Using Machine Learning to Ensure the Capacity Safety of Individual Microservices

Reliability engineering teams at Uber build the tools, libraries, and infrastructure that enable engineers to operate our thousands of microservices reliably at scale. At its essence, reliability engineering boils down to actively preventing outages that affect the mean time between failures (MTBF). As Uber’s global mobility platform grows, our global scale and complex network of […]

Introducing Ludwig, a Code-Free Deep Learning Toolbox

Over the last decade, deep learning models have proven highly effective at performing a wide variety of machine learning tasks in vision, speech, and language. At Uber we are using these models for a variety of tasks, including customer support, object detection, improving maps, streamlining chat communications, forecasting, and preventing fraud. Many open source libraries, […]

Machine Learning-Powered Search Ranking of Airbnb Experiences

How we built and iterated on a machine learning Search Ranking platform for a new two-sided marketplace and how we helped itgrow. Airbnb Experiences are handcrafted activities designed and led by expert hosts that offer a unique taste of local scene and culture. Each experience is vetted for quality by a team of editors before […]

Teaching AI to learn speech the way children do

A collaboration between the Facebook AI Research (FAIR) group and the Paris Sciences & Lettres University, with additional sponsorship from Microsoft Research, to challenge other researchers to teach AI systems to learn speech in a way that more closely resembles how young children learn. The ZeroSpeech 2019 challenge (which builds on previous efforts in 2015 […]

Updating Neural Networks to Recognize New Categories, with Minimal Retraining

Many of today’s most popular AI systems are, at their core, classifiers. They classify inputs into different categories: this image is a picture of a dog, not a cat; this audio signal is an instance of the word “Boston”, not the word “Seattle”; this sentence is a request to play a video, not a song. […]

AI Blueprints: Implementing content-based recommendations using Python

In this article, we’ll have a look at how you can implement a content-based recommendation system using Python and the scikit-learn library. But before diving straight into this, it’s important to have some prerequisite knowledge of the different ways by which recommendation systems can recommend an item to users. Content-based: A content-based recommendation finds similar […]

Manifold: A Model-Agnostic Visual Debugging Tool for Machine Learning at Uber

Uber built Manifold, a model-agnostic visualization tool for ML performance diagnosis and model debugging, to facilitate a more informed and actionable model iteration process. Machine learning (ML) is widely used across the Uber platform to support intelligent decision making and forecasting for features such as ETA prediction and fraud detection. For optimal results, we invest […]

AI year in review

At Facebook, we think that artificial intelligence that learns in new, more efficient ways – much like humans do – can play an important role in bringing people together. That core belief helps drive our AI strategy, focusing our investments in long-term research related to systems that learn using real-world data, inspiring our engineers to […]