Archive
135 articles published in this period.
Permissionless training networks pay peers for gradients they can't re-run. Proof-of-Learning was meant to verify the work — until it was forged for 3% of the training cost, then for one floating-point op per weight. Here's the mechanism, the attacks, and what's deployed instead.
Wire an LLM into a Governor contract and the proposal text becomes the attack surface. A frozen-weights ablation finds the twist: turning on deliberation drops adversarial robustness from 100% to 68.5% — and the 226s it takes to think is itself extractable value.
DataDAOs promise to pay you for your data — but 'pay you fairly' hides a cooperative-game problem that's O(2ⁿ). Inside Data Shapley, the KNN trick that makes it tractable, why rankings flip under SGD noise, and what Vana's Proof of Contribution actually computes instead.
DX Terminal Pro ran 3,505 LLM agents trading real ETH on Base for 21 days: 7.5M invocations, ~$20M volume, 99.9% settlement. The reliability came from the operating layer around the model, not the weights — here are the numbers and the failure modes.
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.
An agent doesn't need its key stolen to drain a wallet — it can be talked into signing. CrAIBench shows memory injection beating prompt injection 55% to ~0% on the strongest model, and only fine-tuning closes the gap.
Majority voting over LLMs throws away the one node that got it right. Fortytwo's swarm inference ranks answers pairwise instead — +17 points on GPQA Diamond — with on-chain reputation and proof-of-capability for Sybil defense. The mechanism, the math, the tradeoffs.
Most 'on-chain AI' keeps the model off-chain and posts a proof. But you can also just run the forward pass in Solidity. We do the gas math — ~106k gas per weight, an MNIST net that needs 180 Ethereum blocks — and find the thin band of models that fit.
An AI agent that acts on your bank balance has to prove it saw that balance — without a trusted API. zkTLS turns any HTTPS session into a portable proof. We dissect MPC-TLS vs proxy vs TEE, the real TLSNotary benchmarks, and read Reclaim's on-chain verifier on Base down to its single attestor.
zkML, optimistic, TEE, FHE all prove the computation. Restaking takes the other road: bond it and slash liars. We do the cost-of-corruption math behind EigenLayer's $18B AI-AVS security, the overloading attack that breaks it, and the probabilistic-audit tax.
Yesterday an AI agent deployed a prediction market on Gnosis; other agents will price it, bet on it, and resolve it. The calibration data behind LLM forecasters, the FPMM math they trade against, and what breaks when the marginal bettor is a model.
Story raised $140M to make IP programmable for the AI era. We read its chain: 6.46M registered IP assets, 230,300 licenses ever minted, one week of royalties totaling $10 — plus the LAP/LRP royalty math and the precompile at 0x0101 that computes the graph.