Summarize the key information about the history and development of summarization techniques.
Summarize the key information about the history and development of summarization techniques.
user
Summarization techniques have evolved over several decades. Early approaches relied on extracting important sentences based on heuristic rules or statistical features. In the 1990s, machine learning methods were introduced, using techniques like naive Bayes classifiers to identify salient sentences. With the rise of neural networks, more advanced models like sequence-to-sequence architectures and transformer-based systems have enabled abstractive summarization, generating new text beyond just extracting existing sentences. Recent years have seen progress in areas like multi-document summarization, query-focused summarization, and incorporating external knowledge.
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: I want to lose weight, summarize the new weight-loss findings in this article:

"A REVOLUTION IN weight loss is apparently underway. It started in 2021, when the FDA approved the diabetes drug semaglutide for weight loss. The weekly injectable—sold under the brand name Wegovy—can help users lose 5 to 10 percent of their body weight, leading commentators to describe the drug as both a “medical breakthrough” and a “silver bullet” for obesity. Elon Musk says he’s taking it, Kim Kardashian is rumored to be using it, and everyone from Hollywood to the Hamptons reportedly wants a prescription.  Soon, there will be a new weight loss medication on the block—and it’s even more potent than its peers. Last fall, the FDA fast-tracked the review process for using tirzepatide as a weight loss drug after a clinical trial showed that people with BMIs labeled “overweight” or “obese” lost a staggering 22.5 percent of their body weight on the highest dose. If all goes according to plan, that will make Mounjaro the latest in a fast-growing biomedical sector—spanning everything from bariatric surgery to deep brain stimulation for binge-eating—that aims to combat, if not cure, the problem of “excess” weight. 

For pharmaceutical companies, the race to market is financially motivated: Wegovy and Mounjaro cost more than $1,000 a month. Weight loss drugs are rarely covered by insurance, but people who can afford them have proven they’re willing to pay. And the market seems effectively limitless: Despite an ongoing “war on obesity,” more than 1.9 billion adults globally are considered overweight or obese, and the number of prospective users is growing every year. Now doctors—desperate to treat what is widely seen as an “obesity epidemic”—are coming on board. In January, the American Academy of Pediatrics recommended such medications for kids as young as 12.  The victorious narratives gilding drugs like Mounjaro are already being positioned as a direct challenge to fat activism. For decades, the movement has pushed for social and economic opportunity for people of all sizes through civil rights, fat pride and liberation, and biomedical evidence itself. Thanks to prominent voices like Aubrey Gordon and Michael Hobbes, many people now know that “lifestyle changes” like calorie restriction and exercise fail to produce sustained weight loss for 97 percent of people and that many dieters end up gaining back more weight than they lost. But what happens to the strength of these arguments when a weight loss drug seems to work?

Like other purported weight loss solutions, Mounjaro promises “to fix weight stigma by making you thinner, instead of removing the stigma,” says Susanne Johnson, a fat activist and family nurse practitioner in Pennsylvania. In so doing, these drugs and surgeries further exacerbate anti-fat discrimination. Instead of criticizing people in larger bodies for their perceived lack of willpower—that old “calories in, calories out” adage—people can now blame those in bigger bodies for something more akin to a techno-pessimist, or even anti-science, stance: “Just take the miracle cure!” "
Response: The weight-loss findings in the article are the following:

A new injectable drug (called Wegovy) has been called a "silver bullet" for weight loss and has the potential for the user to lose between 5-10% of their body weight. Another drug called tirezpatide showed a 22.5% decrease in body weight in its clinical trial (currently being fast-tracked by the FDA). However, both of these drugs can cost upwards of $1000 a month (weight-loss drugs are usually not covered by insurance).

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.
