The rise of large language models (LLMs) has revolutionized many industries, providing businesses with more efficient ways to retrieve and generate relevant information through retrieval-augmented generation (RAG). As the variety of LLMs grows, companies face new opportunities and challenges in...

As advancements in AI continue, Large Language Models (LLMs) are playing increasingly critical roles across various industries. However, assessing their performance requires more complex and nuanced evaluation methods compared to traditional machine learning or deep learning models. Since LLMs are...

In the rapidly advancing field of artificial intelligence (AI), Large Language Models (LLMs) have transformed various industries by offering powerful text processing capabilities. However, while these pre-trained models are impressive, they are not always suitable for specific industry applications without...

Earlier this year, OpenAI’s Sora showcased the potential of video generation models, sparking a wave of releases from other companies. On October 4th, Meta finally introduced its own text-to-video model, and impressively, it also includes the ability to generate audio....

RAG (Retrieval-Augmented Generation) has become a crucial technology for enabling more precise AI responses. Its strength lies in generating tailored answers using specialized domain knowledge. At the heart of this process is the structuring and efficient retrieval of data. In...

A scene of playing the game ‘DOOM’ using the GameNGen model On August 27th, Google Research unveiled their study on the real-time game engine model, GameNGen. The model is powered by diffusion and reinforcement learning. Let’s take a closer look...

On May 21st, the European Union (EU) officially confirmed the implementation of the world’s first “Artificial Intelligence Act (AI Act).” Set to be fully enforced by 2026, this legislation applies to any AI model used within Europe, regardless of where...