To address this, the author introduces Hivekit, a tool designed to provide the necessary rulesets and communication to enable the emergence of higher-level behaviors and self-organization. Hivekit aims to connect millions of people, vehicles, machines, and data sources, visualizing them in a 3D digital twin and providing human operators with the tools they need to control their operation. The ultimate goal is to create a distributed spatial rules engine that can process large streams of spatial and machine data, execute instructions in real-time, and send events and actions, thereby unlocking the mechanism behind higher-level self-organization and emergence.
Key takeaways:
- The article discusses the limitations of current AI systems, particularly GPTs, in addressing real-time problem solving in dynamic environments, understanding and reacting to current events or spatial reasoning and coordination in the physical world.
- It suggests looking at natural and human systems like swarms, hives, colonies, societies, free market economies, and the internet as models for creating more effective thinking systems.
- The article identifies the lack of a communicative fabric that allows for real time feedback loops as the main reason why we don't employ these systems in organizing ourselves.
- Hivekit is presented as a solution to this problem, aiming to create a mechanism that enables this fabric, provides both rulesets and communication to enable the emergence of higher level behaviours and self organization.