AI summarization
Summarize documents, text, and more with generative AI and LLMs
Use Google’s large language models (LLMs), generative AI, and Google Cloud services to summarize documents and text.
New customers get up to $300 in free credits to try Vertex AI and other Google Cloud products.
New customers get up to $300 in free credits on signup to apply towards a document summarizing solution.
Overview
What is AI summarization?
Put simply, AI summarization is the use of AI technologies to distill text, documents, or content into a short and easily digestible format. For example, AI summarization can use natural language processing or understanding to condense a long PDF and restate its most important takeaways in just a few sentences.
What is the best AI for summarization?
The best AI for summarization varies depending on your goals. Google's Gemini can help you summarize text, code, scripts, musical pieces, email, letters, and more for personal use. For more advanced summarization, including for research and business intelligence purposes, the Gemini API in Vertex AI can extract a summary of the most important information from text using summarization prompts.
Is there an AI that summarizes documents?
Google Cloud's Document AI uses generative AI to easily generate customizable (length and other variables can be changed based on preferences) summaries for documents. And with Document AI Warehouse, users can get answers to natural language questions about their documents.
What are the benefits of AI summarization?
The benefits of AI summarization range from cost savings to improved accessibility to information. AI summarization can help businesses and organizations save time and money when producing research, business intelligence, or insights. AI-powered summarization can extract key information from news articles, research, legal and financial documents, technical literature, and even customer feedback. Summartization, then, means more time acting on information instead of sifting through it.
What are the challenges of AI summarization?
There are a number of challenges associated with AI summarization, mostly the use of immature technology or improperly-tuned AI. AI summarization machine learning (ML) models can sometimes lack context, leading to uninformative summaries. Summarizations can also be biased, depending on the AI used and how it was trained, resulting in inaccurate or factually incorrect results. But with the proper AI, ML training, and services in place many of these issues can be minimized or potentially avoided.
How It Works
AI summarization uses machine learning (ML) models to generate a concise synopsis from text, documents, etc. There are two primary types of AI summarization: extractive and abstractive. Extractive summarization leverages statistical methods to identify sentences that are most likely to be important. Abstractive summarization generates new sentences that summarize the main points of the original text.
AI summarization uses machine learning (ML) models to generate a concise synopsis from text, documents, etc. There are two primary types of AI summarization: extractive and abstractive. Extractive summarization leverages statistical methods to identify sentences that are most likely to be important. Abstractive summarization generates new sentences that summarize the main points of the original text.
Common Uses
Summarize using LLMs
Deploy an AI summarization solution in the Google Cloud console
Launch a Google-recommended, preconfigured solution that uses generative AI to quickly extract text and summarize large documents.
How-tos
Deploy an AI summarization solution in the Google Cloud console
Launch a Google-recommended, preconfigured solution that uses generative AI to quickly extract text and summarize large documents.
Document summarization
Build a document summarizer in the Google Cloud console
In this guide, you'll create a document summarizer processor, upload a sample document for processing, and create a custom processor version to adjust the summary structure. The guide will also cover how to enable Document AI in a Google Cloud project and use the document summarizer.
How-tos
Build a document summarizer in the Google Cloud console
In this guide, you'll create a document summarizer processor, upload a sample document for processing, and create a custom processor version to adjust the summary structure. The guide will also cover how to enable Document AI in a Google Cloud project and use the document summarizer.
Generative AI summarization
Summarize text content using generative AI (code sample)
This code sample lets you summarize text content using a publisher text model using Vertex AI. Sample code is viewable in Google Cloud documentation and on GitHub.
How-tos
Summarize text content using generative AI (code sample)
This code sample lets you summarize text content using a publisher text model using Vertex AI. Sample code is viewable in Google Cloud documentation and on GitHub.
Start summarizing with AI
New customers get $300 in free credits
Try gen AI summarization in Vertex AI
Generative AI on Google Cloud
AI-powered code assistance
