"Matrix” is a word with many different meanings, but they all share the idea of connecting different things into one. In our industry, we often use it to describe the switching equipment that connects signals to various destinations, like an SDI (Serial Digital Interface) “matrix.”
I decided to name this column “The Media Matrix” because I will discuss how many new technologies are linked to media. Using technologies as varied as cloud computing, analytics and AI (Artificial Intelligence), media technologists are constantly changing our companies, the way that creators make content, and how audiences enjoy it.
I will share this space with industry leader Karl Paulsen, where we will talk about the future of tech in media. We are ready to dive into any hot tech trend that pops up and share our insights.
AI at NAB Show
Like the 2023 show, AI was clearly the buzzword at the NAB Show in April and we are going to zoom in on that first. There are many aspects of our business that will be impacted. From preproduction to distribution, every step of the media workflow has the potential to be transformed as AI evolves.
One of the first things that struck me in Las Vegas was how few booths had AI plastered all over them. Sure, there was a lot of buzz about AI at the show, but I thought every booth would have something akin to a flashing neon sign.
Maybe it’s because AI is not new to our industry, and we’ve learned to tone down the hype just a bit. I think technologists are looking for real examples they can apply to their operations now for practical use. There are some areas in media where AI is solid and ready to go—you can see for yourself how subtitling and language translation and even voice generation are working well. You can use AI to analyze content and add metadata to make it easier to find and use. You can use AI in post to improve images or create mattes. These and other use cases are worth exploring and implementing now.
One of the first things that struck me in Las Vegas was how few booths had AI plastered all over them."
At the conference sessions I managed to attend or speak at, there was also a lot of talk about the future possibilities of AI. While people often worry about fake content, in one session there were discussions about how AI can help bring more facts to journalists or directly to viewers in news and sports content genres. There were also discussions about how AI can help personalize content in digital distribution.
What I found most interesting were the number of seasoned technologists who were saying how we’ve seen this kind of disruption many times in media and how the “doom and gloom” predictions about how such disruptions impact creativity or jobs are often wrong.
AI’s Impact
In the next few months, we’ll have a lot of interesting topics to cover here:
Defining AI: What is AI? What are the different kinds of AI? How does AI relate to machine learning? What is the future of AI? What are the limits of AI? How do various types of AI work under the hood? Is the future the big models that get all the attention now, or smaller, more focused approaches to AI?
Workflows and Integration: What parts of the workflow in a media company can benefit from AI and how? How do we make AI work well with other technologies in our workflows? What standards are there for interacting with AI and what standards should media develop?
People and Management: How will AI affect jobs in the media and entertainment industry? What skills do technical folks need to learn to be ready for more AI in their work? How do we deal with the human side of change?
Infrastructure and Architecture: How do we set up our computing and storage layers to handle the heavy AI load in our environment? How do we design our data layer to improve the quality of data used to feed and train models? How do software application layers talk to AI models? Do we have enough power, cooling, and space to run all this stuff?
Cost and Financial: How much does AI really cost and is it worth it in different use cases? Are there ways to optimize the real-world costs of AI? How can we monitor the technology to give us efficiency insights?
Creativity: Can AI take over various craft or creative functions? How “creative” can we expect AI to be? What new content types or genres will AI enable in the media space?
Rights and Legal: What are the intellectual property issues with AI? How do we make sure that AI outputs won’t put our business at risk? What technological controls can we use to help protect the business?
Viewer Response: Do viewers really want a lot of highly personalized content? What about genres like sports where the shared experience is part of the value? As we collect more data about viewers how can we protect their privacy and ensure appropriate controls?
These questions are not all purely technical, but technology issues have been merging with business issues since media adopted IT practices. Today’s broadcast engineers are always asked to evaluate their technology investments through a business lens.
We won’t just talk about AI here. We have some slightly older tech trends still evolving like cloud and blockchain and many more. Interestingly, all these trends intersect with each other. For example, the C2PA (Coalition for Content Provenance and Authenticity) specification is a new approach for content provenance that uses watermarks and blockchain technologies to deal with critical issues like the risk of fake AI content in our ecosystem.
But let’s be honest. We are at the start of the hype cycle for AI, and it’s important to be well-informed on the subject for the many discussions that are coming and so we’ll focus there first.
Writing this column is something I’m very excited about. I’ve been in the media technology field for more than three decades, and it just keeps getting better and more fascinating.
