#ordinary language

I've just posted a summary and some thoughts on, and from, the talk Bob Hopkins gave for the London Aesthetics Forum earlier this month. | Hopkins on individual artistic style

Robert Hopkins – Artistic Style as the Expression of Ideals (joint work with Nick Riggle) London Aesthetic Forum Wednesday 2 October 2019 The Senate House

What is it for a work of art to exhibit the artist’s individual artistic style?

A common view, Hopkins and Riggle (H&R) say, is that for a work of art to exhibit an artistic style is for it to express the artist’s personality, or some…

New Post has been published on http://www.newsnish.com/technology/computer/operating-system/writing-programs-using-ordinary-language/

Writing programs using ordinary language

Systems that can convert written specifications into working code in a few narrow cases could be generalized to other tasks.

In a pair of recent papers, researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have demonstrated that, for a few specific tasks, it’s possible to write computer programs using ordinary language rather than special-purpose programming languages.

The work may be of some help to programmers, and it could let nonprogrammers manipulate common types of files — like word-processing documents and spreadsheets — in ways that previously required familiarity with programming languages. But the researchers’ methods could also prove applicable to other programming tasks, expanding the range of contexts in which programmers can specify functions using ordinary language.

“I don’t think that we will be able to do this for everything in programming, but there are areas where there are a lot of examples of how humans have done translation,” says Regina Barzilay, an associate professor of computer science and electrical engineering and a co-author on both papers. “If the information is available, you may be able to learn how to translate this language to code.”

In other cases, Barzilay says, programmers may already be in the practice of writing specifications that describe computational tasks in precise and formal language. “Even though they’re written in natural language, and they do exhibit some variability, they’re not exactly Shakespeare,” Barzilay says. “So again, you can translate them.”

The researchers’ recent papers demonstrate both approaches. In work presented in June at the annual Conference of the North American Chapter of the Association for Computational Linguistics, Barzilay and graduate student Nate Kushman used examples harvested from the Web to train a computer system to convert natural-language descriptions into so-called “regular expressions”: combinations of symbols that enable file searches that are far more flexible than the standard search functions available in desktop software.

In a paper being presented at the Association for Computational Linguistics’ annual conference in August, Barzilay and another of her graduate students, Tao Lei, team up with professor of electrical engineering and computer science Martin Rinard and his graduate student Fan Long to describe a system that automatically learned how to handle data stored in different file formats, based on specifications prepared for a popular programming competition.