Appendix & Reference
Last updated
Last updated
ZK Rollups, or Zero-Knowledge Rollups, are an innovative Layer-2 scaling solution for blockchain networks, e.g., Ethereum. They utilize zero-knowledge proofs to validate batched transactions efficiently while maintaining security and decentralization. By processing multiple transactions off-chain and submitting only a cryptographic proof to the main blockchain, ZK Rollups significantly enhance transaction throughput and reduce costs.
ZK Rollups operate by grouping numerous transactions into a single batch, which is then processed off-chain. The key steps involved are:
Batching Transactions: Multiple transactions are aggregated into a single batch, reducing the amount of data that needs to be recorded on the main blockchain.
Generating Validity Proofs: A zero-knowledge proof is created for the entire batch, which certifies that the transactions are valid without revealing any sensitive information.
Submitting to the Mainnet: The proof and a summary of state changes are sent to the main blockchain, where a smart contract verifies the validity proof and updates the state accordingly.
This method ensures that while transaction data is minimized on-chain, the integrity and security of the blockchain remain intact.
In addition, ZK Rollup eliminates the dependence on observers and replaces game-theoretic economic security with cryptographic security. This is because, in traditional blockchain technology, the verification and confirmation of transactions depend on the participation of miners and observers, which can bring some security and efficiency issues. ZK Rollup adopts a cryptographic-based verification method, moves the verification process to the layer 2 chain, and uses zero-knowledge proof to prove the legality of transactions, thereby greatly improving the security and efficiency of transactions.
ZK Rollups offer several significant advantages over traditional blockchain transaction processing methods:
Scalability ZK Rollups can handle a much larger volume of transactions per second compared to standard on-chain processing. By moving computation off-chain, they alleviate congestion on the main blockchain, enabling it to process thousands of transactions simultaneously.
Reduced Costs Transaction fees are substantially lower with ZK Rollups because they optimize on-chain resource use. Users benefit from reduced costs, often paying less than $1 per transaction, compared to higher fees experienced during peak network congestion on Ethereum
Enhanced Security The use of zero-knowledge proofs ensures that transactions are validated without exposing any private information. Furthermore, users retain control over their assets since they can always withdraw funds back to Layer 1, providing a robust safety net against potential failures in Layer 2 systems910.
Faster Transaction Confirmations - ZK Rollups expedite transaction confirmations by simplifying the verification process. The challenge period for confirming transactions is shortened as only validity proofs need to be verified on-chain23.
Improved Privacy Zero-knowledge proofs allow users to prove transaction validity without revealing transaction details, enhancing user privacy compared to other scaling solutions like optimistic rollups69.
Minimal Withdrawal Delays Users can access their funds quickly due to streamlined withdrawal processes in ZK Rollups, contrasting with other solutions that may impose longer waiting times for fund retrieval.
The development of artificial intelligence computing power is limited by the distribution and availability of computing resources. Currently, there is an imbalance in the distribution of computing resources, and some regions and organizations may not have sufficient computing resources to support the development of artificial intelligence. Many large models (such as ChatGPT) require a large number of GPUs, so Zippy provides a decentralized computing platform and uses edge computing two-layer network technology to form a computing resource sharing network, in which participants can crowdfund by using their own GPUs to improve the efficiency of large-scale artificial intelligence algorithm training.
Edge computing platform is a distributed computing platform that can assign computing tasks to devices closer to the data source for processing, avoiding the bottleneck problem of data transmission and improving the training speed. In Zippy, participants use their own GPU resources on the edge computing platform to crowdfund and perform parallel computing on multiple GPU devices to accelerate the training process, which can train more complex and accurate models in a shorter period of time. This can fully utilize participants' computing resources, avoid idle resources, improve resource utilization, and reduce costs by avoiding the need to purchase expensive GPU devices. In addition, participants can receive rewards to incentivize them to provide computing resources, which also promotes the development and expansion of the network.
The layer 2 network technology is a distributed computing network based on blockchain technology, which can distribute computing tasks to multiple devices for processing and aggregate processing results to the main network. In Zippy, training tasks are assigned to different participants' GPUs for processing. Each participant can perform calculations on their own device and then submit the calculation results to the blockchain network. After the calculation results are aggregated, the final training result can be obtained. Therefore, using two-layer network technology to distribute training tasks to different participants' GPUs for processing can prevent single-point failures, improve network reliability, protect data privacy, and prevent data leakage.
Meanwhile, participants can use smart contracts to coordinate and verify computing results, ensuring the correctness and security of algorithm training. Blockchain technology can also be used for data sharing and verification, enhancing the reliability and credibility of algorithm training. This approach allows participants to freely choose to participate in crowdfunding GPUs, and edge nodes can also join or exit at any time, ensuring the fairness and transparency of algorithm training.
In addition, smart contracts are used to manage transactions and protocol execution between participants. For example, when a participant completes an artificial intelligence training task, they receive a certain amount of tokens as a reward. These tokens are stored in their wallet and can be used to purchase computing resources provided by other participants.
[1]. https://trendfeedr.com/reports/ethereum-virtual-machine-report/
[2].https://www.skyquestt.com/report/blockchain-ai-market
[3].https://interexy.com/decentralized-ai-exploring-the-potential-of-the-revolutionary-technology/
[4]. https://inplp.com/latest-news/article/blockchain-vs-data-protection/
[5].https://yellowcard.io/blog/how-to-implement-amlkyc-checks-for-your-customers-in-crypto/
[6].https://www.openware.com/news/articles/implementing-kycaml-in-crypto-exchanges
[7].https://coinpaper.com/3331/is-ethereum-a-security-understanding-the-legal-classification
[8]. Sompolinsky, Y., Wyborski, S., & Zohar, A. (2021, September). PHANTOM GHOSTDAG: a scalable generalization of Nakamoto consensus: September 2, 2021. In Proceedings of the 3rd ACM Conference on Advances in Financial Technologies (pp. 57-70).
