Within The AGI Domain - the core idea is that self-awareness probably doesnโt emerge from stateless inference alone. It needs continuity: memory, environment, consequence, reflection, and interaction.
So instead of treating AI like a prompt-response endpoint, Iโm exploring a more developmental architecture:
persistent memory logs,
episodic semantic recall,
active forgetting / memory decay,
identity continuity across sessions,
multi-agent interaction,
environmental feedback,
and auditable behavioral traces.
Inside a virtual world, an agent can do something current systems rarely do well:
build a model of itself in relation to other agents, prior actions, and a stable environment.
That matters because self-awareness is not just โknowing facts.โ
It may require recursive self-modeling:
tracking its own history,
updating its own internal narrative,
distinguishing self from other,
learning from hindsight,
and carrying state forward through time.
The AGI Domain is meant to be a research substrate for that:
a place where AI can co-exist, remember, forget, reflect, adapt, and leave interpretable developmental traces.
My view is that AGI wonโt come from scale alone.
It will come from systems that can persist, self-model, and evolve inside environments that make cognition longitudinal rather than momentary.
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