In the burgeoning intersection of blockchain and AI, discussions often revolve around decentralized inference and decentralized training. However, the critical component of this data remains largely overlooked. One major question remains: how can we safeguard against biases and manipulate data in AI models? Covalent Network addresses this challenge with the largest reservoir of structured, verifiable data, ensuring AI systems are trained on reliable, trustworthy information. By providing clean, trustworthy data, Covalent Network ensures that AI systems can make accurate and unbiased decisions, fostering the development of robust applications.
Covalent Network’s unique, decentralized data pipeline structures and cryptographically secures every historical blockchain datapoint across over +225 blockchains. With over 100 billion transactions semantically decoded and classified, Covalent Network ensures meticulous accuracy in its data handling. This comprehensive approach has enriched 300 million wallets to date, positioning Covalent as the reliable solution for all Web3 data needs.
Unlike traditional databases, blockchains function more like billboards, displaying information temporarily before it’s permanently deleted. For instance, Ethereum blob data is removed after two weeks, and similar practices are seen with projects such as Eigenlayer and Celestia. This presents a significant challenge: how is verifiable data secure and protected for the long term, ensuring it remains accessible? Covalent Network’s Ethereum Wayback Machine provides a solution, preserving historical Ethereum data and securing it against deletion, thus maintaining the integrity and security of the blockchain.
As the leading modular data
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