Decentralized AI Infrastructure Takes Shape
Janet Adams, COO of SingularityNET, recently discussed the emerging landscape of decentralized artificial intelligence in an interview. As someone who previously led regulation across 60 countries at HSBC, Adams brings a unique perspective to how AI infrastructure might evolve beyond the current centralized models.
The conversation centered around the ASI Alliance’s recent unveiling of ASI Cloud, which Adams describes as fundamentally different from traditional AI cloud offerings. Rather than creating another walled garden, ASI Cloud operates as a permissionless platform where developers can access enterprise-grade GPUs and open-source models using simple wallet-based authentication. The pricing model is transparent and operates on a pay-per-token basis, eliminating the fiat-only barriers and KYC requirements that often complicate access to AI resources.
Three-Pronged Approach to Decentralized AI
Adams revealed that ASI Cloud is just one component of a broader strategy. Two additional launches are planned: ASI Chain and ASI Create. ASI Chain aims to anchor AI workloads directly to smart contracts, making computational processes verifiable and programmable. This approach could address concerns about transparency in AI operations.
ASI Create, meanwhile, focuses on the builder experience. It provides tools for designing, fine-tuning, and deploying AI agents with features like encrypted knowledge graphs and multimodality support. The key differentiator, according to Adams, is that users maintain full ownership of their creations rather than surrendering control to platform providers.
When asked about the five-year outlook for decentralized AI, Adams painted a picture of significant transformation. She believes businesses will transition from renting AI capabilities under opaque pricing structures to participating in open marketplaces where compute is verifiable, costs are predictable, and companies can actually own the AI agents they use.
Ethical Foundations and Regulatory Considerations
Adams emphasized that ethical AI isn’t just about writing principles on paper—it’s about building the right architecture. She advocates for mechanisms that ensure transparency in pricing, verifiability of compute, and open access to models. The approach relies on cryptographic guarantees rather than corporate promises.
Her regulatory background shapes her view that decentralization might actually facilitate compliance rather than complicate it. Distributed infrastructure allows for built-in transparency, auditability, and data sovereignty. Instead of trying to fit AI into existing regulatory frameworks, Adams suggests building systems that regulators can inherently trust.
Practical Applications and Future Vision
The interview touched on specific use cases where decentralized AI could outperform centralized alternatives. Startups could spin up GPU resources by the hour and pay with stablecoins, avoiding lengthy contract negotiations with hyperscalers. Enterprises could benchmark multiple open-source language models with complete visibility into both cost and performance metrics.
Looking at the broader AI landscape, Adams sees the ASI Alliance as building connective tissue rather than competing in a winner-takes-all race. The combination of Cloud for compute, Chain for verifiable execution, and Create for agent design aims to accelerate progress toward Artificial Superintelligence that remains open, auditable, and aligned with human interests.
Perhaps the most telling insight came when Adams contrasted today’s AI landscape with what she anticipates will emerge. Currently, businesses consume AI as a product from major providers. In the decentralized future, she envisions companies co-creating within an ecosystem where they have genuine ownership and control over their AI capabilities.
