Articles tagged “machine learning”
Testing Firefox more efficiently with machine learning
A browser is an enormously complex piece of software, and it's always in development. About a year ago, we asked ourselves: how could we do better? Our CI relied heavily on human intervention. What if we could instead correlate patches to tests using historical regression data? Could we use a machine learning algorithm to figure out the optimal set of tests to run? We hypothesized that we could run fewer tests to save money, get results faster, and reduce the cognitive burden on developers.
DeepSpeech 0.6: Mozilla’s Speech-to-Text Engine Gets Fast, Lean, and Ubiquitous
The Machine Learning team at Mozilla continues work on DeepSpeech, an automatic speech recognition (ASR) engine which aims to make speech recognition technology and trained models openly available to developers. In this overview of recent improvements, we'll show how DeepSpeech can transform your applications by enabling client-side, low-latency, and privacy-preserving speech recognition capabilities. Find out how you can participate.
Teaching machines to triage Firefox bugs
To help get bugs in front of the right Firefox engineers quickly, we developed BugBug, a machine learning tool that automatically assigns a product and component for each new untriaged bug. By presenting new bugs to triage owners faster, we hope to decrease the turnaround time to fix new issues. Check out BugBug for your own issue-tracking triage.