Summarize the key points of the following text about text summarization techniques:

Automatic text summarization is the process of shortening a set of data computationally to create a subset that represents the most important or relevant information within the original content. Summarization methods are either extractive or abstractive. Extractive summarization involves identifying important sections of the text and outputting them as is. Abstractive summarization aims to generate new phrases and sentences that capture the most salient ideas in a more concise form. Some popular abstractive summarization models use neural networks and are trained on large datasets to produce high-quality summaries. While extractive summarization is faster and simpler, abstractive techniques can produce more coherent and fluent summaries.
Summarize the key points of the following text about text summarization techniques:

Automatic text summarization is the process of shortening a set of data computationally to create a subset that represents the most important or relevant information within the original content. Summarization methods are either extractive or abstractive. Extractive summarization involves identifying important sections of the text and outputting them as is. Abstractive summarization aims to generate new phrases and sentences that capture the most salient ideas in a more concise form. Some popular abstractive summarization models use neural networks and are trained on large datasets to produce high-quality summaries. While extractive summarization is faster and simpler, abstractive techniques can produce more coherent and fluent summaries.
user
The key points are: 1) Automatic text summarization shortens text data computationally to extract the most important information. 2) Summarization techniques are either extractive (identifying and outputting important sections verbatim) or abstractive (generating new, concise phrases and sentences). 3) Abstractive summarization models often use neural networks trained on large datasets to produce high-quality summaries. 4) Extractive summarization is faster but abstractive can produce more coherent and fluent summaries.
assistant
Generate a series of (instruction, response) pairs that are similar in context and structure to the example provided below. Each pair should consist of a concise instruction followed by an appropriate, detailed response. The instruction should pose a clear task or question, while the response should provide a comprehensive answer or solution that could be understood by someone with a basic understanding of the subject.

Example pair: 
Instruction: Please read this text: 

People consume information in lots of different ways: visually, audibly, through text, and sometimes all three at once. Search engine algorithms like Google’s are advancing to reflect this experience for users. No longer will the algorithms just look at web pages as a single piece of text content. Google will look at all the ways real people consume information: text, images, videos, infographics, tables, charts, and interactive elements that make up a piece of content.

In recent years, we saw the rise of visual search – particularly in image-heavy industries like travel and tourism or ecommerce. Moving into 2023, Google will expand its foothold in multisearch and multisearch near me. 

What does it say about multi-format content in a brief summary?
Response: The text says that people prefer content in different forms like audio, video, or text format. As a result, Google plans to advance the multi-search function and page search algorithms accordingly. 

Your task is to generate more pairs that maintain this level of clarity and detail. The topic is Summarization. Write a long text of instruction by yourself, then summarize the given instruction in a response. Ensure that the responses are informative and accurate, suitable for an educational context. 

Store the generated pairs in valid JSON format, with each pair as an object within an array. Each object should have two key-value pairs: "instruction" and "response". For instance: 

{"contents": [{"instruction": "text", "response": "text"}, {"instruction": "text", "response": "text"}, ...]} 

Remember to maintain consistency in the format and ensure the generated pairs are diverse and cover a broad range of subjects. You must return the response in the asked format and you must not add any additional text in your response.
