Topic: Transformers
All essays filed under "Transformers".
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What LLMs Do at Inference: A Deep Dive Under the Hood
Updated:A step-by-step, reference-backed explanation of what happens during LLM inference: tokenization, embeddings, prefill & decode phases, KV caching, decoding strategies, bottlenecks and optimizations like quantization, FlashAttention and speculative decoding.
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Understanding Tokenizers in AI — A Deep Dive into ChatGPT, Grok, and Gemini
Updated:A complete guide to tokenizers in modern LLMs, covering BPE, WordPiece, SentencePiece, Unigram, and how ChatGPT, Grok, and Gemini tokenize text. Includes examples, real-world impact, and why tokenization is the foundation of AI.
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KV Cache Explained - A Deep Dive into Transformer Optimization
Updated:A Deep Dive into Transformer Optimization
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Transformers in AI - The Architecture That Revolutionized Machine Learning
Updated:The Architecture That Revolutionized Machine Learning