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AugLy: A new data augmentation library to help build more robust AI models What the research is:We are open-sourcing AugLy, a new Python library that will help AI researchers use data augmentations to evaluate and improve the robustness of their machine learning models. Augmentations can include a wide variety of modifications to a piece of content, ranging from recropping a photo to changing the
EngineeringUber AI Labs Open Sources Pyro, a Deep Probabilistic Programming LanguageNovember 3, 2017 / Global Achieving Uber’s goal of bringing reliable transportation to everyone requires effortless prediction and optimization at every turn. Opportunities range from matching riders to drivers, to suggesting optimal routes, finding sensible pool combinations, and even creating the next generation
For the past month, we ranked nearly 250 Machine Learning Open Source Projects to pick the Top 10. We compared projects with new or major release during this period. Mybridge AI ranks projects based on a variety of factors to measure its quality for professionals. Average number of Github stars in this edition: 1,385⭐️“Watch” Machine Learning Top 10 Open Source on Github and get email once a month
オンプレミスでディープラーニング(深層学習)を活用するユーザーにとって、米フェイスブック(Facebook)は最も頼れる存在になるかもしれない。深層学習フレームワークだけでなく、学習済みモデルもオープンソースソフトウエア(OSS)として公開し始めたからだ。AI(人工知能)クラウドで稼ぎたい競合には追随できない手法で自社製OSSの普及を図る。 フェイスブックは2018年5月1、2日に米サンノゼで開催した開発者会議「Facebook F8」で、AIに関する新しい施策を発表した。2日目の基調講演に登壇したCTO(最高技術責任者)のマイク・シュローファー(Mike Schroepfer)氏は、同社が中心となって開発を進めるOSSの深層学習フレームワーク「Caffe2」と「PyTorch」を統合して数カ月以内に「PyTorch 1.0」としてリリースする計画や、フェイスブックによる学習済みの機械学習
IntroductionWith the deluge of deep learning libraries and software innovation in the field over the last few years, it is an exciting time to be working on machine learning problems. Most of the libraries available evolved from fairly specialized computational code for large dense problems such as image classification into general frameworks for neural-network-based models offering marginal suppo
As an example of the kind of improvements T2T can offer, we applied the library to machine translation. As you can see in the table above, two different T2T models, SliceNet and Transformer, outperform the previous state-of-the-art, GNMT+MoE. Our best T2T model, Transformer, is 3.8 points better than the standard GNMT model, which itself was 4 points above the baseline phrase-based translation sys
By Jay Mahadeokar and Gerry Pesavento Automatically identifying that an image is not suitable/safe for work (NSFW), including offensive and adult images, is an important problem which researchers have been trying to tackle for decades. Since images and user-generated content dominate the Internet today, filtering NSFW images becomes an essential component of Web and mobile applications. With the e
Gym is a standard API for reinforcement learning, and a diverse collection of reference environments# The Gym interface is simple, pythonic, and capable of representing general RL problems: import gym env = gym.make("LunarLander-v2", render_mode="human") observation, info = env.reset(seed=42) for _ in range(1000): action = policy(observation) # User-defined policy function observation, reward, ter
A few days ago, Facebook open-sourced its artificial intelligence (AI) hardware computing design. Most people don’t know that large companies such as Facebook, Google, and Amazon don’t buy hardware from the usual large computer suppliers like Dell, HP, and IBM but instead design their own hardware based on commodity components. The Facebook website and all its myriad apps and subsystems persist on
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic under federal,
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