Facebook to Open PyText Source Code

NLP-library (Natural Language Processing - processing of natural speech) is used in neural networks for the processing of written and oral speech
17 December 2018   1669

Facebook has opened the source code for PyText, a library for processing spoken and written language. According to the developers, such a move should accelerate the development of the project.

NLP-library (Natural Language Processing - processing of natural speech) is used in neural networks for the processing of written and oral speech. According to the developers, the tool is useful for document classification, speech sequence marking, semantic analysis, and multitasking modeling.

The structure of the library makes it easy to move from the development of an NLP system to practical application. The company's engineers claim that using the PyText implementation of the neural network model that recognizes human speech will take only a few days.

Library features:

  • PyText is based on PyTorch, a framework with a developed ecosystem, so models created using the NLP library are easy to publish.
  • The tool includes several ready-made models. The structure of PyText allows you to modify them with little effort, which simplifies development.
  • Developers have included special models in the library that use the context of speech to better recognize the essence of statements. They are tested on datasets using the M Suggestions tool (one of the helper functions) in Facebook Messenger.
  • PyText can conduct distributed training, as well as work with several models at the same time.
  • Integration with the PyTorch framework allows the library to convert models to ONNX and use the Caffe2 engine to export them.
  • Scaling your own models in PyTorch is limited due to the multithreading limit of the Global Interpreter Lock principle in Python.
  • Exported models allow you to use C ++ features to improve performance.

The company is already using PyText in practice. According to the developers, the models created with its help make more than a billion predictions on Facebook every day. The opening of the source code and a free license should attract independent specialists to the improvement of the tool. At the same time, the company's engineers are not eliminated from further developing the system. They intend to focus on the use of its capabilities in the field of mobile devices.

Get more info at GitHub

BNC to Monitor BTC Community's Mood

The system called Twitter Sentiment analyzes over 34M BTC-related Twitter posts each week, using AI to track the mood of the community
22 January 2020   479

Blockchain-based New Zealand-based research firm Brave New Coin (BNC) has unveiled a new system for measuring the mood of the Bitcoin community based on Twitter messages.

According to BNC, the new Twitter Sentiment rating system analyzes over 34 million BTC-related Twitter posts each week. The company uses artificial intelligence (AI) algorithms that look for records containing the words bitcoin, $ BTC and BTC and others.

BNC notes that user sentiment continues to be a “significant” factor in the price and dynamics of digital assets, and a new technique has been developed to track these sentiments. According to the BNC, it took 18 months to launch the Bitcoin Twitter Sentiment. The data obtained is divided into seven categories - Opinion, Technical Information, Inside the Network, Advertising, Bots, Macros and Hacking.

For the week ending January 17, the most common entries were in the Opinion category - their number was 30.42% of all data received. In second place was the category Technical Information, and in third inside the network (includes information on mining and hashrate).

BNC spokeswoman Pierre Ansaldi said that during the first quarter of this year, the company will also launch community sentiment analysis tools for other crypto assets.