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Utilities

Token goal​

The incentive structure must consider a form of value accrual from the clients (users of the data) and redistribution of that value in the form of liquidity for the PGPT token which makes it attractive for the node holders and other stake holders within the ecosystem. Token is also considered to be the primary form of payment for the usage of the data or the AI trained with the data to the data creators.

Utilities:​

  • Value accrual

    The PGPT token will gain value through various mechanisms, including:

    • Buyback and burn: The project will repurchase PGPT tokens from the market and burn them, reducing the total supply and increasing the value of remaining tokens. With fewer tokens available to trade, buyers must bid up the price to acquire them. The buyback and burn schedules will align with the project's market-making strategy based on prevailing conditions and token performance. Token burning entails sending tokens to a null address that no one can withdraw tokens from.
    • Investor liquidity: As more investors purchase and hold PGPT tokens, the token's value will rise, increasing demand.
    • Fee retention: Fees received from transactions within the network, such as payments for transactions, AI analytics, and data usage, will be partially retained by the project and used to buy back and burn PGPT tokens, reducing supply and increasing token value.

  • Payments for AI analytics

    The system includes a SaaS subscription model where clients pay a monthly fee for using AI services. Each time a call is made, a reward is distributed to the data providers whose data is used to service the particular query. Part of the awarded tokens is distributed to the data storage providers whose storage was used to host the particular data. This mechanic intends to incentivize data providers to keep their data available and up-to-date, and to ensure that the AI is trained on the most relevant and accurate data possible. Treasury also collects a fee for the payment.

  • Payment for data usage (retrieval payment)

    When a client purchases access to data from a data provider, a fee is paid for the data usage to the data provider. Part of this fee is distributed to the node storage providers as a reward for keeping the data available for retrieval at all times. The remaining part of the fee goes to the treasury.

  • Staking of tokens by nodes to ensure commitment (incentive against malicious behavior)

    This is a mechanism that incentivizes node holders to maintain nodes and provide data storage capacities for the platform. Node holders that stake tokens are required to keep their nodes active and maintain a certain level of performance. Should they fail to meet these requirements, they risk losing their staked tokens. This provides a disincentive for malicious behavior and ensures that the platform functions effectively and efficiently. The goal of validators within a network is to retain data for unlimited stretches of time. PrivateAI has implemented a node replacement mechanism which is directly connected with staking. In the event that an unresponsive node is identified, it is excluded from the network via the burning of staked tokens. Additionally, nodes that stake tokens are eligible for rewards in the form of additional tokens or other benefits. These further incentivize them to maintain their nodes and contribute to the platform's success.

  • Reward for writing a scientific article

    This is a mechanism that incentivizes scientists to contribute to the ecosystem by producing high-quality research and publishing it. This mechanism can take various forms, such as awarding tokens for peer-reviewed publications, offering grants or fellowships to support research. The goal of this mechanism is to promote innovation and advance scientific knowledge within the ecosystem, while also providing incentives for researchers to engage with the PrivateAI and contribute to its growth and development. By providing rewards for scientific articles, PrivateAI aims to attract top talent and foster a vibrant research community that can help drive the platform forward. The size of the work reward allocated for the article is calculated according to the formula which incorporates an adjusting coefficient which is set depending on the quality and value (qualification) of the study.

  • Reward to DAO reviewers for analyzing articles

    The quality of each submitted article is graded by the DAO Reviewers. Each quality grade has a corresponding qualification coefficient, which affects the amount of remuneration received by the author of the submission, i.e. by scientists. Tokens are paid to reviews from Treasury and incentivize them to take part in analyzing articles, providing professional estimate of their quality. This is an important step in rewards mechanism because all scientists should be paid fair corresponding amount of tokens for their papers. Scientists should understand that their remuneration depends of the quality of work which is confirmed by independent board of professionals. Thus, rewards for reviewers create a mechanism of openness and fairness.

  • Retrodrop

    Retrodrop is a mechanism that provides incentives to early adopters of a protocol. This mechanism can take various forms, such as providing rewards for participation or giving a status of "early bird" for target actions of scientists and clients. Retrodrop aims to stimulate participation in the protocol at early stages and to ensure that the protocol functions effectively and efficiently. The mechanism can include rewards in PGPT tokens from the project to data storage providers in case clients' demand is low, or rewards in tokens for scientists which provided data at early stages. Retrodrop is one of the mechanisms that incentivizes people to take part in a protocol at early stages and fosters a sense of belonging, encourages ongoing participation, and facilitates networking with other data providers and industry professionals.

  • Bandwidth Fees – pay for the bandwidth you use when you upload or download files. This can also include wear and tear fees set by the host to help pay for their physical storage devices. (Sia inspired)

    This mechanism allows users to pay in token to accelerate a upload or download of necessary data. The purpose of this mechanism is to incentivize users to use the network efficiently, while also enabling storage providers to receive compensation for the resources they provide. The fees may be set by the network or negotiated between the user and the storage provider through an auction mechanism.

  • May include mechanic to give vePGPT tokens against locked PGPT tokens in order to give opportunity for yield farming

    The vePGPT token mechanism is designed to incentivize users to lock their PGPT tokens for a period of time, creating a yield farming opportunity. When users lock their PGPT tokens, they will receive vePGPT tokens in return, which represent their locked tokens. These vePGPT tokens can then be used to participate in yield farming activities, such as staking in a yield farming pool. The longer the tokens are locked, the more vePGPT tokens are earned, increasing the yield farming potential. This mechanism is intended to encourage long-term holding of PGPT tokens and increase their value over time.

  • Payment for services in Private AI ecosystem (roadmap)

    The payment for services mechanism is a planned utility within the PrivateAI ecosystem that will allow clients to use PGPT tokens for various services and products offered by the protocol. At initial stage this includes paying for data storage, AI analytics, and data usage. The mechanism is intended to incentivize clients to accumulate tokens and hold onto them long-term, as there will be exclusive features and services available only to those who hold the token. Additionally, the mechanism is designed to provide liquidity for the PGPT token, making it more attractive for node holders and other stakeholders within the ecosystem. The payment for services mechanism will be flexible and able to accommodate new products and services as the platform develops.

  • Utilities for clients to incentivize them to accumulate tokens:

    • Staking with long locking period. A client lock tokens for 6+ months and gain passive income upon them. This mechanism incentivize clients to buy more tokens and hold them for long.
    • Exclusive Access and Features: Token holders could gain exclusive access to certain features or services within the PrivateAI. This might include early access to new research findings, privileged access to certain data sets, or participation in exclusive events or conferences. These perks motivate clients to hold tokens long-term to enjoy these benefits.
    • Loyalty Programs and Discounts: PrivateAI could introduce loyalty programs or provide discounts on services or products within the ecosystem for long-term token holders. This encourages clients to retain their tokens as they can avail themselves of various advantages, rewards, or discounts that enhance their experience and provide added value.
    • Recognition and Community Engagement: PrivateAI ecosystem can recognize big holders through various means, such as badges, certifications, or featured profiles. This recognition fosters a sense of belonging, encourages ongoing participation, and facilitates networking with other data providers and industry professionals.

  • Utilities to incentivize people to take part in a protocol at early stages:

    • Rewards in PGPT from project to data storage providers in case clients' demand is low
    • Give a status of ‘early bird’ for target actions of scientists and clients. This status will bring benefits in the future. For example, retrodrop or discounts.
    • Give free access to AI analytics
    • Reputation and Trust Scores: The protocol can establish reputation systems or trust scores for data providers based on the quality, accuracy, and consistency of the data they provide. Higher reputation scores can lead to increased rewards and recognition within the ecosystem, encouraging data providers to maintain a good reputation by offering reliable data. At early stages scientists with good reputation will receive tokens from an additionally created pool.
    • Recognition and Community Engagement: PrivateAI ecosystem can recognize long term holders through various means, such as badges, certifications, or featured profiles. It is much beneficial to take part in early stages to gain a recognition badge faster. This fosters a sense of belonging, encourages ongoing participation, and facilitates networking with other data providers and industry professionals.fits.