因为数据库无法满足生产需求。pgEdge CEO David Mitch

    Most enterprise # AI projects don't stall because the model is wrong. They stall because the database can't meet production requirements. pgEdge CEO David Mitchell explains why agentic systems make this harder: they're not just answering questions. They retrieve live data, initia…

    链接 rtinsights.com/how-todays-agentic-ai-chan…

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