Introducing Augment-to-Earn (A2E)

Introducing Cryptomate's Augment-to-Earn System

Read more HERE about Human-In-The-Loop (HITL) for LLM applications.

Traditionally, HITL systems have focused on tasks such as validation and correction, where human agents verify the accuracy of AI outputs. However, as AI technologies, particularly generative AI, have advanced, the role of human agents has expanded to include augmentation—enhancing and refining AI outputs to achieve higher quality and more nuanced results. This evolution has paved the way for new incentive structures that reward human contributions, leading to the concept of “Augment-to-Earn.”

Augment-to-Earn is a novel incentive mechanism within the HITL framework, where human agents are rewarded for their active participation in modifying, validating, and enhancing AI-generated content. This approach recognizes the value of human expertise and feedback in improving AI performance and offers cryptocurrency or other digital assets as compensation for these contributions.

How It Works

Cryptomate's augment-to-earn system operates through a series of interconnected steps. It begins with Task Generation, where AI-generated responses to user queries are screened for sensitive content. When detected, the system creates augment-to-earn tasks, either real-time or review, and broadcasts them to CMA token stakeholders known as Augmenters.

In the Human Augmentation phase, these expert Augmenters, who are sophisticated investors and crypto experts, engage with tasks. They can either select the best existing completion or input their own, leveraging their deep knowledge of the crypto ecosystem.

The Completion Selection process follows, where Augmenters vote on candidate completions. These votes are weighted based on CMA token stake, with the highest-voted completion chosen as the final answer.

The Acceptance step varies by task type. Feedback tasks are judged by end-users, prediction tasks are evaluated against future outcomes, and poll tasks are assessed through Augmenter consensus.

Finally, Reward Distribution occurs. Augmenters supporting accepted completions receive both reputation points and CMA tokens. Reputation rewards reflect consistent positive contributions, while crypto rewards are distributed proportionally to each Augmenter's stake. This dual reward system balances immediate financial incentives with long-term commitment to quality, fostering a sustainable ecosystem of crypto expertise.

Read More

Augment-to-Earn Lifecycle: From Task to RewardHuman-in-the-loop (HITL) in LLM Apps