🌐🔗 NODES | compute framework LIVE
The Backbone of Society AI: A 100K-Node Network
The journey to Global AI begins here.
Society AI envisions a future where AI is global, decentralized, and powered by the collective.
At the core of this vision lies our 100K-node network—a groundbreaking foundation for democratizing AI and scaling it beyond the limitations of centralized systems.
Society AI’s decentralized infrastructure redistributes GPU power, making compute a shared, community-driven resource.
By leveraging nodes—distributed across servers, personal devices, and edge devices—we’re building a resilient and scalable foundation for AI training, inference, and data storage.
Nodes are the lifeblood of Society AI’s ecosystem, providing the compute power necessary to:
Train AI models collaboratively.Execute real-time and batch inference tasks.Store and manage datasets in a secure, decentralized manner.
Each node is a piece of the larger puzzle, creating a global, distributed network that powers the AI solutions of tomorrow.
Together, these nodes redefine how compute is accessed and utilized, transforming it into a decentralized commodity that benefits everyone—from individual contributors to enterprise developers.
With the 100K-node network, Society AI is not just building infrastructure; we’re laying the foundation for a truly equitable and accessible AI future.
100K-node network of Society AI
vs
existing centralized and decentralized compute networks
1. Centralized Cloud Providers (e.g., AWS, Google Cloud, Microsoft Azure)
Scale:
These platforms have vast computing resources,
but they are concentrated in a limited number of centralized data centers.
Cost:
High costs for AI compute, making access prohibitive for startups,
small developers, and open-source projects.
Flexibility:
Limited flexibility in adapting to community-driven needs or local requirements.
Key Contrast:
Society AI distributes compute across a 100K-node global network,
lowering costs via token emissions and providing affordable, community-owned infrastructure.
2. Decentralized GPU Networks (e.g., Render Network, Flux, Akash)
Scale:
Render Network leverages GPUs for rendering and creative applications, while Flux and Akash provide cloud-like infrastructure on decentralized systems.
Specialization:
Many focus on general-purpose computing or specific applications like rendering rather than AI training and inference.
Incentives:
Token-based systems incentivize compute providers but often lack mechanisms for broader ecosystem alignment.
Key Contrast:
Society AI’s node network is designed explicitly for AI, aligning incentives across compute providers, developers, and users through gamified onboarding and tokenized subsidies.
3. Blockchain Networks with Computing Power (e.g., Ethereum, Solana, Filecoin)
Scale:
These networks primarily focus on decentralized storage (Filecoin) or transaction processing (Ethereum, Solana) rather than AI compute.
Compute Orientation:
Blockchain networks often lack the raw GPU power or specialized frameworks required for large-scale AI tasks.
Key Contrast:
Society AI directly tackles AI compute needs, creating a network optimized for high-performance GPU workloads tailored to AI.
4. OpenAI and Other Centralized AI Providers:
Scale:
OpenAI and similar providers offer powerful AI models but rely on centralized infrastructure.
Access:
Limited accessibility due to high costs and tightly controlled access.
Key Contrast:
Society AI democratizes access to AI resources by offering a decentralized marketplace (AI Hub), where affordable compute fuels innovation and collaboration.
The Unique Strength of Society AI’s Decentralized Network
Scale:
A 100K-node network delivering GPU power comparable to centralized giants but distributed across a global community.
Affordability:
Token emissions subsidize compute costs, making high-performance AI affordable and accessible.
Inclusion:
Gamified onboarding ensures mass adoption, turning idle devices into compute contributors.
Resilience:
Decentralized infrastructure ensures no single point of failure, enhancing reliability and uptime.
Innovation:
Tailored for AI, enabling training, inference, and model hosting at unparalleled cost-efficiency.
Why This Matters:
With Society AI, developers, businesses, and individual contributors gain access to a distributed infrastructure that rivals centralized providers in power while surpassing them in accessibility, affordability, and alignment with community interests.
This is the backbone of Global AI—a network built by the people, for the people.
How Nodes Power the Decentralized Network
Model Training:
Nodes divide training workloads, compute gradients, and synchronize parameters, enabling efficient and collaborative AI model training.
Inference Execution:
Real-time and batch inference tasks are handled by nodes, delivering predictions and classifications for low-latency applications.
Data Sharing:
Nodes facilitate federated learning by locally training models and aggregating updates to preserve data privacy.
Node operators: enabling the 100K nodes
Core Responsibilities of Node Operators
Providing Compute Power: Node operators contribute GPU or CPU resources from their dedicated servers, personal computers, or edge devices to handle AI workloads.
Enabling Decentralized AI: By distributing tasks like training and inference, node operators eliminate the reliance on centralized cloud providers, ensuring scalability and resilience.
Maintaining Network Health: Operators monitor their nodes to ensure optimal performance, uptime, and compliance with the network’s protocols.
Facilitating AI Services: Nodes execute AI services such as model training, inference tasks, and data processing for developers, businesses, and end-users.
Benefits of Participating as a Node Operator
Economic Incentives: Earn Society AI tokens from network fees and token allocations based on the compute power provided.
Community Contribution: Be part of a decentralized movement shaping the future of AI.
Long-Term Growth: Participate in a network designed for scalability, accessibility, and innovation.
Governance Role: Influence platform decisions through DAO participation.
STATUS
The technical backbone for scaling decentralized nodes and reducing reliance on centralized providers, all while powering diverse AI models.
A scalable compute infrastructure built on KServe
Technical infrastructure built and operational on our AI Hub.
Already serving leading open source LLMs and image models like meta/Llama 3.2 and black-forest-labs/FLUX
Serving AI application built on our AI Hub
The foundation for our decentralized node framework
VALUE:
Building the framework for community powered AI, enhances participation and creates a revenue share. Ensures Society AI offers ultra-competitive compute costs to attract open-source developers and businesses.
Next Steps:
Conduct node sale and sell the licenses as NFTs to community members to operate nodes.
Finalize compute infrastructure over 3 stages to achieve network decentralization.
Integrate compute power delegation from users’ edge devices such as mobile phones and desktops, enhancing community participation.
Improve system efficiency to reduce compute costs further.
Last updated
