Anyone with even a passing interest in machine learning understands how these algorithms learn to perform their intended function by example. This has

A Shiny New Programming Language

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2024-11-20 13:30:14

Anyone with even a passing interest in machine learning understands how these algorithms learn to perform their intended function by example. This has proven to be a very powerful technique. It has made it possible to build algorithms that can reliably recognize complex objects in images, for example, which would be virtually impossible with standard rules-based programming techniques.

Austin Z. Henley of Carnegie Mellon University has been exploring the idea of using a set of examples when running inferences against a trained model as well. Specifically, Henley has been designing a proof of concept programming-by-example programming language that is powered by a large language model (LLM). The basic idea of this unique language, called Mirror, is that the programmer should just provide a few input-output examples for a function, then the LLM should write and execute the actual code behind the scenes.

To use Mirror, a user first defines the signature (name, input and output parameter data types) of a function. This is followed by one or more example calls of the function, with appropriate input and output parameters supplied. Functions are then called and chained together as needed to accomplish the programmer's goal.