Large Language Models (LLMs) stand out for their ability to parse and generate human-like text across various applications. These models have become integral to technologies that automate and enhance text-based tasks. Despite their advanced capabilities, modern LLMs...

The rapid progression of Large Language Models (LLMs) is a pivotal milestone in the evolution of artificial intelligence. In recent years, we have witnessed a surge in the development and public accessibility of well-trained LLMs in English and other languages,...

Generative adversarial networks (GANs) are a popular tool for creating realistic data, but they often struggle with a problem called mode collapse. This happens when the variety of generated samples isn’t as diverse as real ones. Researchers have had trouble figuring...

In recent years, deep learning has been effective in high-performance computing. Surrogate models continue to advance, surpassing physics-based simulations in accuracy and utility. This AI-driven progress is evident in protein folding, exemplified by RoseTTAFold,...

The Language Processing Unit (LPU) represents a groundbreaking advancement in processor technology, specifically engineered to optimize tasks associated with natural language processing (NLP). Unlike general-purpose CPUs and GPUs, LPUs are tailored for the sequential...

Cloud infrastructure is a key component of AI development and implementation in the modern era. There should be less complexity in managing and utilizing cloud infrastructure. Establishing deployment pipelines is challenging, and keeping cloud settings and application...