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The scope of Project Aether is centered on Reasoning and Factuality. It aims to move beyond simple chat data to provide models with complex, multi-step logical reasoning chains. The project spans various high-level domains, including: STEM: Advanced mathematics, physics, and chemistry. Coding: Debugging, code optimization, and architectural reviews. Specific Data Labeling Tasks Fellows on Project Aether perform "Expert-in-the-Loop" tasks that go far beyond standard bounding boxes or sentiment analysis: RLHF (Reinforcement Learning from Human Feedback): Ranking multiple AI responses based on accuracy, tone, and safety. . Project Size and Scale Workforce: Managed by platforms like Handshake or similar specialist vendors, the project utilizes a global network of thousands of graduate-level experts (Masters and PhD candidates). Quality Measures Adhered To To ensure the data is suitable for "frontier" model training, Project Aether enforces strict quality controls: Multi-Stage Review: Every task typically undergoes a "Reviewer" and sometimes a "Super-Reviewer" phase to confirm the "Linguistics" and "Logic" are flawless.