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.

Summarize the key points discussed in the following text:

Automatic text summarization has become increasingly important in today's information-rich environment, where vast amounts of textual data are generated daily. Effective summarization techniques can help individuals and organizations efficiently process and understand large volumes of information by distilling the most crucial aspects into concise summaries.

Extractive summarization methods are relatively simpler and involve identifying and extracting the most relevant sentences or phrases from the original text to form a summary. These methods typically rely on statistical or linguistic features, such as word frequency, position in the text, and semantic similarity, to score and rank sentences based on their importance.

Abstractive summarization, on the other hand, is a more complex and challenging task. It involves generating entirely new sentences that capture the essence of the source text while potentially rephrasing or paraphrasing the content. This approach often utilizes advanced natural language processing techniques, such as deep learning models, to interpret the text and generate coherent, fluent summaries that may not necessarily contain phrases directly extracted from the original text.
user
The key points discussed in the given text are: 1) The increasing importance of automatic text summarization in dealing with large volumes of textual data. 2) Extractive summarization methods involve identifying and extracting relevant sentences or phrases from the original text based on statistical or linguistic features. 3) Abstractive summarization is more complex, generating new sentences that capture the essence of the source text using advanced natural language processing techniques like deep learning models. 4) Abstractive summaries may rephrase or paraphrase the content instead of directly extracting phrases from the original text.
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