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Generative Synchronous Diffusion

The fourth pillar of generative AI. Every layer of a video, in one pass.

Four Pillars

Four Pillars. GSD is

the Fourth.

Each one changed what AI could make. GSD changes the complexity class.

Pillar One · Language

Attention 
Θ(N²)
 per layer

Gave us language models.

01

Pillar Two · Clips

Diffusion Transformer Θ(L·M²·N²)

Gave us today’s video models.

02

Pillar Three · Streams

State Space Model 
Θ(N)

Gave us long streams.

03

Pillar Four · Wishtales GSD

​Topological Graph World Model

O(M log N + N)

The whole video, every layer, in one pass.

04

How GSD Works

Plan Once. Render Once.

GSD understands the whole story first, then executes it.

01

02

03

Symbolic Layer

Retrieve O(M log N)

Finds every character, voice and sound the story needs in the world graph.

Combinatorial Optimisation

Optimise O(1) amortised

Locks one quasi deterministic blueprint. Every sync decision, made once.

Combinatorial Optimisation

Render O(N) 

Six layers from one shared state, in a single linear pass.

“Synchronisation is a property of the architecture, not a correction applied to the output.”

120s+

One shot, 154 s demonstrated

≈240 s

To render 120 s of six layer 4K

≈67x

Realised inference efficiency

Zero

Denoising steps

Measured on NVIDIA Blackwell B300.

Topological Identity

Shape, Not Coordinates.

One signature holds identity across every modality, every scene and every edit.

98.99%

Prompt to physics adherence

Prompt constraint adherence

98.89%

Across 10,000 outputs, measured on NVIDIA Blackwell B300.

Giga Papaya

Editing to the Second.

Only the chosen layer re renders, for only the chosen seconds.

Benchmarks

Five Numbers That Define the Gap.

Version 2026 evaluation against the commercial frontier.

29 of 39

Benchmark categories led

Safe by Construction

Harmful concepts are left out of the world graph, so they cannot be generated.

Governed for Enterprise

Brand rules and prohibited concepts are enforced inside the graph, as the video is made.

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