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.
If part of the information burden is reduced structurally, downstream compute, memory and infrastructure requirements may also be reduced.
Potential applications
Concrete environments.
Relevant GH technology
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.
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