Exploring the Realm of DeFi and Rollups: Unlocking Scalable Solutions for Blockchain Computation
In Brief
Imagine if smart contracts had the capability to handle data as efficiently as traditional databases. Lagrange is turning this concept into a reality with its innovative SQL-based zero-knowledge proofs, drastically transforming on-chain computations while paving the way for enhanced DeFi applications and blockchain scalability.
What if smart contracts could seamlessly operate with data just like databases do? Lagrange is realizing this vision through SQL-based zero-knowledge proofs, granting developers an effective method to execute verifiable computations on-chain. This cutting-edge solution is unlocking entirely new avenues in DeFi and scalability for blockchain applications.
We spoke with Ismael Hishon-Rezaizadeh , Founder and CEO of Lagrange In this discussion, we'll delve into his transition from Web2 investments to creating a robust Web3 infrastructure. Here’s how his team is redefining the blockchain development landscape.
Could you kick things off with a brief overview of your personal journey into the Web3 space?
Before launching Lagrange, I invested in Web2. My background includes working at a small venture fund called Renegade Partners in San Francisco, which raised around $110 million. My role focused on early-stage B2B software and payment infrastructure investments. Prior to that, I was involved in DeFi engineering for a major insurance firm. After my venture fund experience, I ventured into founding Lagrange.
Initially, we pinpointed the shortcomings developers faced with on-chain engineering. One core issue was the scarcity of effective zero-knowledge tools.
What sets Lagrange’s SQL-based ZK processor apart from conventional ZK-proof systems in terms of scalability and capabilities?
Our solution allows for the efficient proof of SQL-based computations utilizing blockchain data. Should you need to run a query for verifiable consumption in your contract—like calculating a moving average of prices or determining historical volatility—you’ll require a zero-knowledge approach that works efficiently while ensuring a smooth developer experience. We empower users to write computations in SQL, a language well-known for database interactions, enabling the generation of zero-knowledge proofs for those queries to be applied on-chain.
How does this SQL query interface streamline developer workflows compared to designing custom circuits?
It simplifies the process by permitting you to articulate your computations in a friendly, recognizable language instead of laboriously crafting circuits manually. Writing your queries in SQL makes manipulating data much more intuitive than using a different syntax.
Could you give us more details about the additional solutions that Lagrange offers?
We focus on two primary components. The first is a decentralized prover network, and the second is a coprocessor. The decentralized prover network enables us to generate zero-knowledge proofs collaboratively, leveraging a broad base of operators involved in the proof generation process.
We collaborate with numerous significant institutional operators, including Coinbase, Kraken, OKX, P2P, Figment, Luganodes, Infstones, and Black Sand. They contribute computational power to our network, allowing us to produce and deliver proofs to end users.
We have a major announcement regarding our network's application for generating proofs for roll-ups on platforms such as Caldera and Altair.
How does Lagrange’s technology facilitate application scalability across various blockchains?
Currently, our focus isn't heavily on cross-chain work, although we do have a pre-existing product aimed at state proofs that we offer across several protocols. However, it's not our central focus in the cross-chain space.
What impact does Lagrange’s coprocessor have on Ethereum’s future scalability?
It significantly broadens the design possibilities for developers by providing access to large-scale verifiable computation. With the capability to extensively compute historical data, this allows for the creation of on-chain functionalities that were once viewed as unfeasible. In DeFi, price and volatility feeds are critical, but our coprocessor can help eliminate many dependencies while leveraging on-chain data.
What inspired the emphasis on ultra-scalable queries, and what distinct opportunities does this present?
The driving force behind our focus was recognizing the limitations associated with developing on-chain smart contracts. Previously, there was no effective means for contracts to access historical data. Developers often relied on cumbersome design patterns to accumulate data within the state, which was not only costly but also gas-inefficient and potentially insecure. The ability to query historical data verifiably from a contract truly expands the range of what can be constructed.
Do you primarily engage with developers in the USA, Europe, or the APAC region?
We boast a global reach. While I reside in the U.S. and much of our team is located in Europe, we strive to connect with developers worldwide. For instance, I attended DevCon in Bangkok, which was a fantastic event.
How does your system tackle potential latency challenges in distributed proof generation?
Our technology generates proofs using highly parallelizable methods. With a vast network of operators, we can efficiently distribute the computational workload and subsequently consolidate results. This parallel approach significantly reduces proof generation time. Moreover, as ZK technology advances and our proofing methods improve, latency will continue to decrease.
Can you share insights on collaborations with protocols like Arbitrum, BASE, and other projects?
We see ourselves as a credibly neutral entity. We embrace collaboration and are open to anyone interested in utilizing the proofs we create. We’ve successfully integrated our coprocessor with BASE, Arbitrum, among others. Additionally, we are actively partnering with ZK rollups to generate validity proofs, and we will soon unveil collaborations with Caldera and the Altair Layer 2 rollup ecosystem.
What lies ahead for Lagrange following the mainnet launch, and how do you intend to sustain innovation?
Our robust research team, led by our chief scientist Charalampos (Babis) Papamanthou from Yale’s cryptography department, plays a vital role in our journey. Another researcher, Dimitris Papadopoulo, is a professor at HKUST. We aim to adapt our underlying proofing systems as technology evolves, delving into hardware enhancements that include ASIC chips, GPUs, and Fabric’s VPUs.
What advancements do you foresee in ZK-proof technology and the broader blockchain sphere?
The momentum in ZK improvements is evident, with enhancements in hardware acceleration and proofing systems being observed industry-wide. We’re particularly excited about breakthroughs in smaller field technologies like Mersenne 31 and Goldilocks that are accelerating STARKs. We're witnessing significant reductions in recursion times and innovative hardware acceleration efforts with entities like Fabric and Ingonyama, alongside advancements in higher-rarity recursions that permit greater parallel computations.
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