AI Without Limits: How ZeroG is Building the Future of Decentralized AI
summary
ZeroG claims a working stack: an AI native storage layer, a high‑throughput data availability layer, trusted execution attestations, and an INF (ERC‑7857) that embeds an agent’s private keys into NFT metadata so ownership and revenue are verifiable. The team demonstrates fully decentralized training of a 107B parameter model, says it beats prior work with a 357x throughput improvement using a dual‑optimizer/DooloX approach, and launches mainnet/TGE; token utility covers staking, gas, storage and compute payments.
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chapters (11)
- 0:00Introductions and the Convergence of AI and Blockchain
- 2:05Defining AI Without Limits and Trustless Systems
- 3:43Ownership and the Intelligent NFT (INF) Standard
- 5:17Verifiability, TEEs, and Community Governance
- 5:55Overcoming Scalability and Data Throughput Bottlenecks
- 7:02Training Large-Scale Models Decentralized
- 8:12Future Synergy Between Blockchain Protocols
- 9:29Tackling Data Poisoning and Security
- 10:12Emerging Governance Models: DUNA and DAOs
- 12:25Token Sustainability and Long-Term Utility
- 13:49Mass Adoption and the Future of AI on Web3
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