CoreWeave is replacing Hollywood’s render farms with AI-native data engines that turn every frame into a dataset.
In the relentless churn of Hollywood’s digital revolution, the real star isn’t the latest algorithm or even the AI model du jour—it’s the infrastructure quietly orchestrating it all.
Mac Moore, former CEO of Conductor Technologies, now head of Media & Entertainment at CoreWeave, made that clear during his GTC 2025 presentation, where he dissected how AI isn’t just reshaping visual effects but is fundamentally dismantling and re-architecting the industry’s computational backbone.
"You look at visual effects, and you look at what we have done in visual effects for the last 20 years," Moore said. "We’ve built this repository of data… all of that data can then be applied to what is artificial intelligence and its impact."
It’s that deep well of past projects--render farms full of terabytes of dinosaur bones and sci-fi cityscapes--that’s feeding AI models now. But Moore’s real point is that while AI tools are getting the limelight, the hidden layer making it all possible is the infrastructure, the vast and still largely invisible layer that every major studio is now scrambling to modernize or, in many cases, outright replace.
Because here’s the thing: In the Hollywood of tomorrow, every creative decision is ultimately a data call.
From Jurassic Park’s T-Rex to Pixar’s first CG sequences to Avatar’s uncanny-valley blue-skinned giants, the pipeline has always been a monster, devouring hours of render time, hours of human labor, and racks upon racks of servers chugging away like steampunk machinery under the floorboards.
"What you’re hitting is this sort of limiting factor of what is available from a compute standpoint on-premises," Moore said.
The inflection point now isn’t about generating photorealistic VFX, it’s about how quickly that data can be fed through models, trained on terabytes of historical assets, and turned into production-ready content on demand.
Enter CoreWeave. The Conductor Technologies acquisition wasn’t just about bolstering M&E pipelines—it was a strategic play to rewire how studios think about data, AI, and creative throughput. "Imagine a small studio that needs zero compute requirements one week and they need a Disney-size render farm the next week," Moore explained. "Now imagine doing that without ever touching a physical server."
And the pitch is simple: a dynamically reconfigurable architecture where every component—compute, storage, training models—scales independently but operates as a unified system, orchestrated through CoreWeave’s Kubernetes-driven control plane.
But it’s the next phase that really matters. "Think of cloud computing as that single source of truth," Moore said, leaning hard into the MovieLabs 2030 vision, a fully cloud-native M&E landscape. This source is "where studios go into the assets, they work on those assets, they publish those assets to the IP providers, and then they pull those down."
This isn’t just about rendering. It’s about turning every asset into a queryable dataset.
Imagine an ecosystem where assets aren’t locked in proprietary formats but exist as structured data streams, accessible to AI models in real time.
Moore breaks it down: "You have chat, GPT X today, you have X dot five tomorrow." This relentless iteration cycle is creating a demand for infrastructure that isn’t just powerful but elastic, scalable, and modular to the point of being instantly reconfigurable. The render farm, as it exists now, is a bottleneck. The new pipeline is a living, breathing database where AI models train on what the studio has already created, producing new assets that flow directly into production without ever being ‘rendered’ in the traditional sense.
"Imagine running a number of high-volume renders and then wanting to take that data that’s in storage and then run training and inference models against that," Moore added.
Here’s the subtext: It’s not about scaling up and down compute; it’s about dynamically reallocating resources in response to AI’s relentless appetite for data.
The studio of the future, as Moore envisions it, is less a collection of discrete workstations and more a fluid, AI-native pipeline where every frame, every digital double, every storyboard is a dataset waiting to be processed.
And it’s not just about production. CoreWeave’s infrastructure vision extends to the entire M&E lifecycle—archiving, upscaling, dubbing, even character creation.
Moore dropped a particularly interesting nugget here: "Imagine giving your director a photo-real likeness of your inspired jungle scene in a storyboarding application," he said. What he's pointing to here are text-to-image models plugged directly into proprietary IP datasets (actor faces, digital doubles, full asset libraries) all accessible through simple text prompts.
"There’s a general theory that there is not enough resource in this industry to make all of the films that are currently slated today," Moore added.
The implication? The render farm, as a concept, is dead. The pipeline of the future is an AI model--a colossal, self-sustaining dataset that eats assets, spits out scenes, and loops every creative decision back through the inference engine until there is no difference between what was rendered and what was generated.
And the applications aren’t just theoretical. Moore highlighted examples from Wonder Dynamics, where AI-driven motion capture effectively eliminates the need for bubble suits.
"What you saw in that clip is they’ve actually gone where AI is inferring the motion of the actor themselves," he said. "That saves weeks, again, weeks or months of work through artificial intelligence."
AI isn’t just speeding up film workflows. It’s erasing entire steps.
Or consider AI upscaling. "Think of being able to take your archive of 1k footage and upscale automatically to 4k without needing to rework any of those components," Moore said. The potential here is enormous: billions of dollars’ worth of back-catalog assets that can now be digitally remastered, enhanced, and fed into new workflows without a single human touching the frames.
But it’s not just content creation that’s getting the AI treatment. Moore outlined a future where every asset is more than a file—it’s a node in a real-time pipeline:
"Imagine running a set of renders, then applying machine learning inference to identify which assets have the highest reuse potential across projects," Moore said. "Imagine that data being instantly available to the AI model running on the same infrastructure, without moving a single file."
This is where CoreWeave’s control plane becomes the pivot point: a unified orchestration layer that can dynamically reallocate GPU cycles to whatever phase of production needs them—rendering, inference, data prep—all while continuously ingesting and indexing new assets.
"We built a foundational piece of cloud," Moore said. "A control plane that can handle not just the compute but the entire asset lifecycle, from generation to production to archival to training."
The only way to scale is to build an infrastructure that not only handles today’s workflows but anticipates tomorrow’s AI-generated deluge...a landscape where the cloud is less a destination and more a continuous, omnipresent layer, feeding models, refining assets, and orchestrating entire productions in real time.
In other words, forget the render farm. Forget the traditional pipeline.
The new pipeline is an AI model, a massive, self-sustaining dataset that eats assets, spits out scenes, and loops every creative decision back through the inference engine until the idea of ‘rendering’ is as archaic as cutting film on a Steenbeck.
That’s the real play CoreWeave is making, and it’s not just about selling GPU cycles. It’s about building the operating layer for the entire entertainment industry’s next act—a continuous, always-on flow of assets and data, where the infrastructure doesn’t just support creativity—it defines it.