Google Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source - Polidicks

[url]http://googleresearch.blogspot.com/2016/05/announcing-syntaxnet-worlds-most.html?m=1[/url] [QUOTE]At Google, we spend a lot of time thinking about how computer systems can read and understand human language in order to process it in intelligent ways. Today, we are excited to share the fruits of our research with the broader community by releasing SyntaxNet, an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding (NLU) systems. Our release includes all the code needed to train new SyntaxNet models on your own data, as well as Parsey McParseface, an English parser that we have trained for you and that you can use to analyze English text. Parsey McParseface is built on powerful machine learning algorithms that learn to analyze the linguistic structure of language, and that can explain the functional role of each word in a given sentence. Because Parsey McParseface is the most accurate such model in the world, we hope that it will be useful to developers and researchers interested in automatic extraction of information, translation, and other core applications of NLU. [/QUOTE] [QUOTE]Google is among those at the forefront of this research—such tech plays into both its primary search engine and the Siri-like assistant it operates on Android phones—and today, the company signaled just how big of a role this technology will play in its future. It open sourced the software that serves as the foundation for its natural language work, freely sharing it with the world at large. Yes, that’s the way it now works in the tech world. Companies will give away some of their most important stuff as a way of driving a market forward. This newly open source software is called SyntaxNet, and among natural language researchers, it’s known as a syntactic parser. Using deep neural networks, SyntaxNet parses sentences in an effort to understand what role each word plays and how they all come together to create real meaning. The system tries to identify the underlying grammatical logic—what’s a noun, what’s a verb, what the subject refers to, how it relates to the object—and then, using this info, it tries to extract what the sentence is generally about—the gist, but in a form machines can read and manipulate. “The accuracy we get substantially better than what we were able to get without deep learning,” says Google research director Fernando Pereira, who helps oversee the company’s work with natural language understanding. He estimates that the tool has cut the company’s error rate by between 20 and 40 percent compared to previous methods. This is already helping to drive live Google services, including the company’s all-important search engine.[/QUOTE] [url]http://www.wired.com/2016/05/google-open-sourced-syntaxnet-ai-natural-language/[/url]

[QUOTE]Our release includes all the code needed to train new SyntaxNet models on your own data, [b]as well as Parsey McParseface[/b], an English parser that we have trained for you and that you can use to analyze English text. Parsey McParseface is built on powerful machine learning algorithms that learn to analyze the linguistic structure of language, and that can explain the functional role of each word in a given sentence. [b]Because Parsey McParseface is the most accurate such model in the world[/b], we hope that it will be useful to developers and researchers interested in automatic extraction of information, translation, and other core applications of NLU.[/QUOTE] Son of a bitch :v:

not to be confused with SkyNet

I wish I could figure out how to download it, but none of the links seem to let me. This seems like it would be an interesting project for studying language.

[QUOTE=Zenreon117;50310169]I wish I could figure out how to download it, but none of the links seem to let me. This seems like it would be an interesting project for studying language.[/QUOTE] There is a [URL="https://github.com/tensorflow/models/tree/master/syntaxnet"]github link[/URL] in the first link in the OP that tells you what do to.

[QUOTE=Zenreon117;50310169]I wish I could figure out how to download it, but none of the links seem to let me. This seems like it would be an interesting project for studying language.[/QUOTE] [url]https://github.com/tensorflow/models/archive/master.zip[/url]

I read the title as SkyNet at first :v: