The crypto market often faces skepticism regarding the lack of real application scenarios, while the AI field is racing ahead in a competition of computing power and models. The two tracks seem parallel, yet they are experiencing a violent collision through Google DeepMind's latest paper (Distributional AGI Safety).
This paper is not only an academic discussion on AI safety but also a covert investment guide for the AI x Crypto track. It proves with the most hardcore academic logic that the future of general artificial intelligence (AGI) must operate on infrastructure similar to Web3.
For investors, this marks a significant shift from air narratives to rigid demand. The following are the four core investment logics based on the paper breakdown:
Logic one: The form of AGI determines its need for the DeFi market.
The future AGI is likely not a single super brain, but a patchwork AGI. The paper points out that AGI may initially appear as a patchwork system, distributed among network entities. This is a distributed network composed of countless specialized agents with complementary skills, where general intelligence emerges through collaboration.
Since the essence of AGI is a collaborative network of countless agents, they must engage in high-frequency resource exchanges. Agents need to perform service routing and transactions based on their respective specializations, such as data acquisition or code execution.
There are huge investment opportunities here: the agent economic model and trading market. Traditional fiat payments are too slow and expensive, focusing on high-throughput, low-latency high-performance public chains (L1/L2) and protocols dedicated to machine-to-machine micropayments will become the lifeblood of the AI economy.
Logic two: Trust cannot rely on human review but must depend on staking.
In an anonymous and high-frequency agent market, traditional reputation systems fail. The paper explicitly proposes the introduction of a stake-based trust mechanism.
Agents need to deposit assets into a custodial account as collateral (Bond) before executing tasks, which is a form of staking. Once independent supervisors verify malicious behavior, smart contracts will automatically execute forfeiture, and funds will enter the insurance pool or be compensated to the victims.
This is the most mature way of Crypto (PoS) being directly reused in the AI field. DeepMind is actually calling for a financial margin system for agents. A protocol that can provide permissionless staking services for AI agents and automatically execute liquidation in case of violations will lead to an explosion. This is the performance guarantee insurance in the AI world.
Logic three: Governance cannot rely on laws but must depend on smart contracts.
In the face of massive machine interactions, human supervision is ineffective. It is necessary to use smart contracts to automatically verify task results and execute settlements. The paper even directly uses the term smart contracts, suggesting that they be used to programmatically encode payment terms and task constraints.
At the same time, the paper points out that traditional smart contracts cannot assess the non-deterministic outputs of AI, so it is necessary to introduce AI judges as oracles to determine whether contract conditions are met.
This means that the contract layer and oracle layer will capture tremendous value. Public chains that carry agent interaction protocols and next-generation oracle networks that can convert complex off-chain AI reasoning results into on-chain verifiable results are essential bridges connecting AI and blockchain.
Logic four: Identity and audits need an immutable ledger.
To prevent witch hunting, agents need to have unique identities based on public key encryption and be registered in tamper-proof market directories. This is actually the decentralized identity (DID) we are familiar with.
To ensure accountability afterward, all interaction logs must be recorded on a cryptographically secured, append-only ledger. Entries need to be hash-linked to ensure immutability.
Massive AI interaction logs cannot exist on easily tampered centralized servers; they must be on-chain. Decentralized storage networks focused on data availability and permanent storage will become the black box of AI. Furthermore, the paper mentions a taxation mechanism for information pollution, similar to dynamic gas fees, using economic means to govern data abuse.
Conclusion: Web3 is the physical economic infrastructure of AGI.
If you are still looking for the next large-scale application of Crypto, shift your focus away from humans. The next billion-level users may not be humans but AI agents.
DeepMind's paper shows us a future where silicon-based life forms survive, trade, and evolve in a virtual agent economy built on cryptography, smart contracts, and game theory.
Agents need wallets, identities, contracts, and collateral to prevent malfeasance. For investors, when a Web2 giant like Google starts planning AI security with Web3 logic, it means that the infrastructure sector of AI x Crypto has transitioned from conceptual hype to a definite industrial trend.