Generative AI is a game-changer for all sorts of businesses, and how to leverage it is a key strategic and technical concern for a range of streaming organizations looking to monetize their content and operations. Nadine Krefetz, Consultant, Reality Software, Contributing Editor, Streaming Media, explores generative AI’s current and imminent impact with C.J. Leonard, Principal Owner, MAD Leo Consulting, LLC, and Darcy Lorincz, Chief Technology Officer, Barrett-Jackson Auction Company, in this clip from their panel at Streaming Media Connect 2023.
“Which area does GenAI have the most impact from the monetization perspective?” Krefetz asks. “Is it being able to create more versions of something that’s important? Is it being able to target? What is the value that you’re creating out of your gen AI experience?”
C.J. Leonard says, “I don’t have a hard and fast answer to that right now, but I do know that with video, specifically DALL·E 2 and ChatGPT, there’s the paid version. There are other things you can do with scanning video and so forth, [where] all this data that we don’t even realize we have will come into light. And then companies…WPP just did a deal with NVIDIA to be able to use GenAI just for creatives. But I think as they figure out how to take that information about the creatives, pair it with where it ran, what were the users, and ask a GenAI engine, ‘What’s the best way to get greater outcomes?’, I think that will come together over the next few years.”
Krefetz asks Lorincz, “Do you want to chime in on whether you’re seeing it from an efficiency or from a personalization point of view in terms of what is the biggest benefit for you?”
Lorincz focuses on product placement as one unique application of GenAI. Regarding written content, he says that generative language models have already made it possible to incorporate brands easily and quickly into copy with text replace prompts. However, on the video and image side, he says the technology is not quite there yet for easily replicating and replacing images, even though it is catching up fast. “Last week, Midjourney just came out with the ability to replace parts of an image,” he says. “So if I want to replace something on a table, and it’s a Coke bottle, and now I want a beer bottle or something in the background, I can put a rope around it and tell it what to do, and boom, it’s replaced in seconds. So you really see that what used to be a lot of heavy lifting, even for some of these computer vision capabilities for product image replacements, AI just made it a nothing burger.”
Lorincz emphasizes that while using open-source imaging models can be workable, the key now is to train your own generative models. “When you train your own model,” he says, “then you’re all in on only your stuff. It’s only going to be talking in your tone. It’s only going to show you your images. That’s the next step. And at the last Ai4 conference I [attended] a few weeks ago, all the companies there were [talking] about training your own language model.”
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