Functions of Oasis Nodes

Data Aggregation: Oasis Nodes handle the aggregation of raw data collected from users and applications within the PlayAI ecosystem. This data can include everything from user-generated content to sensor data, all of which needs to be processed before it can be used for AI model training or other purposes.
Data Cleaning and Preprocessing: Once the raw data is aggregated, Oasis Nodes are responsible for cleaning and preprocessing it. This involves removing any irrelevant or corrupted data, normalizing the data formats, and ensuring that it is structured in a way that is conducive to accurate AI model training.
Data Extraction: Oasis Nodes initiate the process by extracting relevant data from various sources within the PlayAI ecosystem. This includes user interactions, keylogs, videos, images, textual data, sensor outputs, and any other data streams generated by applications and devices connected to the PlayAI Stack. The extraction process ensures that only pertinent data is captured for further processing, reducing noise and improving the quality of the datasets.

Off-Chain Computation: Oasis Nodes perform critical off-chain computation tasks, such as AI model training, parameter optimization, and executing complex algorithms that require significant computational resources. By handling these tasks off-chain, the ecosystem maintains high performance without overloading the blockchain.
Model Validation: After computing tasks, Oasis Nodes validate AI models by testing them against designated datasets. This validation ensures the models' accuracy, reliability, and suitability for deployment within the ecosystem.
Parameter Exporting: Once validated, the necessary parameters and datasets are exported back into the blockchain. This secure recording of results ensures transparency and accessibility for other nodes, developers, and users.
Distributed Computing: Oasis Nodes collaborate in a distributed computing environment, pooling resources to handle large-scale computational tasks more efficiently. This collaborative approach allows the PlayAI ecosystem to scale effectively, process compute heavy taks, and meet growing demands.

Data Rating: Oasis Nodes evaluate the quality of the data processed, ensuring that only high-quality, reliable datasets are used in AI model training and analysis. This rating helps maintain the integrity of the data and set a price for further usage within the PlayAI ecosystem.
AI Model Evaluation: Oasis Nodes also rate AI models and agents based on the outputs generated — assessing their accuracy, relevance, and overall quality. This evaluation ensures that the AI models produce trustworthy and actionable results, while also have a slashing mechanism to punish the bad actors.
Feedback Loop: The rating system creates a feedback loop where high-quality data and outputs are continually reinforced, driving the improvement of AI models over time.

Last updated 2 months ago