Large Language Models

QumulusAI Secures Priority GPU Infrastructure Amid AWS Capacity Constraints on Private LLM Development

Developing a private large language model (LLM) on AWS can expose infrastructure constraints, particularly around GPU access. For smaller companies, securing consistent access to high-performance computing often proves difficult when competing with larger cloud customers. Mazda Marvasti, CEO of Amberd, encountered these challenges while scaling his company’s AI platform. Because Amberd operates its own…

As Pressure Around AI Returns Increases, Companies Using Should Know the Generative AI Basics

In an era defined by rapid technological advancements, the surge of generative artificial intelligence (AI) and Large Language Models (LLMs) stands out as a particularly transformative development. It’s a trend that’s leading to a wealth of new AI-powered solutions for businesses to consider investing in, whether as part of their internal tech stack or as…

Applied Digital Investor Day: Pioneering Specialized Data Centers for Advanced AI Training

Richard Nottenburg, on the Board of Directors at Applied Digital, highlights the company’s specialized venture into building data centers dedicated to AI training models. These facilities are designed to support the intense demands of generative AI and large language models (LLMs), utilizing cutting-edge computational hardware tailored for these advanced technologies.