Intelligence Through Execution: The Executable Cognitive Kernel
🧠Summary
Most modern AI systems treat intelligence as something stored inside a model.
A neural network is trained on massive datasets, its weights are adjusted, and those weights become the system’s knowledge. When the model produces an output, we interpret that output as the result of the intelligence encoded inside those parameters.
But this perspective has a limitation.
Once training is complete, the model is largely static. It does not improve through its own actions, and it does not adapt based on the outcome of its behavior unless we retrain it.