Transformer
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As you already know, the world of Large Language Models (LLMs) thrives on processing vast amounts of text data, uncovering hidden patterns to generate human-like text, translate languages, and answer questions with remarkable accuracy. This intricate process relies heavily on a fundamental mathematical operation: Matrix Multiplication (MatMul). While MatMul has been the cornerstone of LLM…
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The Long Short-Term Memory (LSTM), introduced in the 1990s, revolutionized deep learning by overcoming the vanishing gradient problem in recurrent neural networks. LSTMs excel at learning complex temporal dependencies and have achieved groundbreaking results in various domains, particularly in natural language processing (NLP). However, the advent of Transformers in 2017 marked a shift in NLP,…