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Wyatt Benno

Wyatt Benno

https://icme.io/

Verifiable AI: Moving From a Black Box To a Glass House.

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Succinct Verification, The Key to AI.

It may seem presumptuous for someone steeped in cryptographic proof systems to claim insight into the future of AI. After all, if there’s a better path forward, why not just build it and let the results speak for themselves? Fair. But some problems are structural — and it’s precisely

Proof Parties - zero knowledge proofs with friends.

Today we’re introducing Proof Parties — an interactive way to use zero-knowledge proofs from your browser and beyond. Get together with your friends to use cutting-edge tech, compete, and earn points. Proof Parties also doubles as a decentralized science suite, where the underlying “win” conditions are determined fairly — based on

If A 'ZK'-Prover Network Asks For Your Data. Don’t Give It to Them.

When many users hear the term zero-knowledge proofs (ZKPs), they assume privacy is built-in by default. After all, “zero-knowledge” sounds like it means “no one knows my data,” right? Wrong. In reality, many ZK prover networks don’t care about privacy at all — they care about speed. The dominant model

Pick, Prove, Profit: The NIVC Singularity.

Incrementally Verifiable Computation (IVC) was first introduced by Valiant in his seminal 2008 work. This groundbreaking concept enables recursive proof systems to tackle long proving tasks by breaking them down into incremental steps. While transformative, the original implementations relied on a universal circuit, meaning the same circuit was repeatedly proven

zkGPU - On the State of the Art for Verifiable Compute of GPU Execution.

*This post is about verifying the computations run on GPU. Not using GPUs to accelerate ZKP! GPUs are having a long — moment in the spotlight. Often celebrated for their prowess in rendering lifelike graphics, GPUs now sit at the heart of some of the most demanding computational tasks in modern

Minimal Space, Maximum Pace: How memory efficient zero-knowledge proofs work

In the rapidly evolving world of blockchain and cryptography, we often hear about blazing-fast zero-knowledge virtual machines (zkVMs) designed to scale Ethereum or tackle large-scale computational problems. However, for true privacy, ZKPs need to run locally. This concept, known as local verifiable compute, involves implementing extremely space-efficient ZKPs for use

Proof Composition Using Zero-Knowledge Virtual Machines: #RunawayZK

Zero-knowledge proof (ZKP) systems often require composition with other ZKP systems to achieve specific traits, such as privacy or improved on-chain verification (e.g., Groth16). Traditionally, this process involves cryptographic experts meticulously converting the verifier of one system into an arithmetic circuit for use in another. This labor-intensive task is

Approaching Constant: The Race for The Fastest Zero-Knowledge Proof System.

Humans have an insatiable desire for speed. From supersonic jets to rockets that breach Earth's atmosphere, we constantly strive to go faster. This obsession with velocity extends to the realm of zero-knowledge proof (ZKP) systems, where we crave for our proofs to run as swiftly as the programs

The cost of composition: an exploration in the state of the art for foreign field arithmetic in zero knowledge proofs.

'Foreign field' or 'non-native field' arithmetic appears everywhere in zero knowledge proof systems. If you want to use ZKP for boolean operations, public-key cryptography, or proof composition you will undoubtedly run into the constraint blowup due to foreign field work. However, if you look into open-sourced