Open Autonomous intelligence initiative
Download the Axiomatic Ontology (AO) Foundation paperDownload the AO Research Program paper
Download the AO Matter Reconstruction Pass 1 Analysis paper
Open Autonomous Intelligence Initiative
Open object-oriented models for accountable AuI
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Checking Keys and Phone Placement After Returning Home
Misplacing keys or a phone can add unnecessary stress for people aging in place. This post explores a simple, ethical, and edge-primary autonomous intelligence use case: gently checking whether essential items are placed in a designated spot after returning home. It explains affordable devices, how the capability fits into the OAII / Open SGI model,…
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EdgePERSignal
PERSignal defines the minimal OAII‑conformant Signal subclass required to carry edge‑primary sensor observations into the Personal Event Recognition (PER) pipeline.
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Why Autonomous Intelligence Needs Open Standards
Autonomous Intelligence systems don’t just analyze data — they observe, decide, and act in the real world. As these systems move into our homes, cities, and care environments, open standards for interoperability, governability, and accountability become essential. This post introduces OAII’s advocacy series explaining why open, object-oriented models are the foundation of trustworthy, human-centered autonomy.
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EdgePERSensor
Purpose EdgePERSensor defines the minimal OAII-conformant Sensor subclass required for edge-primary Personal Event Recognition (PER) for aging in place. EdgePERSensor is designed to: bind a concrete sensing capability to an EdgePERDevice produce PERSignal instances suitable for Subject–Object and PrimaryUser interpretation support conservative operation under uncertain conditions expose policy-aware capture and summarization behaviors EdgePERSensor is intentionally…
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EdgePERDevice
EdgePERDevice defines the minimal OAII-conformant Device subclass required to support edge-primary Personal Event Recognition (PER) for aging in place.
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Modeled Use Cases Enabled by the Open SGI MVM
This post introduces the concrete, real‑world use cases that can be modeled using the Open SGI Minimum Viable Model (MVM) for edge‑primary Personal Event Recognition (PER) in the context of aging in place.
