You know why we love math? Unbeknownst to most, it helps computer scientists create spam filters.
Computer science grad student Neil Toronto created a new way to compute complicated math, making spam filters, voice commands, and artificial weather simulations that much easier to create.
This new groundbreaking programming language can save developers working with probabilistic mathematics substantial amounts of work.
“I made math more like a programming language,” said Toronto, who created this distinct programming language, naming it Lambda-ZFC. Toronto originally created the programming language to help statisticians make more efficient spam filters, but it is now applicable to many different fields, including creating voice commands and scaling in digital imaging.
Instead of adapting the programming language to complicated math as people have tried in the past, Lambda-ZFC makes the math itself readable by the computer.
“It’ll put grad students out of work,” Jay McCarthy said with a chuckle. “So they can do more interesting tasks. I think people’s time will be better spent exploring on the white board than exploring in the program.”
There are some who can do the white board probabilistic math but can’t translate the mathematics into a computer. Lambda-ZFC allows these people to do both instantaneously because it’s designed to mimic the way one writes math.
“(Lambda-ZFC) sort of equalizes opportunity in who can produce that program,” McCarthy said. “If you have steam shovels, you don’t need big muscles. With Lambda-ZFC, you don’t need big brains.”
Lambda-ZFC’s potential to improve computing probabilistic mathematics has not gone unrecognized. Last May, Toronto and McCarthy presented their work to an academic audience in Kobe, Japan.