Hetu is a revolutionary initiative at the forefront of the "AI for Science" movement. It serves as an intersubjective attribution layer, redefining how AI resources are coordinated and utilized in scientific research. Envisioned as the next - generation social contract platform, Hetu is bringing human - like intelligence to the Ethereum ecosystem, enabling a new era of decentralized AI applications in science. Developed by Advaita Labs, with a rich academic background of over 10 OSDI, SOSP, and NSDI papers in causality and distributed systems, Hetu is built on a solid foundation of research - driven innovation.
- Verifiable TEE-based Clocks
Leveraging Trusted Execution Environments (TEE), Hetu implements verifiable logical clocks. These clocks ensure the integrity and reliability of time - stamping for all AI - related events, from data transmission to model training.
- Fast Causal Ordering
Hetu enables fast causal ordering of not only traditional transactions but also abstract AI events such as user - data training. This ensures that all AI operations are executed in a logically consistent manner, enhancing the efficiency and reliability of AI workflows.
- Agent - Empowered Hyper-Scale Chains
By harnessing Directed Acyclic Graph (DAG) technologies, Hetu enables the creation of hyper-scale Agent-Native chains. These chains are designed to support a high volume of AI-related transactions, with a theoretical Transaction Per Second (TPS) rate of over 160,000. This high throughput capacity makes Hetu suitable for large-scale AI-in-science applications.
Hetu's architecture is a masterpiece of engineering, combining two key components:
Hyper-scale Parallel DAG Layer2 Chains: These chains are designed to offer rapid finality, scalable transaction throughput, and instant transaction settlement. They are the backbone of Hetu's ability to handle the high-volume, time-sensitive nature of AI-related transactions.
Off-chain Attribution Layer: This layer establishes a causality framework that unites disparate AI infrastructures. It acts as a bridge, enabling different AI systems to interact in a coherent and interoperable manner. This framework is crucial for attributing value, resources, and contributions within the AI ecosystem, especially in the context of scientific research.
- 🚀 Instant Finality for Onchain Value Attribution
- 🔐 Transparent Secure Timestamping
- 📈 Hyper-scalable verifications
- 🔄 Interoperable Ordering Mechanisms for Incentivization
- 🛡️ Anti-censorship governance
- 🌱 Empowering DeSci Infrastructures
- 🤝 Supporting Collaborative Agent Network
- Hyperscale pre-confirmations for AI-related transactions
- Real-time verifications for GPU platforms
- Verifiable TEE framework for data transmissions
- Shared sequencing for AI-Native chains
- Anti-censorship voting for AI governance
- Hyper scalable DeSci chains
- Attribution for longevity public networks
- Decentralized social layers for DeSci communities
- 📄 Chrono: A Peer-to-Peer Network with Verifiable Causality
- 📄 Building a Verifiable Logical Clock for P2P Networks