CCAI Chain Introduction
Last updated
Last updated
CCAI Chain solves the "impossible triangle problem". The main technical indicators are as follows:
High transaction throughput: Can handle large volumes of transactions, capable of processing up to 10,000 transactions per second (TPS). This is a significant improvement compared to other blockchains like Ethereum, which typically manages around 15-25 TPS. Higher throughput means it can accommodate larger operations without bottlenecks.
Fast block time: The block time on the main chain is about one second, which means that new blocks are generated and transactions are confirmed very quickly. This benefits both users and developers as it leads to a smoother and more efficient user experience.
Scalability: It can be easily interconnected or expanded with other independent blockchain (or regional) networks. Each zone operates independently, managing its transactions and validators, which prevents congestion and enables the network to scale horizontally as new zones are added.
CCAI, as an open AI blockchain infrastructure, maintains compatibility with the Ethereum ecosystem while extending the functionality of the Ethereum Virtual Machine (EVM) to provide additional support for AI applications.
Building on the EVM, CCAI introduces new AI-related system call interfaces. These interfaces enable smart contracts to access financial AI services, including large language models, AI agent models, image recognition, voice recognition, and natural language processing. Developers can easily integrate various AI functionalities into the blockchain by invoking these interfaces.
On CCAI Chain, AI service providers can develop their own financial AI models and systems, which can then be deployed on the blockchain in the form of smart contracts. Other users and developers can call these smart contracts and pay for services according to customized pricing models.
Once the CCAI large financial model is trained and deployed on the CCAIChain blockchain platform, the CCAI model and CCAIChain will natively support the CC-Trains quantitative trading system.
Quantitative Trading System Integration:The system is seamlessly integrated into CCAIChain through the use of oracles. This allows users to access quantitative trading orders, strategies, and trading bot information via native oracle smart contracts on the blockchain. This integration ensures the trading system is continuously updated with real-time market data, which is crucial for maintaining the accuracy and relevance of trading strategies.
CCAI Model Utilization:Qualified investors can interact with the CCAI model through blockchain smart contracts. These interactions enable the creation of independent AI analysts and trading bots, which can be used either for personal purposes or as services offered to others. The predictive analysis of the CCAI model is driven by its ability to process large volumes of financial data and its well-trained algorithms, which can adapt to changing market conditions and make more informed, potentially profitable trading decisions.
Algorithm Enhancement:The algorithms of the CCAI model are continuously improved through decentralized training on the financial blockchain. This ensures the model evolves along with market developments. This decentralized approach democratizes access to advanced AI functionality, allowing a broad range of users to benefit from AI-powered quantitative trading.
Privacy and Security in Quantitative Trading:The system places a high priority on maintaining the privacy and security of trading activities. By utilizing Secure Multi-Party Computation (SMPC) and zero-knowledge proof technologies, the platform ensures that sensitive financial data and trading strategies remain confidential while still allowing for the verification of trade integrity.
Smart Contract Functionality: further enhances the trading system, allowing for the automation of trading strategies. These contracts are designed to execute trades automatically based on the insights provided by the CCAI model when certain market conditions are met, eliminating the need for manual intervention.
