Key Features

Alaya consists of three layers of infrastructure: the Interaction Layer, the Optimisation Layer, and the Intelligent Modelling Layer. The three layers are designed to be open and composable to enable custom data requests and external API access for individual users, model developers and Web3 partners alike.

🦔 Interaction Layer

Alaya’s Interaction Layer is the frontend of our platform that connects data, communities and AI technologies through a simple gamified interface, accessible through both our Google Play app and browser dApp. Users can directly access our platform through either email verification or wallet connection to contribute AI training data and earn a combination of various token + NFT rewards via the Interaction Layer. https://www.aialaya.io/web/alaya/game.html

🦥 Optimisation Layer

Alaya’s Optimisation Layer provides targeted data sampling and automated data preprocessing for optimal sampling efficiency.

The Optimisation Layer automatically verifies data quality by applying Gaussian approximation and particle swarm optimisation algorithms and enables Alaya AI to deliver superior data quality with greater efficiency and lower costs. Sampling bias is also minimised through large and diverse user communities, targeted sampling algorithms and HITL-assisted preprocessing model fine-tuning.

🐇 Intelligent Modelling Layer

Manual data labelling is too costly, inefficient, and limited in scalability for modern AI training demands. Alaya’s Intelligent Modelling Layer addresses this challenge by providing an infrastructure for dynamic autolabelling AI models through a combination of evolutionary computation and RLHF/HITL iteration.

New AI autolabelling model development can be voted by community governance via $AGT token staking in respective data model staking pools. Users receive additional rewards proportionally from the revenue generated by each respective autolabelling models they have staked in in accordance to model performance.