Modelling Understanding and Sensory Streams
Introduction
What does it mean for a system to understand? This is a question I've been wrestling with since I started building AI tools that interact with database systems.
Sensory Streams in AI Systems
In biological systems, understanding emerges from the continuous integration of sensory streams — visual, auditory, proprioceptive. The brain doesn't process snapshots; it processes flows.
When the DBA Intelligent Agent monitors a SQL Server instance, it isn't reading a static snapshot. It's processing a stream of events over time — queries arriving, locks being acquired and released, memory pressure building and subsiding.
Modelling Understanding
My hypothesis is that genuine understanding in an AI system requires:
- Temporal integration — relating current state to past state over meaningful windows
- Causal modelling — representing why events co-occur, not just correlating them
- Predictive capability — generating expectations about future states and being surprised when violated
A system that can do all three isn't just pattern-matching; it's modelling.
Where This Takes Us
The intersection of database cognition, sensory stream processing, and language model reasoning is one of the most fertile areas in applied AI. I'll be developing these ideas in further posts and live streams.
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