Uncharged approaches for decentralized AI services

When trying to design an uncharged platform for decentralized AI services like the "free" YouTube or Gmail in traditional internet, we need to keep in mind that there is no such thing as a free lunch. So, who is actually paying for the AI services and bandwidth provided by the network miners? Existing decentralized solutions all rely on one-time or monthly micropayments, creating transactional friction that discourages adoption. In practice, we typically see strong consumer resistance to micropayments in favor of no fees, flat fees, or one-time payments. Therefore, to build such approaches, we need to solve the problem of guaranteeing "free" and high-quality services to users while ensuring that network miners are rewarded as they provide an increasing amount of services.

The approach we can take is to draw inspiration from the inflation model of the EOS storage design. In this model, there is a certain percentage of annual inflation on the total coin/token supply of the ecosystem to ensure that miners get paid. Meanwhile the clients will need to lock the platform related coin/token into smart contracts in order to gain allowance of job requests. Service collectively provide the computational power and AI service capacity to those requests. For users to access AI services, they must stake their tokens in the smart contract designated for AI services. Think of this staking process as making a fully refundable security deposit. Users can retrieve their tokens by releasing the service providers from the obligation to provide further AI services to them. This mechanism of staking/locking tokens from the client side will prevent all forms of Sybil attacks, which could flood the system with unlimited requests, halting the system indefinitely. Clients can only secure more service capacity by pledging more tokens to the network compared to other clients.