LOS ANGELES, July 17 (Reuters) - Netflix ( NFLX ) said

on Thursday that it used generative artificial intelligence to

produce visual effects that appeared for the first time on

screen in one of its original series, employing a technology

that has been a source of anxiety throughout Hollywood.

Co-CEO Ted Sarandos hailed AI as "an incredible opportunity

to help creators make films and series better, not just

cheaper."

Sarandos offered the example of Argentine science-fiction

series "El Eternauta (The Eternaut)," where the creators wanted

to show a building collapsing in Buenos Aires - a visual effect

that would have been beyond the project's budget. The creative

team partnered with Eyeline Studios, a production innovation

group within Netflix ( NFLX ), to make the dramatic scene with the aid of

AI.

"That VFX sequence was completed 10 times faster than it could

have been completed with visual traditional VFX tools and

workflows," Sarandos said during the company's second-quarter

investor call. "And also the cost of it would just wouldn't have

been feasible for a show in that budget."

Sarandos said the sequence is the first GenAI final footage

to appear on screen in a Netflix ( NFLX ) original series or film,would

just wouldn'tlestone.

AI has become a flashpoint in Hollywood since the labor

unrest of 2023, which resulted in new guidelines for the use of

the technology. The main concern is that AI could replace the

work of humans.

Co-CEO Greg Peters said Netflix ( NFLX ) may find other ways to

leverage generative AI to improve the user experience -

including offering viewers the ability to use spoken words to

find something to watch.

"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," said

Peters. "So that's super-exciting."

Advertising represents another opportunity for generative

AI, Peters said, as brands and marketers seek 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," said Peters.