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: What is a brief summary of the following post?
Two species of palo santo trees are distributed in the Galápagos archipelago, the native Bursera graveolens, and the endemic Bursera malacophylla (Burseraceae). Native Bursera graveolens is the same variety you can find in mainland Ecuador and other countries like Peru. It is called native because it is not an introduced plant, but it came to the islands naturally, thousands of years ago. Bursera malacophylla, on the other hand, grows exclusively in the Galapagos Islands. Palo santo trees (Bursera Jacq. ex L.; Burseraceae) are among the most common and easily recognizable indicator species of the dry and transition zone flora in the Galápagos archipelago. Most of the year, the tree is leafless, but in the rainy season, it quickly produces thin blue-green leaves with toothed edges. The olive shapes fruit turn bright red when ripe, and burst open to reveal black seeds inside. Palo Santo trees (Bursera graveolens) lose their leaves during the dry season to help stop water loss.
Response: There are two types of palo santo tree in the Galápagos called the Bursera graveolens and Bursera malacophylla.

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.

Give a concise summary of the following text: Text summarization is a powerful technique in the field of natural language processing (NLP) that aims to create concise and informative summaries of lengthy documents or large text collections. It plays a crucial role in various applications, such as news aggregation, academic research, legal analysis, and business intelligence, where quickly understanding the essence of vast amounts of textual data is essential. The summarization process typically involves analyzing the original text, identifying the most salient information, and generating a condensed version that captures the key concepts, ideas, and insights while preserving the overall meaning and context. This task can be approached using different techniques, including extractive summarization, which selects and concatenates the most relevant sentences or phrases from the source text, and abstractive summarization, which generates entirely new sentences that convey the underlying meaning and key points. Recent advancements in natural language processing, machine learning, and deep learning have enabled the development of more sophisticated and accurate summarization models, capable of handling complex linguistic structures and producing coherent and fluent summaries.
user
Text summarization is a powerful NLP technique that creates concise and informative summaries of lengthy documents or large text collections, essential for quickly understanding vast textual data in applications like news, research, legal, and business intelligence. It involves analyzing the text, identifying salient information, and generating a condensed version capturing key concepts, ideas, and insights while preserving meaning and context, using techniques like extractive (selecting relevant sentences/phrases) and abstractive (generating new sentences conveying underlying meaning). Recent advancements in NLP, machine learning, and deep learning have enabled more sophisticated and accurate summarization models.
assistant