Why QuarkChain’s Super World Computer Could Redefine the Standards for Blockchain Performance
In Brief
QuarkChain envisions a seamless Web3 future powered by decentralized supercomputers, AI-driven asset tokenization, and effortless Web2-to-Web3 transitions, all underpinned by scalable blockchain, AI innovation, and quantum-resilient security.
Imagine a world where decentralized supercomputers process petabytes of data, AI agents tokenize assets seamlessly, and Web2 users onboard to Web3 without even noticing the shift. This isn’t a distant dream; it’s the vision Qi Zhou, Co-founder and CEO of QuarkChain, is making a reality. QuarkChain, known for its scalable blockchain solutions, is tackling some of the most pressing challenges in Web3—from efficient computation to user-friendly onboarding—all while pioneering advancements in AI and quantum-resilient security.
Can you start by sharing your thoughts on the current state of Web3?
Right now, Web3 essentially has two categories of applications. One is the financial category, where the biggest example is definitely Bitcoin, including recent Bitcoin ETF developments. There’s also a recent popularity of meme coins, where people are mostly transacting these coins even though they have no actual intrinsic value.
On the other side, I’ve observed a great, albeit slower, growth in non-financial applications. For example, Farcaster is now building a decentralized social network and developing an independent chain called Snapchain. They’re working on storing all user interactions like likes and reposts on the blockchain, with the potential to incentivize users in the future.
Another significant trend is definitely the intersection of crypto and AI. For instance, I’ve been exploring ai16z, which has a popular repository called Eliza. This platform can run AI agents that can connect to platforms like Discord and Telegram bots. These agents can issue tokens, essentially creating a new way to tokenize assets similar to NFTs. They can send tokens using wallets, analyze trades, and even help identify investment projects. There are a lot of interesting ideas emerging in this space right now.
How is the concept of decentralized computing evolving to meet the growing demands for scalability and security?
For decentralized computing, we’re primarily solving challenges through Layer 2 solutions. The basic concept is off-chain computation with on-chain verification. We’re aggressively pushing toward more massive computation capabilities.
Data sourcing is another crucial area we’re working on. However, Ethereum currently faces a significant challenge: even if we can upload and verify large amounts of data, the gas cost remains prohibitively high. That’s why we’re developing what we call the Super World Computer, which applies our advances in computation with fast settlement and the ability to handle massive data – we’re talking about petabytes of data.
As a concrete example, we can now store something like the Llama model, which has 7 billion parameters and is about 35 gigabytes in size. Users can safely run their models and agents on the Ethereum network without worrying about single-point failures.
With AI emerging as a major narrative, what key infrastructure elements are necessary to support AI? And how can QuarkChain contribute to this infrastructure?
From an infrastructure perspective, the key is enabling massive off-chain computation with quick on-chain settlement of computational results. One popular approach uses Zk-SNARK technology to verify off-chain computation.
However, compared to verifying Ethereum transactions, the AI computation scale is much larger – potentially 100, 1,000, or even more times larger than traditional Layer 1 or Layer 2 transactions. We need an even faster and more cost-effective way to prove on-chain that AI models and inferences are computed correctly.
We’ve received two or three grants from OpenStack to address this problem. Our approach combines data availability with Zk-SNARK techniques to increase ZK verification bandwidth by more than 1,000 times. We’ve already completed testing and have developed initial specifications. We’re planning to proceed with further testing and hopefully launch on mainnet next year.
What challenges do decentralized applications face when transitioning from Web 2 to Web 3? How can QuarkChain mitigate these problems?
There are several significant challenges in transitioning from Web 2 to Web 3, primarily related to user onboarding. In Web 2, users can easily register for services like Twitter or YouTube using a phone number or email. Web 3 experiences are not yet as smooth.
For instance, in Web 3, users first need to create a wallet and securely store private keys. To send their first transaction – whether swapping tokens, sending value, or running an on-chain agent – they must acquire gas tokens.
Vitalik recently wrote an insightful article about the future of this process. With the introduction of EIP-7702, we can now create on-chain addresses using traditional authentication methods like email. As long as these accounts can provide a basic message signature – which email providers like Google already do – we can use these signatures to authorize on-chain transactions.
We’re in the early stages of contributing to EIP-7702, including helping develop standard specifications. We’ve already created demos on the EIP-7702 testnet and DevNet to demonstrate these capabilities.
Our second approach involves helping users send their first transactions without requiring them to acquire gas tokens. While transaction costs are low on Layer 2, the process of obtaining gas tokens from exchanges can deter users.
Our solution is to airdrop non-transferable “sole guest tokens” to users who verify their Web 2 identity. By making these tokens non-transferable, we prevent potential abuse like creating multiple accounts to exploit airdrop benefits. This approach allows us to provide an onboarding experience almost identical to Web 2.
What regulatory challenges might arise as computing networks and blockchain become more mainstream?
There are numerous regulatory challenges. Take Tornado Cash, a privacy-focused mixer application, as an example. A few years ago, its creators were imprisoned for allegedly breaking regulatory laws in the United States. However, recent court decisions suggest that such autonomous smart contracts cannot be controlled or censored, which is potentially good news for developers.
On the storage side, my colleagues working as storage providers for projects like Filecoin are facing challenges with sensitive or potentially illegal data uploads. Some service providers send legal notices demanding they stop storing or spreading such content.
I prefer the concept of “self-regulation” – using the powerful computational and storage capabilities of Web 3 to create a weak self-regulatory mechanism. One proposed method is using AI, potentially voted on by a DAO, to determine and remove harmful or illegal content.
This approach could help build a healthier network by autonomously managing spam, noise, and illegal content, creating a more valuable ecosystem for everyone.
Regarding recent news about Google’s quantum computing breakthrough, what is the potential impact on blockchain security? How are networks preparing for this threat?
I’ve had extensive discussions with my community about quantum computing, especially Google’s recent breakthrough in reducing quantum noise when creating quantum bits.
Breaking Bitcoin’s encryption currently requires thousands of logical quantum bits. However, due to error rates, we’d previously needed millions of physical quantum bits to effectively counter computational noise.
There are two potential approaches. One is building quantum computers in deep space – which interests Elon Musk, who could use SpaceX to send quantum chips into areas with less electromagnetic interference. However, quantum computation machines are currently huge, power-consuming, and not yet practical.
Google’s recent “Willow” project proved that even in normal Earth environments, they can build chips that suppress noise. Where we once needed millions of physical quantum bits, we might now need only 10,000 or fewer.
This makes cracking Bitcoin’s hash and ECDSA signatures much easier, but it’s still expensive. Bitcoin can likely adopt post-quantum signature schemes. Many quantum signature schemes also use hash functions, allowing a smooth transition from current ECDSA signatures.
There are challenges, like significantly larger signature sizes and potential vulnerabilities in older coins like Satoshi’s. But overall, we believe cryptocurrency will remain robust even with quantum computing advances.
What does the roadmap or vision for Super World Computer (SWC) look like moving forward? What are your plans for the next year?
This year, we’ve made significant progress on our supercomputer. We’ve officially launched our supercomputer website and developed a DevNet that achieves most of our roadmap features, including massive-scale storage and efficient off-chain computation settlement.
We’ve also developed features like the SO-Gas token, which allows users to add jobs without gas tokens, provided they can prove their Web 2 identity. For next year, our first step is launching public testnets with a campaign to attract users to experiment with our network. We aim to launch our mainnet if everything remains stable.
We’re planning what could be one of the largest airdrops in Web 3 history. For context, the largest previous airdrop, Starkware, covered about 1.5 million addresses – negligible compared to Web 2’s billions of users.
Later next year, we’ll start exploring more experimental ideas on our mainnet, such as fast sentiment analysis. We want to ensure everything is thoroughly tested and audited before launch.
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About The Author
Victoria is a writer on a variety of technology topics including Web3.0, AI and cryptocurrencies. Her extensive experience allows her to write insightful articles for the wider audience.
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Victoria is a writer on a variety of technology topics including Web3.0, AI and cryptocurrencies. Her extensive experience allows her to write insightful articles for the wider audience.
