AI-produced films appear to be the most common feature on every corner of the online space these days. Whip out your electronic device, open your favorite social media app and you’re likely to come across a somewhat startling video of a synthetic natural catastrophe, or creatures performing unreal tasks. It’s unsurprising that the common belief among supporters of this emergent technology is that AI-generated films are the next frontier in cinema, posing a significant challenge to Hollywood’s traditional moviemaking. However, the probability of established studios readily adopting this tech at its current stage seems questionable, considering AI-produced content often lacks the requisite quality to produce a top-grade movie or series.
The distinct competitive advantage of Asteria is that, unlike its AI peers, it boasts an ethically fashioned generative model built in collaboration with research organization Moonvalley. This model’s uniqueness lies in its training exclusively on properly licensed source material. Looking at recent legal complications, such as the copyright lawsuit levied by Disney and Universal against Midjourney, Asteria’s ethical approach to AI generations is a timely response that could significantly influence the future adoption of AI within the entertainment industry.
The foundational vision for Asteria was clear for us as filmmakers – we recognized that the representation of AI in Hollywood carried significant hurdles. The core generative model, Marey, developed by Asteria offers a solution, providing filmmakers with advanced power and control. It accomplishes this through the creation of unique, project-specific models trained on original visual elements.
This exceptional framework would enable a creative professional, for instance, to develop a unique model capable of generating a diverse range of assets in their proprietary style. These assets can be used to populate an imaginative universe filled with distinct characters and objects that radiate a unique visual appeal. The financial agreement between Asteria and its client directors may also provide an opportunity for the latter to retain part-ownership of the resulting AI models.
As a testament to its commitment to the creators, not only does Asteria ensure they are rightfully compensated through original license fees for training its central model, but the AI firm is also contemplating the concept of a profit-sharing system. Despite that, Asteria is more inclined towards enticing artists with the prospects of reduced initial development and production expenses.
Similar to its other proponents in the AI camp, Asteria views this technology as a tool for democratization, which may potentially make art creation more attainable for all. Another major advantage emphasized by the firm is the faster turnaround time for finished products that the AI can offer, even with limited manpower.
This feature of an AI-centered production process would enable the writers and directors to interact more effectively with vital collaborators, such as the art and VFX supervisors, reducing the time usually spent on multiple revisions. However, the issue of downsizing staff due to AI streamlining raises important questions about job loss and its social implications.
What does all this mean in regard of imminent progress? Mooser is aware of the weight of his response. He is optimistic and vocal about the benefits, but the real test lies in demonstrating how his technology—and the transformative changes it brings along— can be put to efficient and effective use.