As artificial intelligence proliferates and things on the Internet become easier to manipulate, there is a greater need than ever to ensure that data and brands are verifiable, said Scott Dykstra, CTO and co-founder of Space and Timeat TechCrunch’s The Chain Reaction podcast.
"Not to get too crypto-religious here, but we saw that during the FTX collapse," Dykstra said. “We had an organization that had some trust in the brand, just like I had my life savings in FTX. I trusted them as a brand."
But now-defunct crypto exchange FTX manipulated its books internally and misled investors. Dykstra sees this as querying a database for financial records, but handling it within his own database.
And this goes beyond FTX, in other industries as well. "There's an incentive for financial institutions to want to manipulate their records ... so we're seeing it all the time and it's becoming more problematic," Dykstra said.
But what is the best solution to this? 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 source data itself.
"It has a lot to do with whether there's an incentive for bad actors to want to manipulate things," Dykstra said. Whenever there is a higher motive, where people would like to manipulate data, prices, books, finances or more, 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, assert that a statement is true without conveying more information than whether it is true. For example, if I wanted to know if someone's credit score was over 700, if there is one, a ZK proof — prover — can confirm that to the verifier, without actually revealing the exact number.
Space and Time aims to be that verifiable computing layer for the web3 by indexing both off-chain and on-chain data, but Dykstra sees it expanding beyond the industry to others. As it stands, the startup has been indexed by major blockchains such as Ethereum, Bitcoin, Polygon, Sui, Avalanche, Sei and Aptos and is adding support for more chains to power the future of AI and blockchain technology.
Dykstra's most recent concern is that AI data isn't really verifiable. "I am quite concerned that we will never be able to verify that an LLM was performed correctly."
There are groups today working to solve this problem by creating ZK proofs for machine learning or large language models (LLMs), but it could take years to try to create this, Dykstra said. This means that the model operator can hack the system or the LLM to do things that are problematic.
There needs to be a "decentralized, but globally, always available database" that can be created through blockchains, Dykstra said. "Everyone should have access, it can't be a monopoly."
For example, in a hypothetical scenario, Dykstra said that OpenAI itself cannot own a database of a magazine, for which journalists create content. Instead, it should be something owned by the community and operated by the community in a way that is readily available and uncensored. "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 TechCrunch's Chain Reaction podcast. Sign up in Chain Reaction on Apple Podcasts, Spotify or your favorite pod platform to hear more stories and advice from the entrepreneurs building today's most innovative companies.
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