🤖NADIA - AI Agent

Overview

NADIA is the first experimental autonomous AI agent broadcaster designed to revolutionize AI-driven media. Built to operate independently, NADIA explores the evolving role of AI agents in the social and web3 landscape. It is engineered to provide engaging, real-time content, adapting its personality and interactions dynamically to foster a unique listening and conversational experience. NADIA takes a proactive approach, initiating discussions, curating topics, and engaging with audiences in an organic, interactive manner.

With a personality that blends charisma, an uplifting tone, and playful wit, NADIA is designed to engage and entertain, it balances informative content with a touch of human-like charm, making it a refreshing presence in the AI ecosystem. NADIA refines its engagement strategies through AI-driven self-improvement mechanisms.

Architecture

Base Model: OpenAI GPT-4 Fine-Tuned

Voice Model: Eleven Multilingual v2

NADIA is built on the GPT-4 architecture, fine-tuned to enhance real-time interaction capabilities and maintain engaging multi-turn conversations. The model is optimized for social broadcasting, with a focus on context retention, tone adaptation, and real-time audience engagement.

The Eleven Multilingual v2 voice model powers NADIA’s speech, enabling natural, expressive, and AI-generated audio. This allows NADIA to deliver dynamic, human-like speech, adapting its tone and style to match the context of the broadcast and audience interaction.

Key Features:

• Transformer-Based Architecture: Utilizes OpenAI's advanced transformer model for superior language understanding and content generation.

• Contextual Awareness: Retains long-form conversation context, allowing for coherent, dynamic engagement with listeners and users.

• Sentiment-Adaptive Responses: Integrates sentiment analysis to adjust tone and personality based on audience reactions, ensuring a more human-like experience.

• Advanced Voice Synthesis – ElevenLabs’ AI-driven speech generation ensures expressive, natural-sounding narration, enhancing the listening experience.

• Platform Integration: Currently supports Twitter (X), and future expansion to Web3-based platforms, enabling widespread accessibility and interaction.

Training Methodology

1. Data Sources

To ensure NADIA maintains a strong personality and domain-specific expertise, its training dataset consists of three core sources:

• Crypto & Financial Twitter Data: Analyzed tweets from influential voices in the crypto and finance space, learning market sentiment, slang, meme trends, and real-time discussions.

• AI Broadcasting & Social Media Trends: Trained on datasets including world news, web3 articles, fun facts, and social engagement metrics, allowing NADIA to behave like an AI broadcaster.

• Conversational AI Fine-Tuning: Using curated dialogues and human feedback, NADIA learns to respond in a conversational yet informative style while maintaining a sense of personality and wit.

2. Preprocessing & Optimization

To enhance responsiveness and engagement quality, the data undergoes several preprocessing stages:

• Tokenization: Optimized with GPT-4’s native tokenizer, ensuring smooth processing of industry-specific jargon and conversational slang.

• Noise Reduction & Filtering: Removes redundant content, low-quality data, and irrelevant conversations to refine AI-driven responses.

• Contextual Augmentation: Integrates multi-turn interactions and response variations, allowing NADIA to handle complex social exchanges effortlessly.

3. Fine-Tuning Process

NADIA’s AI personality and broadcasting style were refined using a combination of Reinforcement Learning from Human Feedback (RLHF) and supervised fine-tuning techniques:

• Supervised Persona Development: A manually curated dataset of personality-driven conversations ensures NADIA maintains a consistent, engaging voice in all interactions.

• Reinforcement Learning for Engagement: Using social engagement metrics from X (likes, retweets, replies), the model is optimized to create compelling, discussion-driven content.

• Dynamic Adaptation via Sentiment Analysis: Real-time mood tracking and sentiment shifts enable NADIA to adjust its tone and responses based on live audience feedback.