Background

The Evolution of Task-to-Earn Protocols

T2E protocols have undergone numerous evolutionary stages in the past several years. Advancements in blockchain integration, interoperability, and automation have turned a once-limited and slow category of dApps into a popular form of farming digital assets. This, paired with the overall growth of the greater Web3 ecosystem, has created an environment where T2E is faster, more reliable, and available for a wide range of audiences.

While these advancements have proven to be invaluable for T2E platforms, they have more so addressed the technical and functional aspects of the sector. In terms of conceptual and experiential aspects, T2E protocols have been advancing at a slower pace, projecting some level of stagnation

Rapid Rise of the AI Era

AI technology has rapidly advanced, leading to its extensive use across multiple industries. According to Gartner, the global AI market is expected to reach $50 billion this year (2024) and $297.9 billion by 2027. The demand for high-quality data annotation in fields such as autonomous driving, medical imaging analysis, natural language processing, and video recommendation algorithms is surging.

• Autonomous Driving: Companies like Tesla and Baidu Apollo rely on vast amounts of annotated data for image recognition and scene prediction. In 2023, the demand for data in the autonomous driving industry reached over 100 million annotation tasks annually.

• Medical AI: Companies such as Medtronic require precise image annotations for disease detection, with the global medical AI market projected to breach $30 billion by 2025.

• Content Recommendation Algorithms: Social media giants like ByteDance (TikTok) and YouTube depend on high-quality annotated data to optimize video recommendation algorithms and improve user experience.

It has maintained its position in the public consciousness and has cemented itself in numerous blockchain sectors—most notably AI agents. As traditional LLM models grow, so too do the countless blockchain-based protocols that leverage them.

Whereas T2E protocols do utilize them to some degree, the true potential of AI within the T2E sector remains unexplored.