Blockchain

AI has emerged as a significant catalyst for societal advancement, with the rise of large-scale AI models like ChatGPT fueling rapid growth in AI products and applications. The fusion of AI with Web3 stands out as a leading-edge technical trend, sparking the continuous emergence of related projects. This article delves into the potential and trajectory of AI+Web3 across the industry chain, encompassing Web3's empowerment of AI and the integration of AI technologies in Web3 applications. By enhancing data acquisition, preprocessing, and model validation, Web3 technology can amplify AI development and tackle challenges such as transparency, bias, and ethics. Currently, AI+Web3 applications are predominantly seen in sectors like gaming, social networking, data analytics, and financial prediction, with a competitive edge rooted in product and technical expertise accumulation.

The full-chain interoperability protocol is a grand narrative that integrates thousands of chain islands, especially in the era of modularization where the pursuit of maximum speed and cost-effectiveness is paramount.

This article aims to logically deduce potential differences between the bull market cycle in 2024 and previous cycles. Additionally, it presents personal reflections and strategies for navigating the current market conditions.

Pandora is merely the debut project of ERC404 and cannot capture actual value from ERC404's potential future developments and widespread applications, with its future development depending more on the continuous operation of subsequent project parties.

This article reviews the business cycles in the AI and cryptocurrency industries, and makes predictions for 2024.

This article mainly introduces the Fluence platform, which provides developers with a unique verifiable computing environment through its decentralized server architecture.

This article provides a detailed explanation of the decentralized AI vertical infrastructure Phoenix. The integration of DePIN (Decentralized Physical Infrastructure Network) with AI (Artificial Intelligence) has brought revolutionary changes to the market.

This article introduces Satoshi Protocol, the first Bitcoin Layer 2 project compatible with BEVM for EVM development experience. It will guide readers through various aspects of the protocol and how to participate in the Testnet activities. By understanding Satoshi, readers will gain a rough impression of the trends in BTC Layer 2 development.

Based on chain abstraction technology, MerlinChain enables BTC and other derivative assets to be cross-chained to Layer2, establishing an application protocol ecosystem and providing liquidity markets. Through the BTC-Connect platform of Particle Network, users can securely trade in their wallets, solving the problem of interaction between different chains.

Chain abstraction is a crucial direction for future development, aiming to allow users to enjoy the benefits of decentralization seamlessly. The CEO of Cycle Network believes that chain abstraction and self-custody will be future trends, making it easier for users to integrate into the decentralized world. With the development of rollup technology, layer2 and layer3 applications will see a significant explosion. Cycle Network hopes to address issues such as multi-chain deployment and cross-chain interaction, allowing the industry to return to an era where application development is the core. Cycle is a trustless omnichain ledger that utilizes ZK Rollup technology for fast multi-chain data movement and simplifies multi-chain ledger technology through an indexing mechanism.

Ethereum is a blockchain protocol known for its toolkit, smart contracts, and code-aligned ecosystem, heavily relying on ethers.js (a Javascript library) to provide the necessary potency for its developer-centric approach.

This article introduces the technical implementation of Ethereum and proposes a solution to apply machine learning to the Ethereum network to enhance security, efficiency, and scalability. Innovations have been made in Ethereum's transactions, consensus mechanisms, signature algorithms, data storage, and execution architecture. Machine learning can be applied to Ethereum for optimizing transaction processing, smart contract security, user segmentation, and network stability. Models like RFM and algorithms like DBSCAN can help identify high-value users and customize financial services. In the future, Ethereum can develop more complex machine-learning applications to improve network efficiency and security, and even achieve AI-driven governance mechanisms.

Ethena Labs, the developer of the Ethereum stablecoin USDe, recently announced the launch of its public Mainnet and introduced the “Shard Event” to incentivize users. Backed by Dragonfly Capital and other prominent institutions, the project raised over $14 million, outlining Ethena’s mission and why it is crucial for the success of cryptocurrencies!

The article discusses the potential of TON as a public chain that ranks in the top 20 by market capitalization but performs poorly in terms of trading volume and TVL. By explaining concepts such as public chains, ecosystem development based on Telegram, and new forms of value transfer in content, it demonstrates TON's differentiated experience and development prospects in the Web3 field.

A decentralization rating of BTC, ETH, SOL, XRP, ADA, AVAX, and TRX using six indicators shows ETH and ADA as the most decentralized, with XRP and TRX being the most centralized. The study employs a simple model to gauge decentralization, with ETH rated the highest and SOL more decentralized than BTC. However, no single blockchain dominates in all aspects, necessitating a multi-dimensional approach to assess decentralization.