AI under the Hood
Demystifying the complex world of Artificial Intelligence. From neural architecture breakdowns to the latest in LLM research, we go beyond the hype to see how the engines of modern AI actually run.
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Recent Posts
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Why Embeddings Matter
Updated:A deep dive into what embeddings are, why they matter, and how they power modern AI, semantic search, and RAG-based systems.
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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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Transformers in AI
Updated:The Architecture That Revolutionized Machine Learning
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Top-k vs. Nucleus Sampling
Updated:Decoding the Secrets of AI Text Generation