News

Amazon Releases Container Monitoring for Amazon ECS, EKS, and Kubernetes via CloudWatch

Microsoft plans to rearchitect Azure Stack by making it container-based

Crossplane v0.3 – accelerating support for more clouds and managed services

A standard way of managing configurations for multiple environments (and clouds)

Uber Became Big By Ignoring Laws (and it Plans to Keep Doing That)

This $30 Device Turns the Cold of Outer Space Into Renewable Energy

Understanding Convolutional Neural Networks

A Convolutional Neural Network (CNN) is a class of deep, feed-forward artificial neural networks most commonly applied to analyzing visual imagery. The architecture of these networks was loosely inspired by biological neurons that communicate with each other and generate outputs dependent on the inputs. Though work on CNNs started in the early 1980s, they only became popular with recent technology advancements and computational capabilities that allow the processing of large amounts of data and the training of sophisticated algorithms in a reasonable amount of time.

Three Approaches to Scaling Machine Learning with Uber Seattle Engineering

Reimagining Experimentation Analysis at Netflix

Another day, another custom script to analyze an A/B test. Maybe you’ve done this before and have an old script lying around. If it’s new, it’s probably going to take some time to set up, right?

Introducing LCA: Loss Change Allocation for Neural Network Training

Neural networks (NNs) have become prolific over the last decade and now power machine learning across the industry. At Uber, we use NNs for a variety of purposes, including detecting and predicting object motion for self-driving vehicles, responding more quickly to customers, and building better maps. While many NNs perform quite well at their tasks, networks are fundamentally complex systems, and their training and operation is still poorly understood.