Research
Computation is the last unmodeled environment. We are building the model.
AI has models of the physical world. Of language, of code, of proteins, of weather. It has no model of the computational world it runs in.
That is the environment every model lives inside.
We are modeling it. The science is Heterogeneous Compute Physics.
What happens if this workload moves there, now?
ObserveWorkload shape, queue, device state, and concurrent demand.
PredictLikely latency, throughput, memory pressure, and uncertainty for feasible targets.
CheckIndependent limits rule out unsafe actions before any recommendation or canary.
Compute World Models
A Compute World Model is a learned simulator of a compute environment. It answers the question no system can answer today: what happens if this work moves there, now?
Language models learn from what people wrote. Compute World Models learn from what machines do. The exhaust of the entire computing world, which nobody has assembled, and which is sitting there.
A benchmark describes a machine at rest. A Compute World Model predicts a machine under load.
Compute Intelligence
Spatial intelligence is the ability to reason about the physical world. Every person has it.
Compute Intelligence is the ability to reason about computational environments. It is rare, takes years to acquire, is mostly tacit, and does not transfer easily.
That is why a chip is only as useful as the team available to operate it. It is why the scarcest resource in AI is not silicon and not energy, but the few people who know what silicon will do.
Compute Intelligence gives machines a faculty almost nobody has, and gives it to everyone.
Placement before profiling
You profile a machine. Then you schedule on it. Characterization first, policy second, for as long as computers have been scheduled.
That order is the bottleneck. It slows the path from a new accelerator to useful production work.
We are removing the first step.
Placement and measurement are the same act. You learn the machine by using it, and the cost of knowledge is paid in work the machine was going to do anyway.
The federation
Humanity has been measuring computers for seventy years and has almost no shared record of what they do.
We are building one.
The schema is open. Anyone who runs it produces a profile, with provenance, contributed to a public index. Profiles are contested, corrected, superseded.
The corpus a Compute World Model needs is exactly the corpus the federation produces. The openness and the capability are the same project.
We hold no privileged position in it. A record whose keeper scores itself is the problem it was built to solve.
Heterogeneous Compute Physics
The structure of computation shapes the space of possible algorithms. When hardware was uniform, computation could be abstracted. When hardware is heterogeneous, computation becomes an object of scientific study.
Every abstraction in computing was built to hide the machine. Assembly hid the instruction set. Virtual memory hid the address space. Threads hid the core count. Each leaked exactly where performance mattered.
The reflex is to hide a new difference behind another layer. Building a second target does not undo fragmentation. It is fragmentation.
We do the opposite. We model the differences and make them legible to a system that can act on them.
That is a science, not a product. We publish what we find, and the problems we cannot solve so others can take them.