RTRaghavan T Minchangeofbasis.hashnode.dev·1d ago · 4 min readTransformers: The Architecture That Replaced EverythingYouTube auto-captions a few years ago. Turn them on during a video — half the words wrong, sentences jumbled, meaning lost. You'd laugh at them more than use them. Today, those same captions are accur00
AGAmol Girmeinaicrmvault.hashnode.dev·3d ago · 10 min readTransformerIf you have used ChatGPT, Google Translate, an AI image generator, or a voice assistant, then you have already interacted with a technology called the Transformer. Today, Transformers are the foundati00
RBRajan Bhatejainllms-with-rajan.hashnode.dev·Jun 11 · 6 min readThe Complete LLM Inference PipelineHave you ever wondered what actually happens after you type a prompt into ChatGPT and press Enter? How does the model process your words, understand context, and generate a response one token at a tim00
UBUJJWAL BALAJIinchatteronai.hashnode.dev·Jun 2 · 8 min readInside the Brain of an LLM: From Raw Text to Next-Token Magic Imagine you are sitting in a dimly lit café, watching a master chess player. They aren't looking at the whole board with panic; they are looking at the current setup, calculating the absolute best nex10
CGCristiano Gabrieliincrisdigital.hashnode.dev·May 27 · 15 min readJulia and R the future of AIJulia for LLMs: Why a High‑Performance Language Finally Makes Sense for AI Workflows Introduction — Why Julia Matters Now There’s a moment in every technology cycle where a tool that’s been quietly m00
CGCristiano Gabrieliincrisdigital.hashnode.dev·May 23 · 4 min readUnderstanding Transformer Architecture in 2026 (SilentRecon Deep Dive) Understanding Transformer Architecture in 2026 — A SilentRecon Deep Dive SilentRecon Deep Dive: Understanding Transformer Architecture in 2026 By SilentRecon — Advanced Reconnaissance & AI Systems Eng00
MFMohammed Fahd Abrahinfreecodecamp.org·May 6 · 12 min readAI Paper Review: Improving Language Understanding by Generative Pre-Training (GPT-1) We use AI tools all the time, whether it’s asking questions, generating images, or getting help with everyday tasks. But most of these tools didn’t appear out of nowhere. They were developed based on 00
AAAbstract Algorithmsinabstractalgorithms.dev·May 3 · 23 min readSoftmax Function Explained: From Raw Scores to ProbabilitiesTLDR: Softmax converts a vector of raw scores (logits) into a valid probability distribution by exponentiating each value and dividing by the total. Subtracting the max before exponentiating prevents 00
AAAbstract Algorithmsinabstractalgorithms.dev·May 3 · 22 min readDot Product in Machine Learning: The Engine Behind Similarity, Attention, and Neural NetworksTLDR: The dot product multiplies corresponding elements of two vectors and sums the results. In machine learning it does three critical jobs: it scores semantic similarity between embeddings, computes00
CTClementina Tominclementina-tom.hashnode.dev·May 2 · 14 min readThe Logic Engine: Building a Constraint-Aware AI Recommendation System for Personalized LearningHow I combined Deep Knowledge Tracing, curriculum graph theory, and multi-objective ranking to build a recommendation system that actually understands how people learn --- and achieves a 0.0% prerequi10
