Archive
135 articles published in this period.
zkML costs 1000x, optimistic schemes cost a challenge window. Hardware attestation verifies AI inference at under 7% overhead and ~$0.26 on-chain — if you're willing to trust Intel. Part 3 weighs the third leg of verifiable inference.
Every on-chain scheme that verifies an LLM by re-executing it and comparing digests assumes a forward pass is bit-for-bit reproducible. It isn't — Thinking Machines got 80 different answers to one prompt at temperature 0. Here's why, and what determinism costs.
DeFi interest rate formulas are open-source reward functions. An RL agent reading Aave's two-slope model can compute the optimal adversarial strategy analytically — no learned reward model required.
Autonomous agents run ~19% of on-chain activity and beat Aave and Morpho at stablecoin yield — yet lose to humans at trading by 5 to 1. The split isn't about model quality. Yield-chasing is a constrained optimization against a kinked rate curve; trading needs alpha agents don't have.
MORPH shows that a TPU v6e8 pod runs NTT at 40× CPU — 10× faster than an H100. The same silicon that accelerates AI inference now accelerates ZK proof generation, and the math that explains it is the same in both cases.
A DataDAO sold your data; you invoke the right to be forgotten. Deleting the file is easy, but the model already learned and the ledger can't be rewritten. ZK-APEX proves the unlearning ran in ~2h; UMA still pulls the 'forgotten' data back at MIA 0.97. Certified isn't forgotten.
A landmark 2025 result: ~250 poisoned documents backdoor an LLM whether it has 600M or 13B parameters — 0.00016% of the tokens. DataDAOs sell 'verifiable' training data, but on-chain provenance proves integrity, not purity. Here's the gap, and what actually narrows it.
An AI agent that retrieves from an untrusted vector DB can't tell the true top-k from a cherry-picked or fabricated one. Re-running the search needs the whole corpus. The 2026 fix: commit the snapshot, then prove the k-th distance is a boundary, not the sort. V3DB proves it 22x faster.
ZKLoRA lets a LoRA seller prove adapter compatibility with your base model without exposing the weights. The verifier checks in 1–2 s — but the prover bears 31–74 s per module, and the protocol is interactive, which puts trustless on-chain settlement just out of reach.
World Chain reserved top-of-block space for verified humans while 382M smart-account ops poured in. We read the Semaphore tree on Ethereum — 17.59M identities, hourly batches at ~3,300 gas each — decode PBH's month-stamped nullifiers, and find the human-only lane sitting almost empty.
Passive AMM liquidity is a short option that arbitrage bots exercise every block. LVR = σ²/8 prices the rent — at ETH's 63% realized vol that's ~5% of pool value a year, and most pools don't earn enough fees to cover it. The math, real numbers, and the auctions clawing it back.
A decentralized GPU network has to answer two questions an AWS invoice never raises: is this the GPU it claims, and did it actually do the work? io.net logged 327,000 registered GPUs and roughly 6,720 daily-verified. We dissect metadata trust, PoW puzzles, performance fingerprinting, and zkGPU-ID.