Disclosure: The ideas and opinions expressed here are only for the author and do not represent the ideas and ideas of the editorial of Crypto.
When people talk about zero-knowledge cryptography in 2024, they are often referring to a privacy-centered use case that depends on the combination of users to some extent of blockchain technology, cryptocurrency, digital wallet and web 3 knowledge.
Long before the arrival of Web 3, there are zero-knowledge evidences from the 1980s. So why limit your ability to blockchain applications? Traditional companies can adopt ZK technology without completely embracing the web 3 infrastructure.
At a basic level, Zkps unlocks the ability to prove anything without revealing the underlying data behind that statement. Ideally, a proof makes evidence, a verification verifying it, and these two sides are completely separated from each other to ensure fairness. This is really. There is no reason that this concept will have to be trapped behind the learning state of web 3.
Most organizations that can benefit from ZK technology are not using blockchain or are not even aware of web 3. The industry is still young, with many now familiar with bitcoins (BTCs) and atherium (ath), not to mention layer 2S and 3S.
Despite all this, Zkps can already be applied to a variety of cases of real -world use, and to do so they do not need to fully integrate the web 3 rail.
Do you trust your slot machine payout?
With zero-knowledge evidences, you do not need to rely on the gaming operator. You can simply enjoy playing and knowing that the game can be peacefully designed. Each digital gambling machine in the world should be designed with Zkps; This makes sense only for operators and players. The best thing is that players can enjoy benefits without the words “Web3” or “Crypto”, even enter their minds.
Recently, draftings and white hat gaming were Fined $ 22,500 by the Connecticut state for your online slot machine game, which failed to pay any winner in August 2023 – even though there were more than 20,600 spin that week. The game advertised that about 95 cents would be paid for each $ 1, so the algorithm should return $ 19,570 to the players who grossed $ 20,600 in Spins. Instead, the players lost $ 20,600 – all of which went into drafting.
This is the place where zero-knowledge proofs can create a big difference. A ZKP can prove that a game paid a certain amount at a specific hit rate in a certain period and a personal spin or player’s identity.
This is very good, but still there is a problem of verifying the evidence. One needs to ensure that drafts, or any gaming operator correctly constructed the evidence based on all the necessary data. It can be drafting itself, but we should not trust them to handle our own verification. A regulator or auditor can do this, but this will make the drafcating a lot of money to spend a lot of money, which will then pass the customer.
In this situation, the best option is a public and decentralized network designed to verify the evidence particularly quick and costly. The user is asked to rely on a centralized unit, they can rely on a decentralized protocol that ensures nefarious actors (ie, people who can try to verify a wrong proof) are punished if they misbehave.
AI output and reliability
AI’s ability for deception is well established. However, there are ways that we can exploit AI’s creativity, while still rely on its output. As Artificial Intelligence prevails every aspect of our life, it becomes rapidly important that we know that the model we trust are valid because if they are not, we can really change history and not even feel it. With zkml, or zero-knowledge machine learning, we avoid those potential losses, and the benefits can still be exploited by web 2 projects that have zero interest in going.
Recently, the University of Southern California Participation To create something called Iwitness with the SHOAH Foundation, where users are able to speak or type on the hologram directly on the holograms.
This is a powerful powerful use of machine learning. There is some strangely moving about a hoolocost survivor’s conversation with the holograms and realizing that you are having a real conversation. But with this sensitive subject, it is even more important that the underlying algorithm in the hologram is producing factual information.
Enter zero-knowledge proof. If we were to resume the project, we can consider adding “proof of algorithm output”, where the user is able to see that the reactions they are looking at are based on a natural language processing algorithm that was correctly trained on the trowers of historical tape and interviews with Holocosts, which were properly trained.
Zkps make it possible to obtain this input data and evidence of AI training without revealing the underlying information. A large amount of data will also be required to check Holocost information, possibly the last user needs to download or access the big data set and then spend hours to read hours reading or watching interviews. The ZKPS allows the user to discard this tedious and resource-intensive process.
In this case, we can rely on the USC to verify the evidence for this particular project, but there are definitely more use cases with AI where the final user may not want to rely on a centralized unit to create and verify proofs. When encouraged to build “fake” evidence and align to verify them, decentralized evidence verification makes the most understandable.
ZK is a reliable, decentralized system for all
We do not need to rely on companies or robots to tell us the truth because we have ZK. Many industries can level with zero-knowledge blockchain solutions, even if they do not know anything about web 3 space.
By tapping in ZK -proof verification, companies and institutions can continue to do everything that they are according to the infrastructure. They simply need to create a simple system for proof construction and then use a decentralized system such as zkveriff to handle proof verification. Even though a blockchain is used, users do not need to worry about it.
The future of ZK will be on a large scale, and organizations will not have to change much to get benefits. They can only plug and play.
