Ștefan Colcier's Linkedin Analytics

I'm a passionate, self-taught programmer specializing in Generative AI and Large Language Models (LLMs). My expertise spans the entire spectrum of LLM technologies and applications, including: - Retrieval-Augmented Generation (RAG) - Hybrid RAG - Fine-tuning and prompt engineering - Retrieval-Interleaved Generation (RIG) - Named Entity Recognition (NER) - Vector, graph databases and semantic search - Knowledge Graphs - LLM evaluation and benchmarking - Prompt optimization and chain-of-thought reasoning - Multi-modal AI systems (text, image, audio) - Efficient inference and deployment strategies With a strong foundation in Python, I've implemented end-to-end Generative AI solutions, from data preprocessing and model training to API development and production deployment. I'm constantly exploring cutting-edge techniques in natural language processing, staying ahead of the rapidly evolving AI landscape. My hands-on experience includes: - Developing custom RAG systems for domain-specific applications - Implementing fine-tuning pipelines for various LLM architectures - Creating advanced prompt templates for complex reasoning tasks - Designing and optimizing vector stores for efficient similarity search As an avid learner, I am deeply committed to continuously expanding my knowledge and skills in this fast-paced field. I actively seek out new research, attend workshops and conferences, and engage in hands-on projects to deepen my understanding and stay at the forefront of Generative AI advancements. I'm always eager to collaborate on challenging AI projects and contribute to the open-source community. If you're working on innovative applications of Generative AI or LLMs, let's connect and explore how we can drive innovation in this exciting field. I'm excited to connect with fellow professionals and continue growing in the dynamic world of AI and machine learning.