Provide a summary of the following text about the applications of automatic text summarization:

Automatic text summarization, powered by advances in natural language processing and machine learning, has opened up a wide range of applications across various domains. In the realm of news and media, automatic summarization systems can quickly generate concise summaries of breaking news stories, enabling journalists and readers to stay informed about developing events. In academia and research, these systems can summarize lengthy scientific papers, research reports, and literature reviews, making it easier for researchers to identify and synthesize relevant information from vast databases. Additionally, automatic summarization has applications in business and finance, where it can distill lengthy financial reports, market analyses, and legal documents into digestible summaries, aiding decision-making processes. Furthermore, these systems can be integrated into virtual assistants and chatbots, providing users with succinct summaries of requested information or web content. Automatic text summarization also holds promise in enhancing accessibility for individuals with cognitive or language barriers, by condensing complex materials into simplified and understandable formats.
Provide a summary of the following text about the applications of automatic text summarization:

Automatic text summarization, powered by advances in natural language processing and machine learning, has opened up a wide range of applications across various domains. In the realm of news and media, automatic summarization systems can quickly generate concise summaries of breaking news stories, enabling journalists and readers to stay informed about developing events. In academia and research, these systems can summarize lengthy scientific papers, research reports, and literature reviews, making it easier for researchers to identify and synthesize relevant information from vast databases. Additionally, automatic summarization has applications in business and finance, where it can distill lengthy financial reports, market analyses, and legal documents into digestible summaries, aiding decision-making processes. Furthermore, these systems can be integrated into virtual assistants and chatbots, providing users with succinct summaries of requested information or web content. Automatic text summarization also holds promise in enhancing accessibility for individuals with cognitive or language barriers, by condensing complex materials into simplified and understandable formats.
user
The given text discusses the various applications of automatic text summarization across different domains. Key applications include: 1) In news and media, generating concise summaries of breaking news stories to keep journalists and readers informed. 2) In academia and research, summarizing lengthy scientific papers, reports, and literature reviews to aid researchers in identifying relevant information. 3) In business and finance, distilling financial reports, market analyses, and legal documents into digestible summaries for decision-making. 4) Integration into virtual assistants and chatbots to provide users with succinct summaries of requested information or web content. 5) Enhancing accessibility for individuals with cognitive or language barriers by condensing complex materials into simplified formats.
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: Summarize the quote from Penny Tsavaris in this text.

Getting Back to Lunch Breaks
Tork is dedicated to helping people break the no-breaks habit with their national Take Back the Lunch Break campaign. According to Penny Tsavaris, Brand Communications Manager, “For years, we’ve called employees to take back the lunch break because we know they are happier and more productive when they step away from work midday.”
Response: Employees need to take a lunch break because it makes them happier and more productive.

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.
