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    • ⚖️AI DAO
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  • Overview
  • Scope & purpose
  • Governance mechanism and voting
  • Strategic objectives
  • Example proposals
  • Future plans
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  1. The Technology

AI DAO

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Last updated 2 months ago

Overview

The D3L DAO is the cornerstone of our AI governance, dedicated exclusively to managing and guiding all machine learning activities across the Deep3 Labs ecosystem. From the very first model update to ongoing enhancements in data pipelines and token economics, the DAO ensures that every decision related to AI development is made transparently and with community involvement. Rather than ceding full control over the entire business, we have chosen a focused approach—starting with the AI/ML operations—to build trust, share value, and gradually transition more control to the community as our collective expertise grows.

Scope & purpose

The primary function of the D3L DAO is to democratize the AI development process. It does so by allowing community members to review, validate, and vote on key proposals regarding new model implementations, data integrations, and enhancements to our technical infrastructure. For instance, when Deep3 Labs updates a model, the new version is not pushed live automatically; instead, our system listens for a passing governance vote, and only then is the updated model deployed via the API. This rigorous, community-driven process ensures that all significant AI-related changes are subjected to collective scrutiny, thereby preserving the integrity of our AI products while protecting proprietary trade secrets.

The DAO’s mandate is intentionally narrow at inception, covering decisions directly related to AI/ML activities. However, its scope will gradually expand to include strategic treasury functions such as setting fees, determining royalties, and managing token emissions—all critical components that align with our mission to share the value generated by our technology.

Governance mechanism and voting

The D3L DAO operates on a robust governance framework powered by a dedicated governance token. This token is not only essential for casting votes but also serves as an incentive mechanism to reward active and valuable participation. To prevent voting power from being overly concentrated among wealthy stakeholders, we are exploring advanced mechanisms such as quadratic voting, ensuring a fair and balanced decision-making process.

The governance process is designed to be seamless and automated. Once a proposal receives the requisite support from the community, our smart contract system automatically triggers updates, such as pushing new model data to the API. This integration of automated workflows with decentralized decision-making underscores the DAO’s critical role in maintaining the agility and responsiveness of our platform.

Strategic objectives

The strategic objectives of the D3L DAO are multifaceted:

  • Transparency and Accountability: By opening up key aspects of the AI/ML pipeline to community oversight, the DAO ensures that model development, performance metrics, and data integration practices are transparent and accountable.

  • User Empowerment: The DAO provides users with a direct pathway to influence how AI models are built and deployed, thereby enhancing user agency in an industry where opaque processes are the norm.

  • Sustainable Value Sharing: Through governance over fee structures, royalties, and token emissions, the DAO ensures that the value generated by our AI models is equitably shared among all ecosystem participants.

  • Risk Management: The incremental approach to ceding control helps mitigate risks by balancing innovative decentralization with the need to protect sensitive operational details and trade secrets.

  • Continuous Improvement: The DAO’s iterative review process, including automated updates based on governance votes, ensures that the Deep3 Labs platform remains at the cutting edge of AI/ML technology.

Example proposals

To illustrate the DAO’s scope and decision-making process, here are some examples of the types of proposals that may be brought forward for community consideration:

Model implementation decisions
  • Based on the attached model summary and performance metrics, should model X developed by Deep3 Labs be deployed to the live API?

  • Project X has integrated model Y and has been using it for purpose Z. Should this configuration be permitted as part of our standard offering?

Data integration and pipeline enhancements
  • Deep3 Labs has recently gained access to data source X containing critical market insights. Should we integrate this data into our existing pipelines to improve model performance?

  • Should we partner with external data provider Y to enhance our model's performance by incorporating additional real-time data feeds?

Quality assurance and model removal
  • Model X, submitted by user Y, does not meet its stated performance claims according to evidence Z. Should it be removed from the marketplace and its associated collateral released for indemnification?

  • Given recent performance data indicating a significant shift in market conditions, should the parameters of model X be re-evaluated and updated to better reflect current trends?

Token economics and treasury proposals
  • The current price per API call is set at X tokens. Should this rate be adjusted to Y tokens to better reflect market demand?

  • Should the royalty rate for independent model submissions be increased from X% to Y% to incentivize broader participation?

  • Currently, gD3L token holders earn uD3L tokens at a rate of X%. Should this rate be modified to optimize both user rewards and platform sustainability?

Future plans

While the initial focus of the D3L DAO is strictly on AI/ML activities, its role is expected to evolve significantly as our community matures and as the broader ecosystem gains a deeper understanding of decentralized governance in AI. In the future, we envision the DAO taking on additional responsibilities such as overseeing broader operational decisions, updating the token economics, and even engaging in strategic partnerships. As these changes are implemented incrementally, each expansion will be carefully managed to ensure that the benefits of decentralization are realized without compromising the operational integrity or security of the platform.

In summary, the D3L DAO is not just a governance tool—it is a foundational element of our mission to democratize AI. By giving users a direct voice in how models are built, validated, and deployed, the DAO transforms passive consumers into active participants in shaping the future of AI/ML. This pioneering approach not only enhances transparency and accountability but also drives sustainable growth by ensuring that the value generated by our technology is shared equitably across the entire ecosystem.

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