If you produce video content, nothing beats a large archive of content. Not only can you draw upon it to cost-effectively create new programming, but you can monetize it by selling stock content to other content producers. It’s an asset that becomes more valuable over time.
But one thing stands between content and its potential value: accessibility. Do you know how to find the right content quickly? Do you have an automated way to extract exactly the right content from your archive, or are you relying on spreadsheets, rough guesses, and the irreplaceable memory of your archive manager?
In order to move away from those dangerously inefficient approaches, the secret is something that’s already in your data: metadata. That’s information about your data, contained within the data. File storage includes basic and limited metadata – but object storage provides the ability to include a vast amount of metadata. If you can tag your content with the right metadata, you’ll turn your archives into a deeply searchable asset of data that’s as easily searched as the world wide web.
But what if you have many years’ worth of content that’s never been tagged with metadata? Even if they transition to object storage, few organizations can afford to hire people to view vast amounts of archival material and record metadata. Without a solution to accelerate the process, the size of your archive becomes a liability.
That’s where Cloudian’s integration with AI platforms like Machine Box can help. By creating artificial intelligence and machine learning that can apply your search criteria to content, emerging solutions can rapidly examine years of content, apply the correct metadata, and dramatically improve your ability to find the right content when you need it. Instead of your data being impenetrable, it offers a wide range of possibilities.
As AI matures, it will enable content producers to make their searches more specific and improve searchability over time. Content will be searchable by the basic information regarding its creation – date, time, original program and general subject – but also by any other criteria that become important. Those criteria may include everything from general demographic information to very specific criteria, allowing identification of things like the make of a car, the time of day video was shot, and via facial recognition, even the specific people included in the content.
What does this mean for content producers? It means that AI can help do a wide range of tasks to make using and working with content easier, from spotting obscenities in video clips to tagging appearances by specific performers to automatically identifying the relevant content for individual on-line users.
This flexibility means that AI that identifies and applies metadata will find a wide variety of uses. The technology has obvious applications in security, surveillance, and even in retail and customer loyalty – imagine a “smart store” that uses facial recognition in real time to identify repeat customers and uses that as a trigger to generate mobile marketing offers, or delivers the past buying history of a customer to store personnel to allow them to provide personalized assistance. Another application would be in loss prevention, where a retailer could understand who’s in their stores and to keep previous offenders from offending again.
These powerful AI tools don’t work on their own – they need a robust infrastructure behind them. They generate an enormous amount of data in the course of their operation. That may make a cloud-based storage approach cost prohibitive – the more the data is transmitted and accessed, the more an organization pays to store and access that data. An on-premises solution doesn’t impose that cost penalty, ultimately resulting in less consumption of resources and huge cost savings as a result. Cloudian’s HyperStore offers limitlessly scaleable on-premises object storage that can handle not just increased amounts of data resulting from greater use of metadata, but also more intensive data formats like 4K and 8K video and virtual reality. Adding storage capacity is as simple as adding additional storage nodes.
If you’re at the NAB Show today, be sure to stop by Booth SL6321 at 3 p.m. Machine Box CEO Aaron Edell will be there speaking about how to make AI work for your business, and the how object storage is an ideal repository for AI training data. See you at 3!Share This: