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cover of episode Giving New Life to Unstructured Data with LLMs and Agents

Giving New Life to Unstructured Data with LLMs and Agents

2025/6/6
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AI + a16z
AI Deep Dive AI Chapters Transcript
People
A
Anant Bhardwaj
D
Derek
G
Guido Appenzeller
Topics
Anant Bhardwaj: 我认为AI将显著推动自动化，尤其是在处理非结构化数据方面。传统的RPA在处理非结构化数据时面临挑战，因为它无法适应数据的变化。我们正在押注AI能够克服这些限制，并实现更高效的自动化。我相信，AI不仅可以分析非结构化数据，还可以根据这些数据采取行动，从而彻底改变企业的工作流程。 Derek: 我认为非结构化数据的管理和利用是企业IT的长期目标。非结构化数据是指不能放入SQL数据库中的任何内容，例如PDF文档、图像等。这些数据对业务运营至关重要，但处理和搜索非常困难。AI agents 可以分析文档并对其采取行动。 Guido Appenzeller: 我认为企业对AI的可靠性要求正在发生变化，不再追求绝对完美。他们更关心可预测性，即AI在哪些情况下会出错，以及如何处理这些错误。企业可以接受较低的准确率，只要能够预测哪些部分需要审查。AI将简化信息，提取要点。

Deep Dive

Chapters
This chapter explores the challenges of processing unstructured data using traditional methods like RPA and introduces Instabase's innovative layout-aware models, which leverage LLMs and coordinate encoding to extract insights from complex documents. The discussion highlights the shift from rudimentary techniques to advanced AI solutions for data analysis.
  • Legacy robotic process automation (RPA) struggles with unstructured data.
  • Instabase developed layout-aware models to extract insights from PDFs and complex documents.
  • Encoding X and Y coordinates along with word position significantly improves LLM performance on document understanding.

Shownotes Transcript

Instabase) founder and CEO Anant Bhardwaj joins a16z Infra partner Guido Appenzeller to discuss the revolutionary impact of LLMs on analyzing unstructured data and documents (like letting banks verify identity and approve loans via WhatsApp) and shares his vision for how AI agents could take things even further (by automating actions based on those documents). In more detail, they discuss:

  • Why legacy robotic process automation (RPA) struggles with unstructured inputs.
  • How Instabase developed layout-aware models to extract insights from PDFs and complex documents.
  • Why predictability, not perfection, is the key metric for generative AI in the enterprise.
  • The growing role of AI agents at compile time (not runtime).
  • A vision for decentralized, federated AI systems that scale automation across complex workflows.

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