01
Foundation
Ecosystem, compute, runtime, and model-building foundations.
AI Learning System
Learn AI. Put it to work.
Explore how AI systems work through research, applications, and hands-on experiments. Follow five connected layers from compute and models to agents, deployment, and physical AI. Connect ideas, test what you learn, and use it to build your next project.
02
Agent system
Harness and context layers that turn model capability into an operating system.
03
Assurance
Security and evaluation contracts for bounded, reviewable behavior.
04
Deployment
Local and cloud decisions grounded in workload, control, and cost.
05
Physical AI
World models, swarm research, and the ANT / BEE colony experiments inform digital twins and embodied engineering.
wfmWorld Models Atlas opens in a new tabswiSWI — Swarm Intelligence opens in a new tabantANT — Ant Colony Intelligence Laboratory opens in a new tabbeeBEE — Honey Bee Collective Intelligence Laboratory opens in a new tabitlIndustrial Twin Lab opens in a new tabengOpen Humanoid Engineering opens in a new tab
AI Learning System · connected paths
How the system connects.
Each application explores a different part of building AI. The diagram connects them into a learning loop: understand compute and models, build agent systems, and test how they behave. Compare local and cloud deployment, then explore world models, swarm intelligence, and colony experiments. These paths inform digital twins and the longer-term goal of open humanoid engineering. Each experiment brings new questions and lessons back to the starting point.
Learning system · animated overview
AI Learning System in motion
An earlier overview of the learning loop; the current SWI, ANT, and BEE branches appear in the diagram and the Journey page’s laboratory cards. Each card morphs into the shape that names it: AIA becomes a network, GPU a silicon die, LLM flowing tokens, HNS a hexagon, CTX brackets, SEC a shield, EVL a scale, LCL a local home, CLD a cloud, WFM a globe, ITL twin panels, ENG a humanoid.