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Understanding Transformers: The Engine Driving Modern Generative AI
Attention is all you need
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If you’ve ever wondered how AI models like GPT can write essays, translate languages, or generate human-like conversations, you’re in for a fascinating ride. In this article, we will unravel the magic behind modern Generative AI by exploring the Transformer architecture, a revolutionary model that has redefined natural language processing. You’ll learn how Transformers evolved from earlier models, how they work under the hood with attention mechanisms and query-key-value vectors, and what challenges they still face today. Whether you’re a tech enthusiast or an AI practitioner, this comprehensive guide will deepen your understanding of why Transformers are at the heart of AI’s most impressive breakthroughs.
The Journey from Seq2Seq Models to Transformers: A Quantum Leap in NLP
Before the age of sophisticated models like GPT and BERT, language translation and text generation relied on the pioneering Seq2Seq models. Imagine a traveler navigating a foreign land with only a single phrasebook — this is akin to how Seq2Seq models processed input. These models would encode an entire sentence into a fixed-length vector (like stuffing all your…
