Technology Convergence Report 2025

Decentralized intelligent systems Decentralized intelligent systems fuse blockchain’s trust architecture, peer-to-peer (P2P) networking and edge-centric AI to tackle computing’s dual crises: the energy inefficiency of centralized data processing and the fragility of data privacy in interconnected systems. In addition to federated learning, blockchain adds cryptographic accountability, ensuring AI workflows (e.g. model updates in a supply chain network) are verifiable and tamper-proof without third-party oversight. The addition of P2P networks and content delivery networks (CDNs) dynamically allocate resources, cutting latency compared to traditional cloud pipelines.13,14 The system’s scalability stems from incentive- aligned participation where blockchain tokens reward contributors of edge compute resources (e.g. idle GPUs in a P2P grid), facilitating a self- sustaining ecosystem. The result is a resilient infrastructure where privacy isn’t a trade-off but a foundational feature, and energy efficiency scales organically with network growth. 4 2 1 2 3Decentralized intelligent systemsFederated learning on edge devicesEdge AIEdge AIContent delivery networks (CDNs) P2P networks Autonomous systems Technology domain Omni compute Artificial intelligence Maturity level 3 Product4 Commodity 1 Genesis2 Custom-builtN Industry Company Outcomes ITSeal StorageDecentralized cloud storage delivers secure, verifiable, and sustainable data management for research enterprise and Web3 applications. FinancialAaveAave is a decentralized and open-source protocol that offers a variety of financial tools and services, allowing for greater accessibility and financial transparency. Technology Convergence Report 22