Corinne David (corinne767)

With 26 years of experience and two patents from 2021 for the Emakia system, she developed AI at Forecast Energy and worked in biotech.

San Francisco, California, United States
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YouTube Content Analyzer — YouTube Content Analyzer

YouTube Content Analyzer empowers Reddit communities to evaluate YouTube videos for toxicity, bias, and misinformation. Redditors collaboratively analyze content.

Daytona — Daytona

Built an async LLM-powered moderation dashboard detecting toxicity, bias, misinformation, and sentiment—real-time scoring, Redis caching, and Streamlit UI. Modular, reproducible, and demo-ready.

Toxicity and misinformation Detection — Toxicity and misinformation Detection

I integrated Dynatrace’s DQL API to evaluate bias and toxicity The MCP Server supports local observability testing during development. Final results will be stored in MongoDB.

LLM: Bias, Toxicity, and Misinformation Mesh — LLM: Bias, Toxicity, and Misinformation Mesh

LLM: BiasMesh uses agentic LLMs to classify tweet toxicity, bias, and misinformation—mapping ethical risks in graph form for moderation, traceability, and transparency.

A Transparent Multi-Agent Framework for Ethical AI — A Transparent Multi-Agent Framework for Ethical AI

Emakia is a modular Streamlit app using Google's ADK to detect and correlate toxicity, misinformation, and bias. With BigQuery and transparent agents, it promotes ethical, user-driven AI workflows.

Emakia Fake News Filtering with LLM — Emakia Fake News Filtering with LLM

Detect fake newsEmakia uses cutting-edge LLM technology to detect misinformation, bias, and toxicity—empowering users with reliable content verification in real time.

Emakia: Toxicity Filtering & Validation for Social Media — Emakia: Toxicity Filtering & Validation for Social Media

A system to filter toxic content from social media using Vertex AI's text classifier, validating labels and model outputs with smart AI to enhance accuracy and retrain the model.