Question 1

What is DecideAI (DCD)?

Accepted Answer

DecideAI (DCD) is an artificial intelligence (AI) ecosystem designed to facilitate the development, refinement, and deployment of high-performance, specialised Large Language Models (LLMs). The platform addresses the limitations of general-purpose, centralised AI models by focusing on targeted, domain-specific solutions across industries such as healthcare, finance, and media.

The DecideAI ecosystem consists of three core components:

* **Decide Protocol:** A platform that coordinates human and artificial intelligence to annotate, train, and continuously refine specialised LLMs using Reinforcement Learning with Human Feedback (RLHF).
* **Decide ID:** A verification system employing Proof of Personhood (PoP) to ensure data contributors are authentic and credentialed, enhancing the quality and traceability of data.
* **Decide Cortex:** A platform providing access to pre-trained LLMs and curated datasets for developers and organisations via direct purchase or API.

Question 2

What is DecideAI (DCD) used for?

Accepted Answer

The DCD token functions as the native utility token within the DecideAI ecosystem, supporting a range of activities:

* **Incentivising Participation:** Contributors are rewarded in DCD for providing high-quality data annotations, participating in model refinement, and enhancing ecosystem infrastructure.

* **Funding Innovation:** Developers and researchers receive DCD incentives for creating new AI models, improving datasets, and developing external applications using DecideAI infrastructure.

* **Ecosystem Transactions:** DCD is used for transactions within the ecosystem, including accessing AI models, datasets, and computation resources.

* **Collaboration and Governance:** DCD supports decentralised collaboration, allowing stakeholders to contribute to ecosystem growth and sustainability.

Question 3

DecideAI Ecosystem Components

Accepted Answer

1. **Decide Protocol**:
   - Facilitates the collection, annotation, and refinement of datasets for LLM training.
   - Employs RLHF, integrating human feedback for model accuracy and domain-specific customisation.
   - Incentivises contributors via a reward system using DCD tokens.

2. **Decide ID**:
   - Utilises a Proof of Personhood (PoP) methodology to verify contributors' identities and credentials.
   - Ensures that data contributors are unique, credentialed, and traceable.
   - Employs Zero-Knowledge Proofs (ZKPs) for privacy-preserving verification.

3. **Decide Cortex**:
   - Provides access to pre-trained LLMs and curated datasets for direct use or integration via APIs.
   - Supports model customisation and post-deployment management.