Source: A little light reading: Transit trends, video datasets and more stories from around Google from Google Cloud
At Google Cloud, we love to share how we’re shaping our cloud computing technology. Beyond the cloud blog, though, we know there are lots of fascinating stories from around Google. Here’s a reading list of stories that grabbed our attention recently.
How stuffed is your bus? See transit trends from Google Maps
This post contains some fun graphics and data about the relative crowdedness of various bus and subway lines around the world (fun for us to look at, though perhaps not so much fun for those on the crowded subway cars). The trends are pulled from the aggregated, anonymized feedback data that Google Maps users can opt to give after they’ve used transit mode. One line of the Buenos Aires subway came in first for most crowded worldwide. You can also see breakdowns of the most crowded lines for certain cities.
And take a look at how ML now helps predict transit delays
For more on the topic of transportation trends, check out this blog post on how Google Maps now forecasts bus delays in hundreds of cities using machine learning. (Again, not pleasant for those waiting for the buses in question, but fascinating for ML enthusiasts.) Though some city transit agencies provide public delay data, not all do. This new prediction capability depends on an ML model that combines real-time car traffic forecasts with data on bus routes and stops. To build the model, teams extracted training data from sequences of bus positions over time, based on transit agency feeds, then aligned those to car traffic speeds on the bus’s path.
Get a sense of scale with YouTube-8M Segments
The new YouTube-8M Segments is an extension of the large-scale YouTube-8M dataset, a video classification dataset with, you guessed it, more than 8 million videos. The dataset comes with precomputed audio and visual features from billions of video frames and audio segments. These new segments include human-verified labels at the five-second segment level within a set of the YouTube-8M videos. The idea behind the release is to speed up research into temporal localization—allowing better search within videos—with the aim of improving video tag predictions and enabling uses like capturing special video moments, for example. Human-labeled annotations provide a baseline to help researchers evaluate their algorithms more accurately without having to label every segment in a video. There’s an accompanying Kaggle competition challenge and ICCV workshop as well.
Brush off your mail merge skills
The use of mail merge—combining a data source with a master template document—has been around since the dawn of word processing. Mail merge can create customized copies of the master doc to include unique data records from the data source—for example, adding customer addresses to a form letter. With the launch of the Google Docs API, it’s now easy to do mail merge in the cloud and build custom mail merge apps.
Automate all the things—even at home
If you want your home technology to run as smoothly as your work technology, you’ve got a lot of interesting device options these days. This post covers some tips on connecting IoT devices to Google Assistant and using Actions to create routines and tasks. You’ll see how to control devices with voice commands as well as use a visual interface, and get some detail on the back-end integrations you can set up.
What thought-provoking stories have you read lately? Let us know.