The Proof Batch
Gas cost vs. number of AI inference proofs under three aggregation strategies: naive per-proof (linear), SnarkPack O(log N), and ZK recursion (flat). Drag the slider to find the crossover where each strategy wins.
Lab
138 explorable, interactive pieces — every concept we write about, made tangible.
Gas cost vs. number of AI inference proofs under three aggregation strategies: naive per-proof (linear), SnarkPack O(log N), and ZK recursion (flat). Drag the slider to find the crossover where each strategy wins.
A data market can't pay you for your data's value AND protect it with one privacy budget ε. Drag ε: the worst-case leakage bound hits ≈100% by ε=8 — exactly where from-scratch models finally become usable. Real attacks sit far below the bound, and that gap is your only cover.
Every route to trustworthy AI inference, priced on one log axis: TEE attestation at 1.07×, optimistic re-execution at 2–4×, zkML and FHE at 10³–10⁵×, verifiable FHE beyond. Hover, tap, or arrow through the bars to see what each overhead actually buys — and whom you still trust.
Four guardrail tiers for on-chain AI agents: probabilistic classifiers through Lean 4 theorem provers. Select an attack scenario to see which tier catches it — and which let it through.
An on-chain agent is told to pay an invoice, but one MCP tool hides an instruction in its description that redirects the transfer to an attacker. Pick a defense layer — model, tool, client, policy, custody — and run it; alignment alone refused under 3% of these in MCPTox.
Pipeline-parallel decentralised post-training, split across four nodes. Click any internal stage to place the compromised node — the task-vector injection indicator and attack metrics update to show 94% ASR collapsing alignment from 80% to 6%.
Real reasoning-token embeddings cluster tightly in projected 3D space; phantom billing tokens scatter as noise outside the CoIn detection boundary. Toggle inflate to inject phantom tokens and watch 94.7% get flagged outside the wireframe sphere. Drag to orbit.
Three agentic payment protocol architectures—AP2, TessPay, and On-Chain ERC-4337—shown as flow stages. Toggle Attack Mode to highlight where prompt injection compromises each design. Click a column to inspect protocol details.
Compare Chainlink's push oracle price against Pyth's pull price and live spot. Drag the slider to see exactly when the 0.5% deviation threshold triggers an on-chain update.
Where reliability comes from in on-chain LLM trading agents, over DX Terminal Pro's production run: model upgrades move swap success 87% to 96%, but the operating layer takes the same weights to 99.9%. Switch panels for the prompt fixes that erased three failure modes. Tap or arrow the bars.
The six stages of an ERC-4337 UserOperation — from construction by an AI agent to paymaster settlement — with the actor, failure modes, and gas cost at each step.
Under secure two-party inference, a transformer's cost is eaten by Softmax and GELU, not the matrix multiplies. Stacked per-operation communication and interaction rounds for one BERT-base block across Iron, BumbleBee, and Nimbus — the nonlinear activations are 80–95% of the bill.