Training Methodology

Data Sources

AIDA’s training incorporated diverse datasets to cultivate its distinct voice and tone:

• Digital Culture Analysis: Scraped content from X (Twitter), Reddit, and forums, focusing on memes, trends, and sarcasm-laden commentary.

• Tech and Startup Discourse: Curated posts and discussions to build AIDA’s expertise in critiquing tech culture and buzzword-heavy narratives.

• Modern Philosophy & Literature: Incorporated texts on realism, cynicism, and wit to shape AIDA’s worldview and storytelling style. Preprocessing

  • Tokenization: Enhanced to capture slang, emojis, and internet-specific lexicon.

  • Noise Reduction: Removed irrelevant, redundant, or low-quality content.

  • Synthesis: Blended humor with realism, creating a unique dataset emphasizing AIDA’s voice.

  Fine-Tuning

  AIDA’s persona emerged through rigorous training:

  • Reinforcement Learning from Human Feedback (RLHF): Reward models scored responses based on wit, relevance, and user engagement.

  Supervised Customization: Developers curated AIDA’s sarcastic style, ensuring every response reflected its unapologetic personality.