We’re committed to providing the community with high-performance machine learning tools so that everyone can create intelligent apps and services. Caffe2 is shipping with tutorials and examples that demonstrate learning at massive scale which can leverage multiple GPUs in one machine or many machines with one or more GPUs. Learn to train and deploy models Read more about Caffe2 Open Source Brings Cross Platform Machine Learning Tools to Developers[…]

The idea is to collect and analyse quantities of information to understand consumer tastes, recommend products to people and personalise websites for customers. Otto’s work stands out because it is already automating business decisions that go beyond customer management. The most important is trying to lower returns of products, which cost the firm millions of Read more about AI Otto buys stock for ecommerce, decreases customer returns[…]

No one really knows how the most advanced algorithms do what they do. That could be a problem. Source: There’s a big problem with AI: even its creators can’t explain how it works It’s a good run down of some of the places where accountability (self-driving cars, medical recommendations, AI driven tanks and drones, Siri, Read more about There’s a big problem with AI: even its creators can’t explain how it works[…]

We have found that the flexibility and adaptiveness of TensorFlow lends itself to building higher level frameworks for specific purposes, and we’ve written one for quickly building neural network modules with TF. We are actively developing this codebase, but what we have so far fits our research needs well, and we’re excited to announce that Read more about Open sourcing Sonnet – a new library for constructing neural networks with Tensorflow[…]

At first, the bot lingo was more like Morse code: an abstract symbol was agreed upon and then scattered among spaces to create meaning, the researchers explained in a blog post. The team tweaked the experiment so that there was a slight penalty on every utterance for every bot, and they added an incentive to Read more about This AI stuff is all talk! Bots invent their own language to natter away behind humans’ backs[…]

The system, which has been trained on thousands of hours of BBC News programmes, has been developed in collaboration with Google’s DeepMind AI division. “Watch, Attend and Spell”, as the system has been called, can now watch silent speech and get about 50% of the words correct. That may not sound too impressive – but Read more about Towards a lip-reading computer[…]

MXNet stands for mix and maximize. The idea is to combine the power of declartive programming together with imperative programming. In its core, a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. The library Read more about MXNet – Amazon machine learning Open sourced[…]

Cloud Video Intelligence API (now in Private Beta) uses powerful deep-learning models, built using frameworks like TensorFlow and applied on large-scale media platforms like YouTube. The API is the first of its kind, enabling developers to easily search and discover video content by providing information about entities (nouns such as “dog,” “flower” or “human” or Read more about Google Cloud can now recognise items in videos[…]

Keras: Deep Learning library for Theano and TensorFlow You have just found Keras. Keras is a high-level neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least Read more about Keras – deep learning library for Tensorflow and Theano[…]

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Source: Caffe | Deep Learning Framework

Tensors and Dynamic neural networks in Python with strong GPU acceleration. PyTorch is a deep learning framework that puts Python first. We are in an early-release Beta. Expect some adventures. Source: PyTorch

Machine learning is cropping up more and more in research papers – does it work? Source: From drugs to galaxy hunting, AI is elbowing its way into boffins’ labs • The Register

We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input image to output image, but also learn a loss function to train this mapping. This makes it possible to apply the same generic approach to problems that traditionally would require very different loss Read more about Image-to-Image Translation with Conditional Adversarial Networks[…]

ETSI is pleased to announce the creation of the Industry Specification Group ‘Experiential Network Intelligence’ (ISG ENI). The purpose of the group is to define a Cognitive Network Management architecture that is based on the “observe-orient-decide-act” control model. It uses AI (Artificial Intelligence) techniques and context-aware policies to adjust offered services based on changes in Read more about New ETSI group on improving operator experience using Artificial Intelligence[…]

Gamalon uses a technique that it calls Bayesian program synthesis to build algorithms capable of learning from fewer examples. Bayesian probability, named after the 18th century mathematician Thomas Bayes, provides a mathematical framework for refining predictions about the world based on experience. Gamalon’s system uses probabilistic programming—or code that deals in probabilities rather than specific Read more about AI Software Juggles Probabilities to Learn from Less Data[…]

Graph Engine – Open Source Microsoft Graph Engine is a distributed in-memory data processing engine, underpinned by a strongly-typed in-memory key-value store and a general distributed computation engine. This repository contains the source code of Graph Engine and its graph query language — Language Integrated Knowledge Query (LIKQ). LIKQ is a versatile graph query language Read more about Microsoft Graph Engine goes open source on github[…]

As described by Hadley Wickham, tidy data has a specific structure: each variable is a column each observation is a row each type of observational unit is a table This means we end up with a data set that is in a long, skinny format instead of a wide format. Tidy data sets are easier Read more about The Life-Changing Magic of Tidying Text in an R package[…]

text2vec is an R package which provides an efficient framework with a concise API for text analysis and natural language processing (NLP). Goals which we aimed to achieve as a result of development of text2vec: Concise – expose as few functions as possible Consistent – expose unified interfaces, no need to explore new interface for Read more about text2vec[…]

Source: multilabel datasets (for mulan) UCI Center for Machine Learning and Intelligent Systems Machine Learning Repository Netflix Prize dataset

Initially used to improve the experience for visually impaired members of the Facebook community, the company’s Lumos computer vision platform is now powering image content search for all users. This means you can now search for images on Facebook with key words that describe the contents of a photo, rather than being limited by tags Read more about Facebook’s AI unlocks the ability to search photos by what’s in them[…]

As the “Brains vs. Artificial Intelligence: Upping the Ante” poker competition nears its halfway point, Carnegie Mellon University’s AI program, Libratus, is opening a lead over its human opponents — four of the world’s best professional poker players.One of the pros, Jimmy Chou, said he and his colleagues initially underestimated Libratus, but have come to Read more about CMU AI Is Tough Poker Player[…]

A bunch of highly funded researchers Source: The Google Brain Team Publications subdivided into subjects Machine Intelligence publications subset Big Picture does a lot of high level visualisation of datasets and their relationships