Annotate Data to Fuel Al Development and Earn Rewards through a Transparent Mechanism.
Take on quests like annotating data for AI training, evaluating AI responses, ensuring AI safety, and more. Receive NFTs and cryptocurrency for completing quests successfully.
Train AI
Training data powers AI like premium gasoline powers an engine. Just as crude oil needs refining, raw data requires careful data labeling, annotation, and curation. This process is crucial for effective AI training, ensuring models achieve both accuracy and reliability.
Label Data: Provides accurate and relevant labels for raw data, which are essential for training AI models to make precise predictions.
Curate Data: Transforms raw data into structured, labeled datasets, facilitating effective training and evaluation of machine learning algorithms.
Evaluate AI
Evaluating AI is like running tests for fine-tuning high-performance engines. It's intricate and demands precision. For advanced generative AI models, this means rigorously assessing performance to ensure accuracy and reliability across various scenarios.
Rate AI Output: Use thumbs up or down to offer direct feedback, which aids in refining AI behavior and enhancing output quality.
Vote for Excellence: Choose the most effective response from multiple AI-generated options to guide model enhancements and ensure peak performance. Your selection helps fine-tune the AI's output, driving continuous improvement and delivering higher-quality results.
Provide Feedback: Review and assess language model responses to measure their precision and reliability, pinpointing areas for enhancement.
Harness AI
Harnessing AI is like steering and safeguarding the vehicle. It's about guiding the technology to ensure it serves humanity effectively and safely. Ultimately, AI should be here to benefit human beings.
Identify AI vs. Human Content: Differentiate between AI-generated and human-generated content to enhance transparency and understanding.
Assess Harmfulness: Evaluate content for potential risks and provide feedback to ensure AI practices are safer and more responsible.
Shape AI's Future: Share your insights and preferences to influence the development of AI technologies, helping to align them with human values and needs.
Uses Cases Supported by Data Engine
High-quality, large-scale, and diverse datasets powered by data annotators from a global and engaging community.
Natural Language Processing
Collect and annotate text data for tasks such as sentiment analysis, language translation, and text generation.
Natural Language Processing
Collect and annotate text data for tasks such as sentiment analysis, language translation, and text generation.
Foundation Models
Utilize Reinforcement Learning from Human Feedback (RLHF) for model development, evaluation, safety, and alignment.
E-Commerce
Annotate data for recommendation systems, receipt transcription, and more.
Speech Recognition
Compile and annotate audio datasets for accurate speech-to-text and voice command applications.
Autonomous Driving
Collect bounding boxes to identify the position of cars, pedestrians, traffic lights in your data for training self-driving algorithms.
