Author: HaroonAkram

AI language models require updating from time to time in order to make them accurate and aware of the latest information. The overall update of the entire language model demands a lot of resources and power. Here comes handy the Retrieval-Augmented Generation (RAG) and the fine-tuning. RAG is one of the most helpful strategies to keep the Virtual Large Language Models (vLLMs) updated with frequent intervals instead of the overall revamp. The RAG method allows you to update the vLLMs with the latest information available on the internet as part of continuous batching. It equips the models with the fresh…

The applications based on artificial intelligence work on Machine Learning (ML) and the phenomena of Natural Language Processing (NLP) Models. There are different types of language models, and Virtual Large Language Models (vLLMs) are the best-performing models. These models can be optimized easily with continuous batching that reduces the operating cost and allows the necessary modifications to be done regularly and within the time. Additionally, the vLLMs are more powerful and include a larger database than the traditional language models. This makes them a perfect fit for specific AI applications that enable growth, productivity, and deliver results.  The question arises:…