George Chrysochou

AI & ML interests: - AI for SEO (AIO/GEO/LLMO): A primary research and application area focused on understanding and optimizing for the new generation of AI-powered search and answer engines. - Natural Language Processing (NLP): Core interest in applying NLP models to understand, generate, and optimize web content. - Large Language Models (LLMs): Focused on the practical application, fine-tuning, and optimization of LLMs for specific domains like finance, e-commerce, and media. - Generative AI: Specializing in text generation, summarization, and data augmentation for large-scale content strategies. - Retrieval-Augmented Generation (RAG): Actively developing and implementing RAG systems to ground LLM outputs in real-time, factual data from custom knowledge bases and live web searches. - AI Agents & Multi-Agent Systems: Building and deploying autonomous agents for tasks like data retrieval, content creation workflows, and automated outreach. - Prompt Engineering: Advanced techniques for crafting, testing, and optimizing prompts to control LLM behavior for high-quality, consistent outputs. - Transformer Architectures: Deep interest in the underlying technology of models like GPT, BERT, and T5 for tasks ranging from semantic search to translation and generation. - Semantic Search & Information Retrieval: Using embedding models and vector databases to improve search relevance and build custom knowledge retrieval systems. - Knowledge Base Construction: Developing automated pipelines to scrape, process, and structure unstructured web data into queryable knowledge bases for RAG applications. - Entity Recognition & Linking: Identifying and linking named entities in text to build more comprehensive knowledge graphs and improve content relevance for search engines.