— blog
Llms
Let's explore the source of my reflections — on data, AI, and everything that sits between a raw dataset and a good decision — turn complexity into clarity, and share it all in the most naive way.
- Nov 16 min
LLM-based Agents: Single and Multi-Agent Systems
LLMsAgentic AIOverview of LLM-based agents, including single-agent and multi-agent systems, core components (planning, memory, tool use), and common coordination and planning patterns.
- Oct 269 min
Preference Alignment: RLHF and DPO
LLMsFine-tuningRLHFDPOAn in-depth exploration of preference alignment techniques for LLMs, including Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO).
- Mar 148 min
Retrieval Augmented Generation (RAG) with Vector Databases
LLMsRAGVector DatabasesContext EngineeringThe article delves into Retrieval-Augmented Generation (RAG), which integrates retrieval and generative models to enhance GenAI applications efficiently. It highlights the architecture of RAG, utilizing vector databases for data retrieval and response generation.
- Dec 1218 min
From Transformer to LLMs
LLMsRAGPrompt EngineeringFine-tuningThis article explores the evolution from Transformers to Large Language Models (LLMs), detailing the mechanisms of self-attention and multi-head attention, the role of position embeddings, various types of transformer models, and the training and fine-tuning processes of LLMs.
- Jul 111 min
LLMs in LangChain - Part 2. LLMs Core Concepts
LLMsAgentic AIThis article provides an overview of the core concepts of Large Language Models (LLMs) in LangChain, including LLM components, prompt templates, indexing, memory, chains, and agents.
- Jun 306 min
LLMs in LangChain - Part 1. Conceptual
LLMsAgentic AIThis article provides an overview of Large Language Models (LLMs), LLMs evolution and the core concepts of LangChain - an open source framework for building applications based on LLMs.