AI Scalability – itsabout.ai

Deploying AI Workloads in Virtualised Environments with VMware VVF, Private AI on VCF, RHEL KVM, and Nutanix

Artificial Intelligence (AI) is transforming industries, but deploying AI workloads efficiently remains a challenge. Many organisations look to virtualisation to maximise resource utilisation, improve security, and streamline AI infrastructure management. This blog explores how to deploy AI workloads in virtualised environments using VMware Virtualised vSphere for AI (VVF), Private AI on VMware Cloud Foundation (VCF), […]

Simon Todd in 11 Mar 2025 No Comments

The AI Revolution: Why the Technology of Today Won’t Power the AI of the Future

Blockchain Finance Financial

Future General Healthcare Human Resources Informational Infrastructure Recruitment Security Society Technology

Artificial Intelligence (AI) is undergoing a rapid transformation, driven by advancements in hardware and software. Today, AI relies heavily on high-performance computing (HPC), GPUs, TPUs, ASICs, and optimised software frameworks. However, as AI models become more complex, the limits of current technology become apparent. This raises an important question: will the AI infrastructure we rely […]

Simon Todd in 28 Feb 2025 No Comments

Network Architecture Design for AI Workloads

General Informational Infrastructure

Security Technology

Artificial Intelligence (AI) workloads are exerting escalating pressures on network infrastructure. As models increase in complexity, efficient data transmission, minimal latency, and high bandwidth are crucial for seamless operations. The architecture of AI networks must be meticulously crafted to enhance performance in both training and inference tasks. This article examines InfiniBand and Open Ethernet topologies, […]

Simon Todd in 17 Feb 2025 No Comments

Why RAG is Important vs Fine-Tuning and Training

Blockchain Finance Financial

Future General Healthcare Human Resources Informational Infrastructure Recruitment Security Society Technology

In the swiftly changing realm of artificial intelligence, companies are pursuing the most effective methods to optimise Large Language Models (LLMs) for their specific needs. Although conventional techniques like fine-tuning and comprehensive training are prevalent, Retrieval-Augmented Generation (RAG) is developing as a more efficient and pragmatic alternative. This essay will examine the significance of RAG, […]

Simon Todd in 01 Feb 2025 No Comments