Applications

AI & Machine Intelligence

AI increasingly becomes an information architecture problem.

As models scale, more of the cost sits in how weights, activations, memory and context are represented and moved — not only in raw computation.

Why we are relevant

We work below the model layer. MSML represents information as multi-level structure; IDDO optimizes its density; MSML-LLMC extends this into the model-processing pathway.

How the architecture fits

One system view.

Model
Weights
Memory
Context
Accelerator
Network
Inference
MSML · IDDO · MSML-LLMC

If part of the information burden is reduced structurally, downstream compute, memory and infrastructure requirements may also be reduced.

Potential applications

Concrete environments.

Foundation modelsLLMsInferenceKV / context processingMemory movementModel distributionEdge AIMultimodal AIAI acceleratorsCloud AI

Relevant GH technology

MSMLIDDOMSML-LLMC

Pilot opportunity

What a pilot would test.

  • Model / activation representation
  • Memory & KV/context efficiency
  • Inference workload information movement
  • Model distribution to edge

Strategic relevance

For AI infrastructure companies, model developers and accelerator vendors, a structural information layer is a licensing and integration opportunity beneath the stack.

Explore Strategic Opportunities