Cognition Infrastructure
Memory, planning, perception, reasoning. The substrate that compounds beneath every embodied system.
— Experiments / Vol. I / Operations room
An operations room, not a publication. The institute's work organised into three structural layers — the engineering domains we operate inside, the active experiments in motion within them, and the field instruments being built beneath both to engineer the physical AI era through real-world conditions.
What we are running now · Engineering Domains · Active Experiments · Field Instruments
Live operations / what we are running now
A subset of the programme — the experiments currently absorbing the most field input, and the typed signals that are shifting engineering positions in real time.
The integrator gravity shift is reshaping who actually mediates operator trust. Position under revision.
Three early-draft frameworks observed. Likely to constrain operator selection by 2027 — earlier than the field models.
Integration cycles averaging 4.7 months across an 11-operator sample. Position holding; corroboration deepening.
Framework / Vol. I
An interactive five-layer framework — embodiment, perception, world model & cognition, action & control, and the learning loop — with every component clickable.
Layer A / Engineering Domains
Domains are not topics. They are operating frames — the way the institute decides what counts as an answer.
Memory, planning, perception, reasoning. The substrate that compounds beneath every embodied system.
Humanoids and embodied platforms as policy objects — geometry, dexterity, labor profile, supply chains.
Integration, certification, telemetry, retraining, recall. The unglamorous half of intelligence.
Autonomy as a strategic surface — the control hierarchies, accountability structures, and political weight of self-operating systems.
The institutional shape of knowing. What states, operators and labs actually need to perceive the field clearly.
The long-horizon trajectory: capital, governance, labor, and the metabolism of institutions inside the physical AI era.
Layer B / Active Experiments
Each experiment is a standing operational track — refined as field evidence accumulates, not republished as a new opinion every quarter. Status reflects current activity, not importance.
From credible demonstrations to ten million units per year: actuators, training data, regulation, capital intensity, and the labor profiles humanoid platforms will compete with first.
The full vertical between sensor and intent — perception, world models, memory, planning — and the deference policies that decide when a machine should yield to a human.
The legal, insurance and political architecture around autonomous systems in public space — what permits scale, what halts it, and where the breakpoints will be.
Coordinating fleets of agents in the physical world — supervision, fallback hierarchies, telemetry, and the operating discipline that decides where multi-agent autonomy is real.
The physical and political topology of where intelligence is manufactured — chips, energy, fabs, labs, capital — and the strategic positions that follow.
How states are positioning across the stack — compute, models, operators, regulation — and which configurations actually constitute sovereignty in the physical AI era.
Who runs the fleets — the new operator class for humanoid and autonomous systems, their internal structure, accountability surface, and economics.
At what speed do institutions, infrastructure, labor markets and political systems actually metabolize the substrate being built? The honest answer reshapes every other position.
Layer C / Field Instruments
Experiments compound into instruments — maps, atlases, taxonomies, doctrine systems. Released only when the underlying structure is stable enough to draw honestly. Until then, we resist the false map.
A live cartography of the institutions, capabilities and dependencies competing across the physical AI substrate — at a resolution that supports real decisions.
The full vertical of embodied cognition — perception, world models, memory, planning, deference — mapped layer by layer, with the open frontiers marked.
A structured catalogue of how physical AI systems actually fail inside real institutions — integration, regulation, trust, accountability, supervision.
Where intelligence is being manufactured — chips, energy, fabs, talent, capital — and which sovereign positions are real, which are aspirational, which are quietly lost.
The path from credible demonstration to industrial scale — actuators, supply chain, training data, regulation, operator class — held together as one decision surface.
A field manual being assembled in public: how autonomous and embodied systems should be staged, supervised, audited and retired inside real institutions.
Engage / 04
Engagements, dossier access, and instrument previews are made available to a small number of institutions operating directly on the physical AI horizon.
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