Summarize the key points about the applications and challenges of text summarization from the following text:

Text summarization has numerous applications across various domains, including news and media, research and academia, legal and business domains, and more. In the news industry, summarization algorithms can automatically generate concise summaries of news articles, enabling readers to quickly grasp the most important information. In academia, researchers can use summarization to quickly comprehend the key findings and contributions of research papers. In the legal domain, summarization can help lawyers and judges efficiently review and understand lengthy legal documents. However, text summarization also faces several challenges. One significant challenge is capturing the context and nuances of the original text, which can be lost in the summarization process. Additionally, generating coherent and fluent summaries, particularly in the case of abstractive summarization, remains a complex task that requires advanced natural language processing techniques. Furthermore, evaluating the quality and accuracy of summaries is challenging, as it often relies on subjective human judgment.
Summarize the key points about the applications and challenges of text summarization from the following text:

Text summarization has numerous applications across various domains, including news and media, research and academia, legal and business domains, and more. In the news industry, summarization algorithms can automatically generate concise summaries of news articles, enabling readers to quickly grasp the most important information. In academia, researchers can use summarization to quickly comprehend the key findings and contributions of research papers. In the legal domain, summarization can help lawyers and judges efficiently review and understand lengthy legal documents. However, text summarization also faces several challenges. One significant challenge is capturing the context and nuances of the original text, which can be lost in the summarization process. Additionally, generating coherent and fluent summaries, particularly in the case of abstractive summarization, remains a complex task that requires advanced natural language processing techniques. Furthermore, evaluating the quality and accuracy of summaries is challenging, as it often relies on subjective human judgment.
user
The key points about the applications and challenges of text summarization are: 1) Text summarization has numerous applications across domains like news, academia, legal, and business, enabling efficient comprehension of important information. 2) In news, it can generate concise article summaries; in research, it can summarize key findings and contributions; in legal, it can help review lengthy documents. 3) However, capturing context and nuances of the original text is a challenge that can lead to loss of information. 4) Generating coherent and fluent summaries, especially with abstractive methods, requires advanced natural language processing techniques. 5) Evaluating the quality and accuracy of summaries is challenging due to the subjective nature of human judgment.
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.
