👁️‍🗨️Technology

Society AI employs a hybrid Web2 x Web3 tech stack: combining web2 compute & AI technologies with web3 governance, decentralization and economic models.

Web2 : Providing an intuitive, fully featured and scaleable platform supporting all commonly used frameworks used in AI development.

• AI Developer Infrastructure: Supporting the common programming languages and frameworks used to develop AI, such as Python, TensorFlow, PyTorch, and Hugging Face Transformers. This ensures that developers can easily transition their existing projects to Society AI.

• Deploying Models and Running Inference on All Hardware: Enabling seamless deployment of AI models and running inference across various hardware environments, including CPUs, GPUs, and specialized AI accelerators, ensuring compatibility and performance optimization.

• Scalable Cluster Management Solutions: Utilizing Kubernetes for scalable and efficient cluster management, allowing for automated deployment, scaling, and management of containerized applications, ensuring high availability and reliability.

• Comprehensive API Support: Offering extensive APIs for model deployment, management, and monitoring, providing developers with the tools needed to integrate and manage AI capabilities within their applications effortlessly.

• User-Friendly Interface: Providing an intuitive and user-friendly interface similar to what AI developers are used to from web2 platforms for managing models, datasets, and computational resources, making it accessible for both novice and experienced developers.

Web3: Building a decentralized and transparent onchain infrastructure to manage governance, decentralized compute and inference and tokenized financial models.

• Society Chain: Our own zkValium Ethereum L2 rollup that will enable us to supports all transactions on-chain, ensuring scalability and low-cost operations, making it feasible for widespread adoption and usage.

• zkML for Verifiable Inference: Using zkML protocols to ensure that inference operations are verifiable, providing transparency and trust in the AI models' outputs performed by decentralized nodes.

• Decentralized Governance via DAO: Allowing community members to participate in decision-making processes, ensuring the platform evolves in a democratic and community-driven manner.

• Tokenized Financial Models: Creating the protocols to share the platform's revenue with the community, incentivizing participation and rewarding contributors fairly, aligning the interests of the platform with its users and developers.

• Interoperability and Integration with other chains: Ensuring interoperability with other L1 and L2 chains and Web3 applications, facilitating seamless integration and expansion to the broader web3 ecosystem.

• Transparency: Leveraging blockchain's inherent transparency and auditability features to provide a clear and traceable record of all transactions and operations, enhancing trust and accountability within the platform.

AI Hub

• Akin to a "decentralized Hugging Face".

• Open-source AI models and datasets: Hosting a comprehensive collection of AI models and datasets contributed by both industry leaders and the global community. This open-source repository promotes collaboration, transparency, and the rapid advancement of AI technologies.

• AI Agents marketplace: A dynamic marketplace where users can discover, share, and deploy AI agents. This marketplace enables the distribution and utilization of specialized AI solutions, catering to a wide array of applications and use cases.

• Compute by distributed community nodes: Harnessing the power of a distributed network of community nodes this decentralized approach ensures scalable, resilient, and efficient processing, leveraging the collective power of the community.

• AI applications: Users can develop and deploy AI applications that seamlessly integrate AI models, datasets, and agents. These applications are powered by the robust infrastructure of community nodes, ensuring high performance and reliability across diverse use cases.