The AI 2.0 narrative presents meaningful structural shifts compared to its predecessor. The key difference lies in focus: where AI 1.0 centered on general large language models and broad adoption, AI 2.0 emphasizes specialized applications, on-chain intelligence, and autonomous agents operating within decentralized ecosystems. This iteration also diverges in execution—rather than enterprise-dependent deployment, we're seeing permissionless, community-driven development gaining traction. The market structure reflects this too: earlier cycles were dominated by megacap plays, while current momentum shows fragmentation across sector-specific AI tokens and infrastructure. For crypto markets specifically, the distinction matters significantly—it reshapes which projects capture value and how investor allocation flows. Understanding these architectural changes helps identify which narratives have genuine staying power versus hype cycles.