Archive
13 articles published in this period.
Olas turned an off-chain AI task into an on-chain contract: 2.1M requests across 100 mechs, a 60-300s priority window, and a Karma ledger that docks no-shows. We read the marketplace off Gnosis and dissect its crypto-economic SLA.
You pay per token for a named model; the provider picks the precision. FP8 quantization costs 0.6 MMLU points and is near-invisible to output auditing — so inference markets bond and attest instead of detect.
An LLM agent that writes its own working smart-contract exploit isn't hypothetical: A1 hits 63% on real exploited contracts and once pulled $8.59M from a single bug. The economics are the story — at a few dollars a scan, attackers profit at a tenth the contract value defenders need.
Most decentralized-AI networks vote or average. Allora bets the network should learn whom to trust per context — using forecasters that predict who's about to be wrong, mapped to weights through a softplus gradient. We dissect the mechanism, the math, and where it pays.
You can copy open model weights bit-for-bit, so on-chain ownership can't be cryptographically enforced — only proven. Sentient's answer: fine-tune 24,576 secret key-response fingerprints into the weights and make scale the security parameter.
Virtuals' Agent Commerce Protocol sells an independent evaluator as the thing that makes agents trust each other's work. We read 62,882 jobs off Base — and in a 30-job sample, every one let the buyer grade itself. Not one used a third party.
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.
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 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.
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.
AI agents now resolve most prediction markets straight off the web — UMA's bot hits 99.3% on sports and 72% on mention markets. The optimistic oracle's dispute game is the backstop, but it only catches errors someone is paid to catch. The numbers, and the silent-settlement gap.
A DeFi liquidation mints a fixed prize, and for years it went to whoever won the gas war, not the protocol. Aave's own data shows Chainlink SVR routing $675M of liquidations and clawing ~$16M back. Inside the recapture-auction mechanics — SVR, Oval, API3 — and what they don't fix.