As AI Expands the Media Universe, We Are Going to Have a Ton of Data (Like, So Much Data)

Artificial intelligence is here to stay and our understanding of its capabilities is growing each day, transforming the future of work and perhaps even the fabric of our daily lives. Media & Entertainment companies are rapidly moving to adopt AI applications that will help optimize their operations, improve audience engagement, and streamline content creation and distribution workflows.

A panel of executives from NVIDIA and Oracle convened in the LVCC’s West Hall at the 2023 NAB Show’s Streaming Summit to discuss how AI-driven analytics are being used to make sense of the vast volume of data generated across the M&E value chain and what the future of this technology holds for the industry.

Watch the full NAB Show 2023 session, “AI and the Expansion of the Media and Entertainment Frontier” above.

“AI and the Expansion of the Media and Entertainment Frontier” highlighted the latest AI applications accelerating the content pipeline in broadcast, film, television and game development. The panel discussion was moderated by Sepi Motamedi, global broadcast industry marketing and strategy lead at NVIDIA, and included Ian Andes, senior business development manager for M&E at NVIDIA alongside Rick Champagne, NVIDIA’s head of Industry Strategy and Marketing for M&E, and Alesandra Madurowicz, VP of Media & Entertainment Streaming at Oracle. Watch the full session in the video above.

The discussion kicked off with a recap of the multi-year partnership between NVIDIA and Oracle announced in late 2022, which is intended to help enterprise customers solve business challenges with accelerated computing and AI. The collaboration aims to bring the full NVIDIA accelerated computing stack to Oracle Cloud Infrastructure (OCI), including the addition of tens of thousands of NVIDIA A100 and H100 GPUs to its capacity and NVIDIA BlueField-3 DPUs to its networking stack.

This partnership has enabled initiatives like NVIDIA AI Enterprise, the software layer of the NVIDIA AI platform, which leverages OCI to provide more than 100 frameworks, pretrained models and development tools to streamline development and deployment of production AI, including generative AI. Other initiatives include DGX cloud, a multi-node AI-training-as-a-service solution, providing enterprises their own AI supercomputer in the cloud.

“For those of you who aren’t familiar, NVIDIA is now a full-stack company,” Champagne said. “We have everything from the GPUs that you know us for. But we also have branched out, in fact, in the last five or so years that I’ve been at NVIDIA, we’ve more than doubled in size in terms of employees. We have more software developers now than we have hardware engineers. The company has completely transformed itself.”

This transformation has enabled the recently-announced NVIDIA AI Foundations, the company’s new generative AI cloud services, which are available through DGX Cloud on OCI. These include the NVIDIA NeMo language service for translation and localization, and Picasso, a suite of image, video and 3D services allowing enterprise customers to build proprietary, domain-specific generative AI applications for professional content creation, digital simulation and more.

Content creation generates monumental amounts of data, on both the creator and the consumer sides, but AI can help us understand that data, the panelists agreed. If content is king, then “data is the queen,” said Madurowicz.

“A lot of service providers are thinking about, ‘we need to create more content, make it more engaging, you know, this app, just trying to pump out as much content as possible to stay competitive,’ when in actuality a lot of the platforms that are maintaining the engagement and the retention are really about the personalized and the personalization of the experience of that content,” she explains. “And that’s data. That’s not the content itself, that data is empowering, that those content decisions, and consumers are having the ability to kind of choose their own adventure, based on historical data or real-time data.”

The sheer potential of what can be done with all this data can be overwhelming, Madurowicz continues, but she believes it should be used to create personal recommendations for consumers. “But we’d be remiss to gloss over how AI and AI-driven analytics will affect the internal decision making of, you know, trend forecasting for certain content, when to launch, what systems are operating the most efficiently,” she adds. “It’s the full landscape of where data and analytics are combined for the end experience.”

Building a strategy for AI is vital, Champagne said. “Whatever that strategy may be, you really need to think through what’s going on out there, and how you’re going to how you’re going to work in this new world, how it’s going to help accelerate your business outcomes, how it’s going to help accelerate the work your employees do.”

But AI can do more than simply speed things up, Andes suggested. “The other thing that AI allows you to do is not only create more content faster, but improve the quality of the content being created,” he said.

The proliferation of AI also means that it’s available to organizations of all sizes.

“A couple of years ago, [AI] used to be only for the big, big companies with all the money,” Andes said. “But I think about the power behind the systems and the power behind the AI and how inclusive it is now, so that everybody can partake. And then I think about what used to take seven years, and then got cut down to four years,” he continued.

“The turnaround time for you to be able to go from concept to final output has been fractionalized. So not only is that great for the planet, but it also means that you get to monetize your results faster. Or, if you’re in a broadcast news environment, you get to get that finish that final product out to your end customer that much quicker, which can make a really, really big difference to them.”

Continue the Conversation: Highlights from This Year’s NAB Show