At its core, ChatGPT-4 is built on the Transformer architecture, which revolutionized AI with its self-attention mechanism. Below, we break down the key components and their roles in generating human-like text. 1. Transformer Architecture Overview The Transformer consists of encoder and decoder stacks, but GPT-4 is decoder-only (it generates text autoregressively). Key Layers in Each Block:…
In recent years, two major breakthroughs have revolutionized the field of Large Language Models (LLMs): 1. 2017: The publication of Google’s seminal paper, (https://arxiv.org/abs/1706.03762) by Vaswani et al., which introduced the Transformer architecture – a neural network that fundamentally changed Natural Language Processing (NLP). 2. 2022: The launch of ChatGPT by OpenAI, a transformer-based chatbot…
Course Introduction: How Large Language Models (LLMs) Work What You Will Learn: The LLM Processing Pipeline In this course, you will learn how Large Language Models (LLMs) process text step by step, transforming raw input into intelligent predictions. Here’s a visual overview of the journey your words take through an LLM: Module Roadmap You will…
Introduction to KV Caching When large language models (LLMs) generate text autoregressively, they perform redundant computations by reprocessing the same tokens repeatedly. Key-Value (KV) Caching solves this by storing intermediate attention states, dramatically improving inference speed – often by 5x or more in practice. In this comprehensive guide, we’ll: Explain the transformer attention bottleneck Implement KV caching from scratch…
Introduction Autoregressive language models generate text one token at a time. Each new prediction requires a full forward pass through all transformer layers, leading to redundant computations. For example, generating the next token in: [What, is, in,] → [the] requires recomputing attention over [What, is, in,] even though these tokens haven’t changed. KV Caching solves this inefficiency by…
As a candidate, I’ve interviewed at a dozen big companies and startups. I’ve got offers for machine learning roles at companies including Google, NVIDIA, Snap, Netflix, Primer AI, and Snorkel AI. I’ve also been rejected at many other companies. As an interviewer, I’ve been involved in designing and executing the hiring process at NVIDIA and…
How a Large Language Model (LLM) predicts the next word, including all the mathematical operations involved at each step, with the appropriate vector and tensor manipulations.
Course on Large Language Models NOTE: You’re only meant to change code marked with “# TODO:” Table of Contents Setting Up API Key Configuration Connecting to OpenAI API Exploring the API Creating Chat Completions Understanding Completion Parameters Prompt Engineering Crafting Effective Prompts Strategies and Best Practices Advanced Techniques Utilizing Embeddings Function Calling in LLMs Extras…
