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PyTorch 1.4 Release Introduces Java Bindings, Distributed Training
PyTorch, Facebook's open-source deep-learning framework, announced the release of version 1.4. This release, which will be the last version to support Python 2, includes improvements to distributed training and mobile inference and introduces support for Java.
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PyTorch 1.3 Release Adds Support for Mobile, Privacy, and Transparency
Facebook recently announced the release of PyTorch 1.3. The latest version of the open-source deep learning framework includes new tools for mobile, quantization, privacy, and transparency.
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Facebook AI Releases New Computer Vision Library Detectron2
Facebook AI Research (FAIR) has released Detectron2, a PyTorch-based computer vision library that brings a series of new research and production capabilities to the framework. While the first Detectron was written in Caffe2, Detectron2 represents a full rewrite of the original framework in PyTorch from the ground up, with several new object detection capabilities.
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Facebook Open-Sources CraftAssist Framework for AI Assistants in Minecraft
Facebook AI researchers open-sourced CraftAssist, a framework for building interactive assistants for the Minecraft video game. The bots use natural language understanding (NLU) to parse and execute text commands from human players, such as requests to build houses in the game world. The framework's modular structure can be extended by researchers to perform their own ML experiments.
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Facebook Releases AI Code Search Datasets
Facebook AI released a dataset containing coding questions paired with code-snippet answers, intended for evaluating AI-based natural-language code search systems. The release also includes benchmark results for several of Facebook's own code-search models and a training corpus of over 4 million Java methods parsed from over 24,000 GitHub repositories.
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Facebook Open-Sources Hydra to Simplify Configuration Management in Python Programs
Facebook Hydra is a new open-source framework aimed to speed up the creation of Python applications by simplifying the implementation of common functionality such as command-line argument handling, configuration management, and logging.
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Facebook Open-Sources RoBERTa: an Improved Natural Language Processing Model
Facebook AI open-sourced a new deep-learning natural-language processing (NLP) model, Robustly-optimized BERT approach (RoBERTa). Based on Google's BERT pre-training model, RoBERTa includes additional pre-training improvements that achieve state-of-the-art results on several benchmarks, using only unlabeled text from the world-wide web, with minimal fine-tuning and no data augmentation.
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Facebook, Microsoft, and Partners Announce Deepfake Detection Challenge
Facebook, Microsoft, the Partnership on AI, and researchers from several universities have created the Deepfake Detection Challenge (DDC), a contest to produce AI that can detect misleading images and video that have been created by AI. The challenge includes several grants and awards for the teams that create the best AI solution, using the DDC's dataset of real and fake videos.
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Facebook Proposes New IsInputPending API for Faster Input Event Processing
Facebook recently announced its first major browser API contribution. The new isInputPending API aims to shorten the time between a user input and its processing by the browser, and to increase the user experience of highly interactive applications.
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Facebook and University Researchers Developing Mind-Reading System
As part of a Facebook Reality Labs (FRL) brain-computer interface (BCI) research program called Project Steno, a team of scientists from the University of California, San Francisco (UCSF) described their work on converting brain waves into a text transcription of speech. The goal of Facebook's project is a device that allows users to "type" by imagining themselves speaking.
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The First AI to Beat Pros in 6-Player Poker, Developed by Facebook and Carnegie Mellon
Facebook AI Research’s Noam Brown and Carnegie Mellon’s professor Tuomas Sandholm recently announced Pluribus, the first Artificial Intelligence program able to beat humans in 6 player hold-em poker. In the past years, computers have progressively improved, beating humans in checkers, chess, Go, and the Jeopardy TV show. Poker poses more challenges around information asymmetry and bluffing.
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Facebook Open-Sources Deep-Learning Recommendation Model DLRM
Facebook AI Research announced the open-source release of a deep-learning recommendation model, DLRM, that achieves state-of-the-art accuracy in generating personalized recommendations. The code is available on GitHub, and includes versions for the PyTorch and Caffe2 frameworks.
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Moving Embodied AI forward, Facebook Open-Sources AI Habitat
In a recent blog post, Facebook has announced they have open-sourced AI Habitat, an Artificial Intelligence (AI) simulation platform that is designed to train embodied agents, such as virtual robots. Using this technology, robots can learn how to grab an object from an adjacent room or assist a visually-impaired person in navigating an unfamiliar transit system.
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Sign In with Apple Touts Single Sign-On without Sharing Your Data
At the recent WWDC 2019, Apple announced its own Single Sign-On (SS) service, dubbed Sign in with Apple. Deemed "Apple's most significant new innovation" by Time, Sign in with Apple promises not to share any personal user data, including email addresses.
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PyTorch 1.1 Release Improves Performance, Adds New APIs and Tools
Facebook AI Research announced the release of PyTorch 1.1. The latest version of the open-source deep learning framework includes improved performance via distributed training, new APIs, and new visualization tools including native support for TensorBoard.