HomeArtificial IntelligenceThe creators of Sora-powered short movies explain the strengths and limitations of...

The creators of Sora-powered short movies explain the strengths and limitations of AI-generated videos

OpenAI's video generation tool Sora surprised the AI ​​community in February with smooth, realistic videos that seem like miles ahead of the competition. But the fastidiously directed debut not noted a number of details – details that were filled in by a filmmaker who had early access to create a brief film starring Sora.

Shy Kids is a Toronto-based digital production team chosen as one in all a couple of by OpenAI Producing short movies essentially for OpenAI promotional purposes, although they got significant creative freedom within the creation of “Airhead”. In one (n Interview with visual effects news agency fxguidePost-production artist Patrick Cederberg described “actually using Sora” as a part of his work.

Perhaps an important takeaway for many is solely this: while OpenAI's post highlighting the shorts leads the reader to assume that they’re kind of entirely derived from Sora, in point of fact they’re skilled productions, complete with in-depth storyboarding, editing, color correction, and post-production similar to rotoscoping and VFX. Just as Apple says “Shot on iPhone” but doesn't show the studio setup, skilled lighting, and color work after the very fact, the Sora post is all about what people can do with it, not how they really do it have made.

Cederberg's interview is interesting and fairly non-technical, so when you're in any respect interested, Go to fxguide and skim it. But listed below are some interesting details about Sora's use that show us that, as impressive because the model is, it's perhaps less of an enormous breakthrough than we thought.

At this time limit, control continues to be essentially the most desirable and at the identical time essentially the most elusive thing. …The best we could do was be overly descriptive in our prompts. Explaining the characters' wardrobe in addition to the form of balloon was our approach to get across the consistency, since from shot to shot / generation to generation the features that allow full control over consistency usually are not yet in place.

In other words, things which might be easy in traditional filmmaking, like selecting the colour of a personality's clothing, require complex workarounds and checks in a generative system because each shot is created independently of the others. That could after all change, but in the mean time it’s definitely rather more complex.

Sora's output also needed to be monitored for unwanted elements: Cederberg described how the model would normally create a face on the balloon the primary character has for a head, or a string hanging down the front. These needed to be removed by mail, one other time-consuming process unless asked to exclude them.

Precise timing and movements of the characters or the camera aren't really possible: “There's a bit of little bit of temporal control over where these different actions happen within the actual generation, nevertheless it's not precise… it's type of a shot at midnight,” said he Cederberg.

For example, unlike manual animations, the timing of a gesture like a wave is a really approximate, suggestion-driven process. And a shot like a pan as much as the character's body may or may not reflect the filmmaker's wishes – so on this case, the team rendered a shot in portrait format and did a crop pan in post-production. The generated clips also often ran in slow motion for no particular reason.

Example of a shot because it got here from Sora and the way it ended up within the short film. Photo credit: Shy children

In fact, using on a regular basis filmmaking language like “pan to the correct” or “tracking shot” was generally inconsistent, Cederberg said, which the team found quite surprising.

“The researchers hadn’t really thought like filmmakers before reaching out to artists to experiment with the tool,” he said.

As a result, the team performed tons of of generations of 10 to twenty seconds each and ended up using only a handful. Cederberg estimated the ratio at 300:1 – but after all we'd probably all be surprised on the ratio in a traditional shoot.

Actually the team I made a bit of video behind the scenes If you're curious, we'll explain a few of the problems they encountered. How much AI-related content The comments are quite critical of your entire endeavor – although not quite as insulting because the AI-powered ad we recently saw pilloried.

The final interesting wrinkle concerns copyright: when you ask Sora to offer you a Star Wars clip, he’ll refuse. And when you attempt to bypass it with “man in robe and lightsaber on a retrofuturistic spaceship” it’ll also refuse because there may be a mechanism during which it detects what you are attempting to do. It also refused to do an “Aronofsky-esque shot” or a “Hitchcock zoom.”

On the one hand, it makes perfect sense. But it begs the query: If Sora knows what that’s, does that mean the model was trained on that content to raised detect that it's a violation? OpenAI, which keeps its training data cards near the vest – to the purpose of absurdity, as in Interview by CTO Mira Murati with Joanna Stern – will almost definitely never tell us.

As for Sora and his use in filmmaking, it's clearly a robust and great tool in his place, but his job isn't to “make movies out of nothing.” Still. As one other villain once said, “That comes later.”


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