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...

Since the emergence of ChatGPT (November 30, 2022) [1], a wave of Large Language Models (LLMs) has been released as if in competition. Just in 2024 alone, we’ve seen the launch of Gemini 1.5 pro (February 15) [2], LLaMA 3...

On July 29th, Meta unveiled SAM (Segment Anything Model) 2. It has been 1 year and 4 months since the initial release of SAM in April 2023. Let’s take a closer look at how much it has changed! 🧐 Segmentation’s...

One of the most effective methods for reducing hallucinations in language models is generating answers based on search results, and a prime example of this is RAG. RAG, or Retrieval-Augmented Generation, involves using search-augmented generation techniques, where the language model...

Recently, competition among chatbot models has reignited. Models like Bard and Gemini have sparked anticipation with each release, hoping to surpass GPT-4, but they haven’t quite succeeded. However, many claim that the newly released Claude-3 family by Anthropic provides responses...