Google is looking for coders who can design machine learning algorithms for tagging 700,000 audio video files in its YouTibe-8M dataset. Machine learning coding teams are welcome to join the competition.
Although most of us may not have heard of YouTube-8M, for those of you who are into machine learning, YouTube-8M is a big deal, since it essentially allows them to test out their algorithms on a large database of video content.
With today’s major update of YouTube-8M Google has allowed even more labels across its humongous audio video database. But Google being Google, it does not want to rest on its laurels, it wants to further optimize the dataset.
Google has now launched a Kaggle competition, which offers sizeable chunks of cash for the geek team which can design the best algorithm for tagging 700,000 new videos in the YouTube-8M dataset.
“The dataset was created from over 7 million YouTube videos (450,000 hours of video) and includes video labels from a vocabulary of 4716 classes (3.4 labels/video on average,” wrote Google on the competition page.
“It also comes with pre-extracted audio & visual features from every second of video (3.2B feature vectors in total).”
The winning team will be announced at the YouTube-8M Workshop, which is held during the IEEE Conference on Computer Vision and Pattern Recognition in July.
The wining team will not only receive $30,000 in prize money but there’s also a good chance of them being absorbed by Google. If that wasn’t enough, Google is also offering some free Google Cloud credits to early participants.
Although the end results of the competition will not directly affect us consumers, however, as noted by Paul Natsev, a Google software engineer, the end result it be very useful since it will allow for the creation of smarter search filters and content filtering for YouTube.