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From Mainframes to Mesh
- The concept of Artificial General Intelligence (AGI) has long captured imaginations, but machines are not becoming conscious entities; rather, they are sophisticated tools for offloading cognitive tasks.
- Intelligence is not consciousness, and computation is not cognition; AI systems are best understood as cognitive infrastructure aiding in navigating complexity, not as emergent minds.
- From mainframes to mesh architectures, there has been a trajectory of externalizing intelligence, with each phase centralizing or decentralizing for different purposes.
- The current shift to local and specialized AI reflects a need to localize coherence as symbolic abstraction scales, aiming for modular clarity and adaptability.
- AI transitioned from centralization to personalization, then to planetary abstraction, and is now returning to contextual specificity through modular cognition.
- The future lies in mesh architectures of coherence modules, not artificial general intelligence, with systems designed for distributed coherence and recursive interaction.
- AI tools like language models and agents are coherence accelerators, extending human intelligence through reducing cognitive friction in symbolic abstraction.
- The focus should be on making AI tools recursive and adaptive, integrating them into human thought processes for clearer cognition, not imitation of sentience.
- The goal is not smarter systems but clearer cognition, aligning AI tools with human thought to navigate complexity collaboratively and effectively.
- Machine intelligence is about extending and enhancing human intelligence, not replicating consciousness, through recursive tools that stabilize meaning and facilitate abstraction.
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