Maybe you’ve already expanded your storage environment to accommodate all of this content. In addition to scaling up your primary production system, you might have integrated an archive solution to help off-load completed projects to cost-effective digital media. Archiving content not only frees up valuable capacity on primary storage, it also enables you to preserve content that can be reused and remonetized in the future.
There’s just one problem. Finding specific content in your large and growing storage environment is not only difficult, it’s often impossible.
Let’s say your organization has installed a new type of industrial machine at your plant, and you need to update the safety videos your team produces for workers. To assemble the new video, you want to find any mention of the older machine (so you can replace it) plus some existing footage of your CEO and images of the factory exterior. You know you have plenty of video of each, but where?
It would be simple to find what you’re looking for if all your content had sufficient metadata tags. But let’s face it, your team members don’t have time to manually tag all of your clips as they’re producing new content. And they certainly don’t have time to go back through the hundreds or thousands of hours of completed videos to add tags after the fact.[mk_fancy_title tag_name=”h2″ style=”true” color=”#393836″ size=”14″ font_weight=”inhert” margin_top=”0″ margin_bottom=”18″ font_family=”none” align=”left”]Smart solutions for finding that needle in a haystack[/mk_fancy_title]
Fortunately, artificial intelligence (AI) can help. AI solutions—sometimes called machine-learning or cognitive solutions—might sound like science fiction, but these technologies are real and available now to help you find the precise content you need, even if it’s buried in terabytes or petabytes of data.
Let’s look at three ways AI can help you find video content:
- Audio transcription: To create a new safety video, you need to find every video in which a specific, older machine is mentioned, so you can replace that reference. An AI engine with audio transcription capabilities can analyze all of your existing video and generate text transcriptions of every word spoken. Instead of watching hours of video, you can simply conduct a text search to find mentions of the equipment you’re looking for.
- Object recognition: An AI engine with object recognition capabilities can help you find images of your factory’s exterior. It can learn from a library of labeled images, and then find matched images everywhere they appear in your archived content. Instead of reshooting, you can rapidly locate those perfect shots you’ve already captured.
- Facial recognition: Finding just the right archived videos of your CEO could be difficult—and reshooting might not be a possibility. But an AI engine with facial recognition capabilities can learn from an existing photo, and then scan your videos to pick out possible matches. Once you’ve identified a single match, the AI engine can use machine-learning algorithms to find additional matches.
Applying these AI capabilities to video stored in production systems and your integrated archive can help you find what you need quickly while also letting you avoid reshooting, manually tagging, and manually searching videos.
Quantum and Veritone have teamed up to give you easy access to the power of AI for mining your vast collection of video content. The aiWARE for Xcellis™ integrated, on-premise appliance offers a version of the Veritone aiWARE AI platform for Quantum StorNext® shared storage environments. With this appliance solution, you can capitalize on AI engines quickly and easily without having to migrate data to cloud-based AI services or relinquish control over your content.
Ready to learn more about how AI can help you find what you need among growing storage volumes? Read the e-book, Applying the Power of AI to Your Video Production Storage.[/vc_column_text][/vc_column][/vc_row]