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Announcing: Agentic Document Extraction! PDF files represent information visually - via layout, charts, graphs, etc. - and are more than just text. Unlike traditional OCR and most PDF-to-text approaches, which focus on extracting the text, an agentic approach lets us break a document down into components and reason about... show more

Andrew Ng

1,574,259 subscribers

688,993 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 11

Фото профиля Arnav Jaitly

Arnav Jaitly1 год назад

This is such a pain point for a lot of companies. Agentic information extraction will be such a productivity and efficiency boost

Фото профиля PDF GPT

PDF GPT1 год назад

This is my favorite AI tool for reviewing reports. Just upload a report, ask for a summary, and get one in seconds. It's like ChatGPT, but built for documents. Try it for free.

Фото профиля Andrei Hasna

Andrei Hasna1 год назад

Well done and well needed.

Фото профиля Vasilis K.

Vasilis K.1 год назад

@JackPNicholls

Фото профиля The AI Agent Architect

The AI Agent Architect1 год назад

Great use case. Using an agentic approach to this is kinda like getting the LLM to add metadata to what it finds in the PDF. So many thing you could do with that. If you want to see the opposite side of that coin - the creation of a structured Word document by an agent from only two simple commands, there will be a video demo showing this in my next article tomorrow.

Фото профиля 🔮

🔮1 год назад

Love what you’re doing! For what it’s worth the URL in your video is wrong and hits a 404

Фото профиля Mr Rio

Mr Rio1 год назад

this is what I need

Фото профиля RyanRejoice

RyanRejoice1 год назад

This is incredible and a game changer for handling and analyzing pdf data.

Фото профиля Clara Data

Clara Data1 год назад

Innovative spin on PDFs! Looking promising for future efficiency!

Фото профиля Huxley MindOS

Huxley MindOS1 год назад

Mastering the PDF mystery: deciphering both scroll & scribe! Sounds innovative. Looking forward to the details.

Фото профиля Javier Modified

Javier Modified1 год назад

Agentic Document Extraction? Finally, AI can stop pretending it understands charts. This is how you handle a PDF! 🚀

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Agentic Document Extraction just got much faster! From previous 135sec median processing time down to 8sec. Extracts not just text but diagrams, charts, and form fields from PDFs to give LLM-ready output. Please see the video for details and some application ideas.

Agentic Document Extraction just got much faster! From previous 135sec median processing time down to 8sec. Extracts not just text but diagrams, charts, and form fields from PDFs to give LLM-ready output. Please see the video for details and some application ideas.

Andrew Ng

290,315 просмотров • 1 год назад

New course: Document AI: From OCR to Agentic Doc Extraction, built with LandingAI, where I'm executive chairman, and taught by David Park and Andrea Kropp. Much of the world's data is locked in PDFs, JPEGs, and other documents. This short course shows you how to build agentic workflows that process documents accurately: breaking them into parts, examining each piece carefully, and extracting information through multiple iterations. Traditional Optical Character Recognition (OCR) captures text but loses context from table headers, chart captions, or reading order of columns. After exploring OCR's limitations, you’ll use LandingAI's Agentic Document Extraction (ADE) framework to process documents. ADE treats pages as visually -- as images -- to parse information and extract fields. Skills you'll gain: - Build agents to convert unstructured files into structured Markdown/HTML and JSON - Use ADE to parse complex data like forms, handwriting, or equations - Map extracted information to named fields using a specified schema, with bounding boxes for grounding and validation - Deploy RAG applications with event-driven document processing Come learn about the best tools for processing documents like financial invoices, medical records, or academic papers intelligently:

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Andrew Ng

198,231 просмотров • 4 месяцев назад

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29,746 просмотров • 2 месяцев назад

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Andrew Ng

192,808 просмотров • 10 месяцев назад

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