arXiv (All)
open access
Werracle: Sub-Cent Intra-Block AI Reflex Oracles and Flash-Loan Circuit Breakers for EVM Smart Contracts
Contemporary on-chain artificial intelligence (AI) encounters an intractable Von Neumann memory and latency wall. Storing static floating-point neural weight matrices inside Ethereum Virtual Machine (EVM) storage costs millions of gas, rendering direct on-chain inference impossible. While Zero-Knowl
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Grainful Holding Ltd v Mineev [2026] EWHC 2007 (Comm) (10 July 2026)#991151
- AI Hardware Accelerators for Large Language Models: Architectures and the Memory Wall#784815
- AI Hardware Accelerators for Large Language Models: Architectures and the Memory Wall#783225
- SonicDB S6: A Storage-Efficient Verkle Trie for High-Throughput Blockchains#2755
- The Synergy of Generative AI and Big Data for Financial Risk: Review of Recent Developments#688578
Record · ID 1105278
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive