What if the next major breakthroughs in AI don't come from racing toward larger models, but from smarter collaboration?

The traditional approach assumes bigger always wins. But there's an alternative perspective worth exploring: a decentralized network layer where AI agents securely exchange insights, validate information through consensus, and gradually establish mutual trust.

This model flips the script on how we typically think about centralized AI development. Instead of concentrating intelligence in a few mega-models controlled by major players, you'd have a distributed ecosystem where different AI systems contribute to collective intelligence.

The appeal is obvious if you're skeptical of centralization. Rather than betting everything on proprietary black boxes, a tokenized or protocol-based approach lets participants build transparent incentive structures. Knowledge sharing becomes verifiable. Trust gets established through repeatable interactions, not brand reputation.

It's an interesting thought experiment: could swarm intelligence principles applied to AI actually outperform the conventional playbook? The infrastructure challenges are real, but so is the potential upside for truly open AI development.