Summarize the following passage about the history and importance of text summarization:

Summarization has been an active area of research in the field of natural language processing for several decades. It involves condensing a piece of text into a shorter version while retaining the most important information and overall meaning. The ability to summarize text is crucial in today's information-rich world, where we are constantly bombarded with large amounts of data from various sources.

Automatic text summarization can be traced back to the late 1950s when researchers at IBM explored techniques for selecting and condensing sentences from technical documents. However, it wasn't until the 1990s that significant advances were made, driven by the increasing availability of digital text and computational power.

Text summarization has numerous applications, ranging from generating news headlines and article summaries to condensing lengthy documents for quick reference. It is also employed in various domains, such as legal, medical, and scientific fields, where professionals need to quickly grasp the essence of voluminous reports and papers.

Different summarization techniques have been developed over the years, including extractive and abstractive methods. Extractive summarization involves selecting and concatenating the most important sentences or phrases from the original text, while abstractive summarization aims to generate entirely new sentences that capture the key points.

Recent advancements in deep learning and natural language processing have led to significant improvements in abstractive summarization, with models capable of understanding the context and generating coherent, fluent summaries. However, challenges remain, such as ensuring factual consistency, capturing subtle nuances, and tailoring summaries to specific user needs or domains.
Summarize the following passage about the history and importance of text summarization:

Summarization has been an active area of research in the field of natural language processing for several decades. It involves condensing a piece of text into a shorter version while retaining the most important information and overall meaning. The ability to summarize text is crucial in today's information-rich world, where we are constantly bombarded with large amounts of data from various sources.

Automatic text summarization can be traced back to the late 1950s when researchers at IBM explored techniques for selecting and condensing sentences from technical documents. However, it wasn't until the 1990s that significant advances were made, driven by the increasing availability of digital text and computational power.

Text summarization has numerous applications, ranging from generating news headlines and article summaries to condensing lengthy documents for quick reference. It is also employed in various domains, such as legal, medical, and scientific fields, where professionals need to quickly grasp the essence of voluminous reports and papers.

Different summarization techniques have been developed over the years, including extractive and abstractive methods. Extractive summarization involves selecting and concatenating the most important sentences or phrases from the original text, while abstractive summarization aims to generate entirely new sentences that capture the key points.

Recent advancements in deep learning and natural language processing have led to significant improvements in abstractive summarization, with models capable of understanding the context and generating coherent, fluent summaries. However, challenges remain, such as ensuring factual consistency, capturing subtle nuances, and tailoring summaries to specific user needs or domains.
user
Text summarization is a crucial technique in natural language processing that condenses lengthy texts into shorter versions while preserving key information. It has a long history dating back to the 1950s, with research accelerating in the 1990s due to increasing digital data and computational power. Summarization finds applications in various domains, from news to legal and scientific fields. Techniques include extractive methods that select important sentences and abstractive methods that generate new sentences. Recent advances in deep learning have improved abstractive summarization, but challenges remain in ensuring factual accuracy and capturing nuances.
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: Shorten the following text to less than 50 words: 

Plant oils have been used medicinally for over 2,500 years. The first references to the use of plant oils can be traced to Chinese medicine, also known as Traditional Chinese Medicine.

Various parts of plants were consumed in either the raw state or dried, boiled, or steamed (to extract the oil). The end product was then consumed, inserted into any one of the natural openings of the body, massaged into the skin, or inhaled in vapor form.

During the Medieval period, a collection of medicinal treatments for a variety of ailments was published by Abu Ali al-Husain Ebn Abdullah Ebn Sina (980–1037 AD). He was known in the West as Avicenna, a Persian physician who was also known as one of the most influential medical writers in the medieval period.

Avicenna`s Canon of Medicine, arguably one of the most famous books in the history of medicine, presents a clear and organized summary of all of the medical knowledge of the time, including a long list of drugs. Interestingly, lily and spotted orchid oils are mentioned as remedies for tinnitus (Mahdizadeh et al, 2015).

Throughout the 18th and 19th centuries, advances in western medicine progressed. The American Medical Association was founded in 1847 and the American Pharmaceutical Association was founded in 1852. At the federal level, the Food, Drug, and Insecticide Administration (FDIA) was created 1927 and, three years later, changed its name to the Food and Drug Administration (FDA).
Response: Plant oils have been used for a long time. Plants in general have been used in many forms and in many ways, with publications about this ranging from Traditional Chinese Medicine to the Medieval period. Since then, Western medicine has progressed, with organizations like the FDA being founded. 

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.
