Sign in Subscribe

Wyatt Benno

Wyatt Benno

https://icme.io/

Agentic Commerce - the hack waiting to happen.

There's a fundamental problem with AI security today. The tools we use were never designed for the world we're rapidly entering, a world where AI agents don't just assist humans, but transact autonomously with each other at machine speed, preferably with no human in

Trustless Agents can't work without Trustless Agentic Memory.

Your agent just made a million-dollar decision based on 'memories' it pulled from a vector database. A TEE attested that the computation was correct. But can you prove they used the right AI memory? Introducing Kinic-CLI: zkML powered Trustless Agentic Memory (zkTAM).

The Definitive Guide to ZKML (2025).

AI systems are making decisions that move money, affect health outcomes, and control autonomous agents. But how do you verify that an AI actually computed what it claimed to compute? That it used the model it promised to use? That it didn't leak your data in the process?

Trustless Agents — with zkML

Ethproof's quest to verify Ethereum blocks in real-time can also be leveraged in a similar race for near real-time verifiable compute for trustless agents — here's how.

Sumcheck good. Lookups good. JOLT good. Particularly for zero-knowledge machine learning.

TL;DR: We made zkML 3-7x faster than everyone else. Here's how. Standing on the shoulders of giants The a16z crypto research team recently dropped some serious heat with their 6x speedup announcement, showing how JOLT's lookup-based approach with sumcheck protocol can dramatically outperform other SNARK

Verifiable AI Memory — When AI Remembers, Who Controls the Truth?

The future arrived, and it tastes like corporate surveillance. AI can now remember a lot about you. Not just your conversation from five minutes ago, but you — your preferences, your quirks, the embarrassing thing you asked about cryptocurrency in March. AI memory is not only a blossoming set of features,

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

▓▓▓▓▓▓▓▓▓▓▓ ░░░░░░░░░░░ ▓ ▓ ░ ░ ░ ▓ ? ▓ ░ P ░ R ░ ▓ ▓ ░ ░ ░ ▓ ▓ ░░░░░░░░░░░ ▓ ▓ ░ O ░ O ░ ▓ ▓ ░ ░ ░ ▓ ▓ ░░░░░░░░░░░

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

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