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.

Provide a concise overview of the multi-document summarization task and some key challenges involved, based on the following information:

Multi-document summarization involves automatically generating a concise summary from a cluster or set of topic-related documents, rather than summarizing a single text. This expands the scope and complexity compared to single-document summarization. One major challenge is determining which content is crucial across the document set, while avoiding redundancy. The summarizer must identify important concepts that are covered across multiple input documents without simply replicating the same facts verbatim from each one. Additionally, multi-document summaries need to present information in a coherent order and structure akin to how a human might summarize connections across various sources on the same topic. Advanced natural language generation capabilities are often required to fuse information from disparate input texts into seamless, readable summaries.
user
Multi-document summarization involves automatically generating a concise summary from a set of topically related documents, rather than a single text. Key challenges include: 1) Identifying crucial information covered across the document set while avoiding redundancy, 2) Presenting the summary content in a coherent order and structure, fusing information from different source texts, and 3) Requiring advanced natural language generation capabilities to produce seamless, readable summaries from multiple input documents on the same topic.
assistant