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The AI ​​world needs more data transparency, and web3 startup Space and Time says it can help

Scott Dykstra, CTO and co-founder of Space and Time, told TechCrunch’s Chain Reaction podcast that as artificial intelligence proliferates and things become easier to manipulate on the internet, it’s more important than ever that we make sure our data and brands are accountable. Verification.

“Not to be too religious about crypto, but we saw this during the FTX debacle,” Dykstra said. “We have an organization with a certain brand of trust, like I have my personal life savings in FTX. I trust them. It’s a brand.”

But now-defunct cryptocurrency exchange FTX was internally manipulating its books and misleading investors. Dykstra thinks of this as similar to querying a database for financial records, but doing so in its own database.

This goes beyond FTX and into other industries as well. "Financial institutions have an incentive to want to manipulate their records ... so we see this all the time, and the problem is getting worse," Dykstra said.

But what's the best solution? Dykstra believes the answer is through data verification and zero-knowledge proofs (ZK proofs), which are cryptographic operations used to prove something about a piece of information without revealing the original data itself.

"It has a lot to do with whether the bad actor has an incentive to want to manipulate things," Dykstra said. Whenever there is a higher incentive and people want to manipulate data, prices, books, finances, etc., ZK proofs can be used to verify and retrieve the data.

At a high level, ZK proofs work by having two parties, the prover and the verifier, confirm the truth of a statement without conveying any information other than whether the statement is correct. For example, if I want to know if someone has a credit score above 700, if so, a ZK proof (certifier) ​​can confirm this to the verifier without actually revealing the exact number.

Space and Time aims to be a verifiable computing layer for web3 by indexing data off-chain and on-chain, but Dykstra believes it will expand beyond the industry and into other areas. Currently, the startup has indexed major blockchains such as Ethereum, Bitcoin, Polygon, Sui, Avalanche, Sei, and Aptos, and is adding support for more blockchains to drive artificial intelligence and blockchain The future of chain technology.

Dykstra’s latest concern is that AI data cannot be truly verified. "I'm very concerned that we can't really effectively verify that the LL.M. is being performed correctly."

Dykstra said there are teams today working on solving this problem by building ZK proofs for machine learning or large language models (LLMs), but it could take years to try and create it. This means that model operators can tamper with the system or LLM to do questionable things.

Dykstra said there is a need for a "decentralized, but always available database on a global scale" that can be created through blockchain. "Everyone needs access to it, it can't be a monopoly."

For example, Dykstra said that in a hypothetical scenario, OpenAI itself could not become the owner of the journal database for which journalists create content. Instead, it must be something owned by the community and operated by the community in a manner that is accessible and uncensorable. “It has to be decentralized, it has to be on-chain, there’s no way around it,” Dykstra said.

This story was inspired by an episode of the TechCrunch podcast Chain Reaction. Subscribe to Chain Reaction on Apple Podcasts, Spotify, or your favorite podcast platform to hear more stories and tips from entrepreneurs building today's most innovative companies.

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