Each capability is a brick that builds upon previous ones

This lets us ensure we optimize for all design constraints & objectives

The total effect aims to be greater than the sum of each component

Evolution has developed intelligence that is efficient and works in the real world, there are lessons there to be learnt

The more we understand why biology does what it does at a systems level, the more we will understand how to build better AI systems

We also are cognizant of the fact that biology has limitations in its design & implementation, that we strive to avoid

We believe it's hard to expand an optimized system's design to include effectiveness for additional goals and constraints.

We address this by deciding on all goals and constraints for our final system, and incorporating as many as possible at each step.

We avoid preclusion at every stage for unoptimized goals & constraints, allowing easier addition down the line.