Organisms and consciousness
How living systems determine what matters when action cannot wait for complete information.
Explore consciousness research →Arik Shimansky
My work ranges from consciousness and artificial cognition to institutions, markets and emerging technologies.
The recurring interest is how systems recognise what matters, respond to change and create possibilities when the future is not yet obvious.

One problem, several domains
How living systems determine what matters when action cannot wait for complete information.
Explore consciousness research →How artificial systems might maintain memory, context, goals, attention and continuity rather than reconstructing themselves with every interaction.
Explore artificial systems →How people, organisations, markets and institutions respond when events or technologies change faster than their existing models.
Visit Synaptic Quanta →Current work
A theory of consciousness based on temporal constraint: what happens when an organism must evaluate the significance of a situation before the underlying information can be fully resolved.
↗A persistent layer between a person and interchangeable AI models or applications, designed to preserve context, goals and continuity over time.
↗An experimental personal AI architecture combining memory, provenance, goals, attention, metacognition and persistent internal state.
↗An exploratory model of how increasingly integrated forms of self may emerge from nested biological and regulatory boundaries.
↗Synaptic Quanta is a commercial practice for consequential situations that cross conventional boundaries, turning insight into strategy, transactions, ventures or systems.
↗An evolving research programme
An early attempt to connect physical mechanisms, predictive processing, affect and evolutionary delay. Presented at The Science of Consciousness, Taormina.
A testable account of why organisms may need to evaluate survival significance before sensory information is fully resolved.
Official conference abstract →Background
My background spans mathematics and physics, institutional finance, investment, technology ventures, climate systems and AI. The domains changed, but the work repeatedly involved the same kind of problem: understanding unfamiliar systems, connecting incomplete information and deciding what matters before the situation becomes obvious.