The days of us communicating with our computers by using our fingers are nearing an end. Google announced that it is releasing its language parsing neural network framework, SyntaxNet, as an open source system.
The released code includes everything you need to train it using your own data set, though Google is also releasing a version already fluent in English: Parsey McParseface.
This has the capability of changing Artificial Intelligence(AI) forever, and also allows anyone to add Voice Recognition to their apps.
Combining machine learning and search techniques, Parsey McParseface is 94 percent accurate, according to Google. It also leans on SyntaxNet’s neural-network framework for analyzing the linguistic structure of a sentence or statement, which parses the functional role of each word in a sentence.
If you’re confused, here’s the short version: Parsey and SyntaxNet are basically like five year old humans who are learning the nuances of language.
And if you’re wondering why Parsey McParseface is even necessary, here’s Google’s explanation:
One of the main problems that makes parsing so challenging is that human languages show remarkable levels of ambiguity. It is not uncommon for moderate length sentences – say 20 or 30 words in length – to have hundreds, thousands, or even tens of thousands of possible syntactic structures. A natural language parser must somehow search through all of these alternatives, and find the most plausible structure given the context.
Parsey McParseface and SyntaxNet aren’t a solution; Google considers them a first step toward better AI language parsing, which is a persistent hurdle.
Besides, a more natural conversation could make Chirp really awesome someday.