We’re not there quite yet. A big problem with generative video is the lack of control users have over the output. Producing still images can be hit and miss; producing a few seconds of video is even more risky.
“Right now it’s still fun, you get a-ha moments,” says Miao. “But generating video that is exactly what you want is a very hard technical problem. We are some way off generating long, consistent videos from a single prompt.”
That’s why Vyond’s Lipkowitz thinks the technology isn’t yet ready for most corporate clients. These users want a lot more control over the look of a video than current tools give them, he says.
Thousands of companies around the world, including around 65% of the Fortune 500 firms, use Vyond’s platform to create animated videos for in-house communications, training, marketing, and more. Vyond draws on a range of generative models, including text-to-image and text-to-voice, but provides a simple drag-and-drop interface that lets users put together a video by hand, piece by piece, rather than generate a full clip with a click.
Running a generative model is like rolling dice, says Lipkowitz. “This is a hard no for most video production teams, particularly in the enterprise sector where everything must be pixel-perfect and on brand,” he says. “If the video turns out bad—maybe the characters have too many fingers, or maybe there is a company logo that is the wrong color—well, unlucky, that’s just how gen AI works.”
The solution? More data, more training, repeat. “I wish I could point to some sophisticated algorithms,” says Miao. “But no, it’s just a lot more learning.”
3. Misinformation isn’t new, but deepfakes will make it worse.
Online misinformation has been undermining our faith in the media, in institutions, and in each other for years. Some fear that adding fake video to the mix will destroy whatever pillars of shared reality we have left.
“We are replacing trust with mistrust, confusion, fear, and hate,” says Pechoucek. “Society without ground truth will degenerate.”
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