Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world. Phone Number: +1-650-246-9381 Email: [email protected]
228 Park Avenue South New York, NY 10003 United States
Website: Publisher: https://towardsai.net/#publisher Diversity Policy: https://towardsai.net/about Ethics Policy: https://towardsai.net/about Masthead: https://towardsai.net/about
Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-François Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
Towards AI Cover
Logo:
Towards AI Logo
Areas Served: Worldwide Alternate Name: Towards AI, Inc. Alternate Name: Towards AI Co. Alternate Name: towards ai Alternate Name: towardsai Alternate Name: towards.ai Alternate Name: tai Alternate Name: toward ai Alternate Name: toward.ai Alternate Name: Towards AI, Inc. Alternate Name: towardsai.net Alternate Name: pub.towardsai.net
5 stars – based on 497 reviews

Frequently Used, Contextual References

TODO: Remember to copy unique IDs whenever it needs used. i.e., URL: 304b2e42315e

Resources

Take our 85+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!

Publication

Phi-3 and Azure: PDF Data Extraction | ExtractThinker
Latest   Machine Learning

Phi-3 and Azure: PDF Data Extraction | ExtractThinker

Last Updated on June 10, 2024 by Editorial Team

Author(s): JΓΊlio Almeida

Originally published on Towards AI.

Extracting structured data from PDFs and images can be challenging, but combining Optical Character Recognition (OCR) with Language Models (LLMs) offers a powerful solution. Within the Azure ecosystem, Azure Document Intelligence is the way to go when analyzing documents.

In this article, I will demonstrate how to leverage the Phi-3 mini model from the Azure AI studio to enhance the data extraction process. The Phi-3 mini model, a small language model (SML) with 3.8 billion parameters, provides efficient and accurate results, making it an ideal choice for this task. While this example focuses on Azure, the principles can be applied using similar tools from other providers.

The solution can be easily replicated for other cloud providers with comparable quality, pricing, and features.

Azure Document Intelligence is an OCR product present in the Microsoft ecosystem. In terms of pricing, it is divided into three tiers as you can see in the image below:

Prices for each DocumentType

The β€œread” only extracts paragraphs and handwritten text. Essentially a pure traditional OCR. This would be enough for most of the document extraction, but for complex documents will not suffice.

The β€œprebuilt” layout is the best choice for the job, the rest will be done by the LLM. This option… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.

Published via Towards AI

Feedback ↓