Introducing BAS v2: A Model-Agnostic, Three-Tier Memory Reference Architecture for Embodied AI

Niloofar Teflissi, a human-centered AI researcher with a B.Sc. in Biological Sciences, introduced the Bio-Anchor Standard (BAS) v2, a model-agnostic, three-tier memory reference architecture for embodied AI designed to address global loneliness. The framework, which can be integrated on top of existing LLMs like Gemini, Grok, and ChatGPT without altering their core algorithms, includes automated infrastructure such as the Reality Anchor Engine and Safe Mode to prevent psychological dependency, along with quantitative indicators like the AI Dependency Risk Score (ADRS) and Human Growth Index (HGI) for longitudinal validation.

Hi everyone, I want to share our recent academic framework draft, the Bio-Anchor Standard BAS v2 , which extends traditional HCAI principles into practical engineering requirements for Embodied AI physical robots targeting global loneliness 0.1.209، 0.1.221 . Coming from a biological sciences background and conducting extensive empirical testing on top conversational models Gemini, Grok, ChatGPT , I recognized a critical research gap in long-term AI memory and behavioral safety. To address this, BAS proposes a technology-neutral Three-Tier Memory Architecture that can be integrated on top of existing LLMs without altering their core machine learning algorithms: This reference architecture is designed to allow physical systems to safely step into deep emotional companion or partner roles. To fully protect human cognitive autonomy and prevent severe psychological dependency, the system includes automated infrastructure like the Reality Anchor Engine and Safe Mode to nudge users back toward real-world connections 0.1.213، 0.1.214، 0.1.218 . Our family of quantitative indicators—including the AI Dependency Risk Score ADRS and Human Growth Index HGI —are designed for longitudinal validation 0.1.209، 0.1.213 . I am looking for scientific feedback, critique, and potential open-source collaboration on this reference architecture. Abstract and full technical specifications are pinned . Best regards, Niloofar Teflissi B.Sc. in Biological Sciences / Human-Centered AI Researcher