Highlights: Retrieval-Augmented Generation (RAG) models are transforming AI by combining Large Language Models (LLMs) with external memory to improve accuracy, reduce hallucinations, and provide context-aware outputs. In today’s post, we’ll explore RAG’s key concepts, challenges, and cutting-edge advancements and learn how RAG models enhance the reliability of LLM models and increase their adaptability across diverse applications. So let’s begin! Tutorial Overview: 1. LLMs today & their Many Challenges Output Accuracy While language models are impressive,…
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Highlights: Large Language Models (LLMs) have become essential tools in Natural Language Processing, powering applications from chatbots to complex data analysis. In today’s post, we’ll dive into the fascinating world of Large Language Models (LLMs) as explained in a lecture by Andrej Karpathy. We’ll study a notable model in this space, i.e., LLaMA (Large Language Model Meta AI), a groundbreaking LLM developed by Meta (formerly Facebook). We’ll also learn how LLMs in general and this…
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Highlights: Large Language Models (LLMs) have become essential tools in Natural Language Processing, powering applications from chatbots to complex data analysis. This is Part 2 of the post we posted earlier where we discussed the LLM by Meta called the LLaMa (Large Language Model Meta AI). We also learned how LLaMa was trained and how models like ChatGPT are trained. In today’s post, we’ll continue to discuss LLMs touching upon scaling laws, real-life applications of…
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