Le monde de l'IA a besoin de plus de transparence des données et la startup Web3 Space and Time affirme qu'elle peut aider

Space and Time proposes to improve data transparency in the world of AI thanks to Web3

In a world where technology evolves at a breakneck pace, data integrity and brand trustworthiness have never been more crucial. Scott Dykstra, the CTO and co-founder of Space and Time, shares his thoughts on the importance of data verification in the age of artificial intelligence. During a discussion on E.S News’ Chain Reaction podcast, Dykstra highlights the challenges posed by the ease with which information can be manipulated on the Internet, and how blockchain technology could offer a viable solution.

The cryptocurrency sector was recently shaken by the FTX affair, an exchange platform that lost the trust of its users by manipulating its accounts. This situation perfectly illustrates the risks associated with poor data management and raises questions about the reliability of financial institutions. **“We constantly see attempts to manipulate data, which is becoming more and more problematic,” says Dykstra.**

To counter these threats, Dykstra is convinced that the solution lies in the use of “proofs of zero knowledge“(or ZK proofs), a cryptographic tool allowing the accuracy of information to be verified without disclosing its content. These proofs work through an exchange between a “prover” and a “verifier”, thus guaranteeing the veracity of the data without exposing sensitive information.

Space and Time aspires to become a reference platform for information verification in the Web3 universe, offering both off-chain and on-chain data indexing. This startup aims not only to revolutionize the blockchain sector but also to expand to other areas, by ensuring reliable and verifiable access to data. **“The goal is to create a decentralized, but globally available, database that is not under the control of any monopoly,” says Dykstra.**

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The latter also expresses concerns about the possibility of effectively verifying data generated by artificial intelligence. The complexity of systems such as large language models (LLM) makes this task particularly difficult. According to Dykstra, although efforts are underway to develop ZK proofs suitable for machine learning, the road is still long and fraught with pitfalls.

Finally, Dykstra calls for community management of databases in order to preserve their integrity. The idea of ​​entrusting ownership of information to a single entity, even in cases as innovative as those of OpenAI, seems contrary to the spirit of decentralization advocated by blockchain technologies. **“It is essential to move towards decentralized and on-chain data management to avoid any form of censorship,” concludes Dykstra.**

With this in mind, blockchain technology stands as a bastion of data verification and reliability in an age where information is as valuable as it is vulnerable.