Is RAG Still Relevant in a Post-LLaMA 4 World?

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Not long ago, I wrote about why Retrieval-Augmented Generation (RAG) is such a pivotal architecture in modern AI workflows, particularly when compared to fine-tuning and training from scratch. The core argument was simple: RAG enables models to stay up-to-date, grounded, and efficient without massive retraining costs. It was (and still is) a pragmatic solution to […]

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Why Enterprises Are Moving Workloads Back to On-Premise Private Cloud for Next-Gen AI

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There has been a clear trend in enterprise IT strategies in recent years, as firms are progressively moving workloads from the public cloud back to on-premise private clouds. The phenomenon known as “cloud repatriation” is particularly noticeable when it comes to advanced workloads such as artificial intelligence (AI) and machine learning (ML). In these cases, […]

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Harnessing the Power of VMware’s Private AI on Intel: Enhancing Data Security, Privacy, and Virtualising AI Workloads

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As artificial intelligence (AI) continues to transform workplace applications, the requirement for strong, secure, and efficient infrastructure becomes more and more crucial. VMware’s Private AI on Intel provides a compelling solution that enables the utilisation of AI in mainstream infrastructure. It focuses on ensuring data protection, privacy, and the smooth integration of AI workloads with […]

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Exploring the Advantages of Private AI: A Balanced View Beyond Cloud Computing

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FutureGeneralHealthcareHuman ResourcesInformationalInfrastructureRecruitmentSecuritySocietyTechnology

In the dynamic world of artificial intelligence (AI), businesses are faced with a crucial decision: opting for the convenience of cloud-based AI or establishing their own private AI systems on-premise. This choice involves a delicate balancing act between cost, data privacy, and flexibility. Let’s take a closer look at why some organizations prefer the path […]

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