Welcome to Part 2 of our GraphRAG tech series. In our previous letter, we explored why GraphRAG is needed and broke down its core architecture. Today, we’ll take a closer look at two key components in the GraphRAG design flow: the Query...

Retrieval-Augmented Generation (RAG) is one of the most widely adopted methods for improving the factual accuracy of generative AI. The approach augments LLM responses by retrieving relevant context from external sources before generating an answer. Typically, this retrieval is based on...

Series 1: RAG, but BetterSeries 2: Better LLM? Think on Graph!  Why are medical school programs so long worldwide? The answer lies in the immense volume of knowledge medical professionals must master. Medicine isn’t just about facts—it’s about navigating complex relationships, countless...

Let’s begin today’s letter by stepping once again into a colossal library. Surrounded by endless shelves of books, we pose the same question as before: “What are the key trends in the tech industry?” In our previous Tech Letter, we likened Graph RAG to a...

Imagine stepping into a colossal library, its shelves stretching endlessly, filled with books. You ask, “What are the key trends in the tech industry?” Now, picture the librarian not only finding relevant books but also summarizing all the tech-related resources in...

Evaluating quality text in the field of Natural Language Generation (NLG) has always been challenging. Assessing text quality to align with human intuition becomes particularly complex for creative or open-ended tasks. Traditional metrics like BLEU and ROUGE are useful for quantifying performance...

As large language models (LLMs) continue to advance rapidly, efficiently retrieving relevant information from vast amounts of text remains a significant challenge. Traditional retrieval methods tend to focus on small, sequential text fragments. However, they often miss the broader context...

Welcome to the final episode of the <LLM Evaluation Trilogy>. In the previous letters, we explored the definition, significance, and examples of LLM evaluation. Today, we will dive into the detailed process of how MoMoJam’s AI safety was evaluated. 1️⃣ What...

OpenAI hs recently released it’s new model o1. Each time a new model is released, researchers explore new fields where the model can be applied. On September 23rd, a paper titled <A Preliminary Study of o1 in Medicine: Are We Closer...

Welcome to our second episode of <LLM Evaluation Trilogy>, presented by Datumo’s NLP researchers! 1️⃣ What is LLM evaluation? 2️⃣ LLM safety evaluation & specific examples 3️⃣ Safety evaluation results of a specific model Following the first part, “What is LLM...