Report: “A New Use For AI: Summarizing Scientific Research for Seven-Year-Olds”

Note: The service discussed in the article below should not be confused with the TLDR paper summarization service provided by the wonderful Semantic Scholar database.

From The Verge:

Academic writing often has a reputation for being hard to follow, but what if you could use machine learning to summarize arguments in scientific papers so that even a seven-year-old could understand them? That’s the idea behind tl;dr papers — a project that leverages recent advances in AI language processing to simplify science.

Work on the site began two years ago by university friends Yash Dani and Cindy Wu as a way to “learn more about software development,” Dani tells The Verge, but the service went viral on Twitter over the weekend when academics started sharing AI summaries of their research. The AI-generated results are sometimes inaccurate or simplified to the point of idiocy. But just as often, they are satisfyingly and surprisingly concise, cutting through academic jargon to deliver what could be mistaken for child-like wisdom.

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Unfortunately, although tl;dr papers has had a rapturous reception among the academic world, its time in the spotlight looks limited. After going viral this weekend, the website has been labeled “under maintenance,” and the site’s creators say they have no plans to maintain it in the future. (They also mention that other tools have been built that perform the same task.)

Dani told The Verge that tl;dr papers “was designed to be an experiment to see if we can make learning about science a little easier, more fun, and engaging.” He says: “I appreciate all of the attention the app has received and thank all of the people who have tried it out [but] given this was always intended to be an educational project, I plan to sunset tl;dr papers in the coming days to focus on exploring new things.

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