Madonna continues to push forward, among early adopters of AI’s next wave
Whenever Madonna sings the 1980s hit “La Isla Bonita” on her concert tour, moving images of swirling, sunsettinted clouds play on the giant arena screens behind her.
To get that ethereal look, the pop legend embraced a still-uncharted branch of generative artificial intelligence — the text-to-video tool. Type some words — say, “surreal cloud sunset” or “waterfall in the jungle at dawn” — and an instant video is made.
Following in the footsteps of AI chatbots and still imagegenerators, some AI video enthusiasts say the emerging technology could one day upend entertainment, enabling you to choose your own movie with customizable story lines and endings. But there’s a long way to go before they can do that, and plenty of ethical pitfalls on the way.
For early adopters like Madonna, who’s long pushed art’s boundaries, it was more of an experiment. She nixed an earlier version of “La Isla Bonita” concert visuals that used more conventional computer graphics to evoke a tropical mood.
“We tried CGI. It looked pretty bland and cheesy and she didn’t like it,” said Sasha Kasiuha, content director for Madonna’s Celebration Tour that continues through late April. “And then we decided to try AI.”
ChatGPT-maker OpenAI gave a glimpse of how sophisticated text-to-video technology might look when the company recently showed off Sora, a new tool that’s not yet publicly available. Madonna’s team tried a different product from New York-based startup Runway, which helped pioneer the technology by releasing its first public text-to-video model last March. The company released a more advanced “Gen-2” version in June.
Runway CEO Cristóbal Valenzuela said while some see those tools as a “magical device that you type a word and somehow it conjures exactly what you had in your head,” the most effective approaches are by creative professionals looking for an upgrade to the decades-old digital editing software they’re already using.
He said Runway can’t yet make a full-length documentary. But it could help fill in some background video, or b-roll — the supporting shots and scenes that help tell the story.
“That saves you perhaps like a week of work,” Valenzuela said. “The common thread of a lot of use cases is people use it as a way of augmenting or speeding up something they could have done before.”
AI VIDEO PITFALLS
Dangers await. Without effective safeguards, AI videogenerators could threaten democracies with convincing “deepfake” videos of things that never happened, or — as is already the case with AI image generators — flood the internet with fake pornographic scenes depicting what appear to be real people with recognizable faces. Under pressure from regulators, major tech companies have promised to watermark AI-generated outputs to help identify what’s real.
There also are copyright disputes brewing about the video and image collections the AI systems are being trained upon (neither Runway nor OpenAI discloses its data sources) and to what extent they are unfairly replicating trademarked works. And there are fears that, at some point, video-making machines could replace human jobs and artistry.
For now, the longest AIgenerated video clips are still measured in seconds, and can feature jerky movements and telltale glitches such as distorted hands and fingers. Fixing that is “just a question of more data and more training,” and the computing power on which that training depends, said Alexander Waibel, a computer science professor at Carnegie Mellon University who’s been researching AI since the 1970s.
“Now I can say, ‘Make me a video of a rabbit dressed as Napoleon walking through New York City,’” Waibel said. “It knows what New York City looks like, what a rabbit looks like, what Napoleon looks like.”
Which is impressive, he said, but still far from crafting a compelling storyline.
CONGEALING THE RANDOMNESS
Before it released its firstgeneration model last year, Runway’s claim to AI fame was as a co-developer of the imagegenerator Stable Diffusion. Another company, Londonbased Stability AI, has since taken over Stable Diffusion’s development.
The underlying “diffusion model” technology behind most leading AI generators of images and video works by mapping noise, or random data, onto images, effectively destroying an original image and then predicting what a new one should look like. It borrows an idea from physics that can be used to describe, for instance, how gas diffuses outward.
“What diffusion models do is they reverse that process,” said Phillip Isola, an associate professor of computer science at the Massachusetts Institute of Technology. “They kind of take the randomness and they congeal it back into the volume. That’s the way of going from randomness to content. And that’s how you can make random videos.”
In the near term, AIgenerated videos will likely show up in marketing and educational content, providing a cheaper alternative to producing original footage or obtaining stock videos, said Aditi Singh, a researcher at Cleveland State University who has surveyed the text-to-video market.
When Madonna first talked to her team about AI, the “main intention wasn’t, ‘Oh, look, it’s an AI video,’” said Kasiuha, the creative director.
“She asked me, ‘Can you just use one of those AI tools to make the picture more crisp, to make sure it looks current and looks high resolution?’” Kasiuha said. “She loves when you bring in new technology and new kinds of visual elements.”