illicit finance; SNARKs; costs of market-making in DeFi, more metrics
1. *special feature*: Building blocks - SNARKs
A SNARK (Succinct Non-interactive Argument of Knowledge) is an important cryptographic primitive that has many applications in web3 — from scaling blockchains (e.g., L2 rollups) to ensuring privacy (e.g., zero knowledge). The original concepts behind SNARKs were introduced in the 1980s, with celebrated theoretical results through the 1990s… But in the last decade, they have jumped from theory to practice: Applications include enabling computationally weak devices to offload security-critical work onto powerful remote servers; running a web application on an untrusted provider; or even implementing verifiable ASICs.
In web3, SNARKs let someone “prove” to an untrusting “verifier” (such as the Ethereum blockchain) that they know some data satisfying certain properties (such as a batch of valid transactions whose execution leads to a given global state). While the costs to the verifier are modest, how about the costs of the prover? Understanding this is key to scaling applications of SNARKs in practice, so computer science professor Justin Thaler outlines how to estimate, measure, and reduce SNARK performance costs.
watch video on SNARK design part 2 – rollups, performance, security
read Thaler’s textbook for more on ‘proofs, arguments, and zero knowledge’
a16z crypto head of research Tim Roughgarden on the “magic” of SNARKs; why they matter for web3 infrastructure; and how fundamental theoretical work can shape technology several decades later… more in this thread
2. signal vs. noise: Crypto regulations, illicit finance, privacy… and beyond
Michele Korver, Jai Ramaswamy, and Sonal Chokshi
In this deep-dive episode of ‘web3 with a16z’, we:
tease apart the facts vs. the buzz around recent news that government authorities sanctioned Tornado Cash and arrested a developer for allegedly laundering proceeds of cybercrimes [first third];
discuss the difference between obfuscating vs. privacy-preserving technologies, and why that matters in the big picture; and
share evergreen frameworks — that go well beyond recent events — to help crypto developers navigate various ongoing regulatory and compliance requirements, while still ensuring innovation. What’s the alphabet soup of different government entities to know? When (and who) should startups hire to resource compliance and more? And what should both regulators and entrepreneurs know when engaging with each other? [second half]
3. web2 to web3: Status mobility in networks
As more people explore social applications in crypto, a key conversation is what makes social networks work (and not work). So a16z crypto general partner Sriram Krishnan shares some lessons learned from time spent in web2 companies, emphasizing that product builders should also manage various status indicators in networks. Because naive implementations of such status indicators — karma points, follower/like counts, XP, verified badges, leaderboards, and so on — results in the fatal flaw of concentrating status in just a few “status rich” users… Which means newcomers have a bad experience, and also leads to long-term network decay. How can builders encourage more status mobility in social networks?
*special theme* metrics & measures:
4. Measuring the cost of market-making in DeFi
with Tim Roughgarden
In traditional finance, participants rely on order books, brokers, centralized exchanges, and other market-making intermediaries to help them trade and hold their assets (including granting those intermediaries access to their personal information to do so). But in decentralized finance (DeFi), math and code enable liquidity providers to pool assets — for a share of transaction fees and/or tokens — through automated market makers (AMMs), allowing anyone to transact directly on decentralized exchanges.
But in such decentralized finance systems, what’s the cost of providing liquidity to an AMM? A new paper from Jason Milionis (Columbia University), Ciamac Moallemi (Columbia University), Tim Roughgarden (a16z crypto & Columbia University), and Anthony Lee Zhang (University of Chicago) answers this question with a new running-cost metric called loss-versus-rebalancing (LVR), or “lever” for short. Unlike the traditional (but widely criticized) metric of “impermanent loss”, LVR isolates the adverse selection/ information costs of liquidity provision, independent of any market risk component. The authors also suggest how LVR can inform liquidity provision decisions, and the design of AMM protocols.
5. Measuring blockchain performance
Performance and scalability are much-discussed challenges in the crypto space — relevant to both Layer 1 projects (independent blockchains), and Layer 2 solutions (like rollups and off-chain channels). We don’t have standardized metrics or benchmarks, which not only makes it difficult to accurately compare projects, but also often obscures what matters most in practice. Since evaluating blockchain performance fairly and accurately is hard, we need a more nuanced, thorough, and multi-dimensional approach, argues a16z crypto research partner Joseph Bonneau. So what are the challenges — and some guidelines & key principles — to keep in mind here?
…when Salvador DALL-E met Diffie, Hellman, & Merkle
--Sonal Chokshi, Tim Sullivan, Robert Hackett, Stephanie Zinn, and a16z crypto team
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