Hello! I'm your financial and business news analyst friend. Today's news discusses a significant change that's currently underway: AI is transforming the process of making movies from a labor-intensive task to something that can be accomplished through computer-generated imagery. This transformation is reshaping the entire film industry in terms of how money is made, how people work, and who holds the power.
To help you understand this better, I'll first summarize the key points of the article, and then we'll break it down into five aspects for a more in-depth analysis.
📝 Summary of Key Points
The article highlights how AI in film and television (AIGC) is moving from being a niche experiment in the tech world to becoming a core component of the mainstream industry:
1. Official Recognition: Top awards such as the Golden Rooster and Hundred Flowers Film Festival have begun to include dedicated AI categories, with strict criteria for the amount of AI used and technical verification, indicating that AI films have officially gained a place in the industry.
2. Production Revolution: Traditional film teams, which used to require hundreds of people and expensive sets, can now complete production with just a dozen people using prompts and models on computers. The production cycle has been reduced from years to months, and costs have significantly decreased, although the core aesthetic and storytelling still rely on human expertise.
3. Changing Investment Logic: Investors used to wait until the final film was completed before investing, but now directors can use AI to create high-quality trailers, allowing them to see the final product in advance and reducing the risk of failure. However, this also brings the risk of technological obsolescence, as models are updated quickly and old materials may become obsolete.
4. Lowered Barriers but Still Hidden Hurdles: While the technical barriers have decreased, new ones have emerged. Platforms like iQiyi and Tencent are directly investing in AI films, holding IP and traffic. Pure technology teams that don't understand the film industry standards struggle to survive on their own and must collaborate with traditional film teams.
5. Future Landscape: The winners in the future won't be those who just provide tools; it will be the platforms that control IP, capital, and distribution channels. A new division of labor will emerge, with model companies providing the productivity, platforms managing IP and funding, and traditional film companies handling the professional production and distribution.
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🔍 In-Depth Analysis: Five Aspects to Understand the New World of AI in Film and Television
1. Have Film Sets Disappeared? No, They've Just Been Replaced by Computer Modeling
Plain Language: Making movies used to be like building a house: you needed to rent land, buy props, hire actors, and wait for good weather. Once production started, money was continuously spent, and any mistakes (like actors being late or bad weather) could slow down the entire process.
Now, AI has replaced the “building” with “computer modeling”:
- Fewer People: A traditional film team might have needed a hundred people; now, a core production team of about ten people can work on computers, giving instructions to AI to generate images.
- Changed Process: Instead of shooting first and then editing, the process is now “design first, generate later.” Directors can use AI to create preliminary 3D sketches, determine the camera angles and character placements, and then have AI add the details.
- Key Point: Although machines can produce a lot of images quickly, whether they look good and the story makes sense still depends on human judgment. Skilled individuals who understand art, storytelling, and AI are in high demand.
2. Investment is No Longer a “Blind Box”; Be Cautious About “Shelf Life”
Plain Language: Investors used to invest in movies like buying a blind box—money was invested, actors were hired, and sets were built, but if the movie turned out to be bad or the visuals were ugly, the investment was lost. Therefore, they only dared to invest in big IPs and stars as a safer option.
Now, AI gives investors a preview:
- Test the Waters: Directors can use AI to create a low-cost prototype of the film. Investors can see this “high-definition trailer” and decide whether to invest further, reducing risk.
- New Risk: Technological Obsolescence: AI models are updated rapidly. If a project takes too long (more than two months), the previously created material may become outdated and need to be redone.
- Conclusion: Speed is crucial in AI film and television. The era of slow, meticulous production is over; now, it's about rapid iteration and verification.
3. Barriers Are Lowered, but Hidden Hurdles Remain
Plain Language: Many think that with AI, anyone can make movies. Indeed, small teams that couldn't afford to make films before can now do so. However, being able to make a film is different from being able to sell it.
- Platforms Getting Involved: Platforms like iQiyi, Tencent, and Mango TV are no longer just waiting for films to be submitted; they are actively investing in AI films. For example, iQiyi requires AI films to be over 60 minutes long and offers substantial rewards.
- Hidden Barriers: Although the technical barriers have decreased, there are still professional ones. Platform executives clearly state that most AI creators are still reaping the benefits of technology but haven’t reached the film industry standards.
- If you're just a tech expert who knows how to adjust parameters or write prompts, it's difficult to get funding for a full-length film on your own.
- Successful projects often involve a combination of AI teams and traditional directors/producers, with AI teams handling the imagery and materials, and traditional teams managing the story and production.
- **The “AI Foxconn Phenomenon”: There will be a lot of low-quality content produced massively using AI, similar to how Foxconn produces products. However, only the truly exceptional works that can make it to theaters and win awards will stand out.
4. Who's Going to Share the Profits? New Roles Are Emerging
Plain Language: Technological revolutions always involve a redistribution of profits. Just as digital cameras replaced film, but Kodak went bankrupt while Adobe (image editing software) and Apple (smartphones) thrived.
In the era of AI in film and television, the new roles are:
- Model Companies (like Keling and Jimeng): They provide the technology to generate images. While they're powerful, if they only sell the tools, they may not get the majority of the film's profits.
- Internet Platforms (like Tomato Novel, iQiyi, Tencent): They hold IP, funds, and user traffic. They are now directly involved in film production, using their IP to collaborate with AI teams.
- Traditional Film Companies: They are the “professional craftsmen.” They understand censorship, distribution, and how to get films to audiences. Although their production methods are changing, they still play an irreplaceable role in the final stage of film delivery.
- Future Landscape: Model companies provide the productivity, platforms manage IP and funding, and traditional companies handle professional production and distribution. Those who control IP and have the distribution channels will get the biggest share of the profits.
5. The “Premium Paradox”: Will Audiences Pay More for AI?
Plain Language: This is a practical question. Does AI reduce production costs and lower barriers, making people more willing to watch AI-made films?
- Audience Psychology: Audiences buy tickets for a good story, not because the film was made with AI.
- Premium Paradox:
- On one hand, lower costs mean more diverse content; small teams can now produce fantasy and science fiction films that were previously out of reach.
- On the other hand, audiences are unlikely to pay more just because a film is made with AI. If the AI is too noticeable (e.g., with unnatural movements or expressions), it may even turn them off.
- Conclusion: AI is a tool, not a selling point. If AI is only used to save costs, it will likely result in low-budget online films. Only if AI can create visually stunning effects (like those in “Avatar”) can it lead to successful theatrical releases.
- Future Competition: The focus will be on who can use AI to tell the most compelling stories.
💡 Lessons for Everyone
1. For Creators: If you only know how to code or adjust parameters, your value is declining. You need to develop skills in film language, storytelling, and aesthetics. Becoming a “director who understands technology” or a “technology expert who understands directing” is the way forward.
2. For Investors: Don't blindly invest in all AI film projects. Check if the team has a traditional film background and the ability to iterate quickly. Be wary of projects with long cycles that rely on a single model.
3. For Audiences: You'll see more uniquely styled AI films in the future. Don't reject them, but don't be overly skeptical either. The standards for good films remain the same; it's just the tools used that have changed.
In summary, AI hasn't killed the film industry; it has broken the physical limitations of production and shifted the competition to creativity and capital. This is a new gold rush, but the real value lies in the stories being told.