The Internet of AIs with Edge Compute, Siloed Data, Agents and Data Markets
In today's AI landscape, data, computation, and governance are centralized. Decentralized AI offers a promising alternative leveraging intelligent, network-based approaches to improve collaboration, incentives, and innovation at the edges. It offers a promising alternative enabling collaboration between distrusted, disincentivized, and disinterested entities.
AI has made remarkable strides, showcasing its vast ability to tackle large-scale challenges. These advancements open new possibilities for areas where data and knowledge are distributed across different organizations and regions such as healthcare, climate science, and supply chain management. We highlight five essential technical opportunities: (1) enhancing privacy, (2) ensuring verifiability, (3) aligning incentives, (4) enabling orchestration, and (5) improving crowdUX. By addressing these opportunities, diverse entities can collaborate to solve global issues while still achieving their local goals. This vision of Decentralized AI encourages further dialogue and research toward a decentralized, inclusive, and resilient AI future.