Netflix has confirmed that it used generative AI for the first time to create a scene in one of its original shows. Netflix co-CEO Ted Sarandos described the technology as an “incredible opportunity to help creators make films and series better, not just cheaper.”
Sarandos said everyone involved with the project was “thrilled” with the result generated by AI. Since generative AI gained prominence in late 2022, there has been significant anxiety across industries about its impact on jobs, with creative fields expected to be among the most affected. In 2023, a Hollywood actors and writers strike led to new guidelines around the use of AI in productions.
Speaking to analysts during Netflix’s quarterly earnings call, Sarandos said, “In fact, that VFX sequence was completed 10 times faster than it could have been completed with traditional VFX tools and workflows.”
“The creators were thrilled with the result. We were thrilled with the result,” Sarandos added. “And more importantly, the audience was thrilled with the result. So, I think these tools are helping creators expand the possibilities of storytelling on screen, and that is endlessly exciting.”
AI was used in the Argentine science-fiction series El Eternauta (The Eternaut) to create a scene showing a collapsing building in Buenos Aires. While creating the scene would have been beyond the project’s budget, the creators partnered with Netflix’s product innovation group, Eyeline Studios, to generate the dramatic scene using AI.
Netflix co-CEO Greg Peters also noted that the company could use generative AI to improve user experience, including enabling users to find content through natural language queries.
“Saying, ‘I want to watch a film from the ’80s that’s a dark psychological thriller,’ and getting some results back … you just couldn’t have done in our previous experiences,” Peters said.
He also gave the example of advertising as another area where generative AI could mark a major opportunity for brands and marketers to create compelling content.
“We think these generative techniques can decrease that hurdle iteratively over time and enable us to do that in more and more spots,” Peters added.
