At a Shanghai forum, industry leaders identified compute power, controllable AI, and distribution models as key challenges for Chinese filmmaking in the AI era. They discussed the need for large-scale computing infrastructure for high-fidelity generative video models, the commercialization conflict arising from limitless content production, and the demand for more obedient AI that precisely executes directors' nuanced creative visions. Panelists also expressed optimism regarding job displacement concerns.
Chinese Film Industry Sees Compute Power , Directable AI and Distribution as Key Hurdles in Next Wave of Filmmaking, Shanghai Forum Finds. Those are the key challenges facing the Chinese film industry when it comes to AI, according to speakers at the'The Paper' Star Domhnall Gleeson on Becoming a Folk Hero for Journalists — and the 'Sad Aspect to It' Alessandro Nivola on Playing Calvin Klein in 'Love Story' and the Todd Haynes Movie He Says Could've Won Michelle Williams an Oscar “For a generative video model to achieve greater fidelity, what you really need is greater computing power to repeatedly refine and experiment,” said Yan.
“The more you experiment, the better to train certain aspects more effectively. Large scale compute infrastructure is critical for every model iteration. ”For other panellists, the problem lies in figuring out a distribution model that works in a world of seemingly limitless production. When full length epic fantasy films can be shot and completed in a matter of days, how will the industry deal with such a deluge of content?
“This is a genuine conflict. From the commercial perspective, it is the contradiction of redefining product value,” said Li Tingwei of Bauhinia Films.
“For commercial studios, one aspect is creation. then there is also distribution, how to sell it? Which also brings challenges. ”“One point is that the AI creators need is actually not just a more powerful AI, but a more obedient AI. A director has a very complete cinematic vision in mind, but the AI often presents something unexpected,” said Nina Zheng, deputy general manager of ASUS China.
“Filmmakers want a very specific emotion, a very particular change in lighting, something very subtle and highly personal in terms of aesthetic judgment. But when these directions are executed by AI, it often fails to get there in one step, requiring frequent adjustments. ” In respect of job losses due to AI, however, panellists seem to be contrarily upbeat.
With the wholesale changes in filmmaking workflow, new jobs and titles have emerged across the entire industry, such as AI directing assistants who specialise in AI prompt engineering.
“We can feel from this that the more advanced the tools become, the more critical the people driving the tools become,” said Zheng. This sense was echoed by Huang Jianxin, the only film director on the panel, and Dean of the School of Film at Xiamen University. He contended that, unlike other industries, filmmaking consists of numerous edge cases, making it hard to automate every aspect.
“The two largest tea factories in China have replaced their 2,000 personnel with 120 people and AI, and the quality of the tea, safety, consistency, and packaging accuracy have all improved significantly. AI rules, when standard processes are the norm,” said Huang.
“Artistic creation , is individualistic and naturally excludes certainty. Therefore, a clash between artists and AI is the most natural thing possible. ”“AI is intimately connected to cinema, because cinema was born out of technology. Theatre, poetry, dance are originating arts.
Cinema is the synthesis of all these arts, though the medium of technology.
“99% of people couldn’t participate in cinema because it required money. The right for everyone to participate in this art was stripped away. This is why so many young people love AI now. It is an equalizer.
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