This blog provides a proof of concept (PoC) for building and training Large Language Models (LLMs) using open-source tools

Embedding models serve as a pivotal component in modern Retrieval-Augmented Generation (RAG) systems, bridging the gap between raw data and meaningful insights

We're thrilled to announce a series of essential updates designed to make your LLM (Large Language Model) training experiences smoother, faster, and more cost-effective. CPU Instances, SSH Access, Network Enhancements and More!

In this article, GreenNode will share our experience with multinode setups—specifically using NVIDIA’s H100 GPUs and InfiniBand technology—to address specific use cases for our clients.

Building an LLM from scratch is not just about coding and data—it’s about navigating uncharted waters with limited resources and an unforgiving clock ticking in the background.

Whether you're a startup dreaming big or a tech-savvy business scaling up, understanding these costs to train an LLM can help you make smart decisions.

GreenNode's AI Platform is designed to simplify your AI development journey. Our platform provides powerful tools and resources to help you manage and analyze large amounts of data efficiently.

In June 2024, GreenNode became the first unit in SEA to successfully launch the GPU cluster specializing in HPC applications, AI training, and integration.

Then what is SLURM for AI and how this high-scalable workload manager works on Linux clusters? In this blog, we’ll guide you through SLURM concept and how to set up a SLURM cluster tailored for AI projects.