Self-Attention

Transformer was first introduced in the seminal paper “Attention is All You Need”

Editor2 weeks ago022 mins

Transformer is a neural network architecture that has fundamentally changed the approach to Artificial Intelligence. Transformer was first introduced in the seminal paper “Attention is All You Need” in 2017 and has since become the go-to architecture for deep learning models, powering text-generative models like OpenAI’s GPT, Meta’s Llama, and Google’s Gemini. Beyond text, Transformer is also applied in audio generation, image…

Inner Workings of ChatGPT-4 AI Attention Blocks, Feedforward Networks, and More

Editor1 month ago1 month ago05 mins

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:…

Understanding Transformers: The Mathematical Foundations of Large Language Models

Editor3 months ago3 months ago010 mins

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…

Implementing KV Cache from Scratch in nanoVLM: A 38% Speedup in Autoregressive Generation

Editor3 months ago3 months ago04 mins

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…

How LLMs Work: Step-by-Step Explanation

Editor7 months ago5 days ago066 mins

What is a large language model (LLM)? Large Language Models are machine learning models that employ Artificial Neural Networks and large data repositories to power Natural Language Processing (NLP) applications. An LLM serves as a type of AI model designed to be able to grasp, create, and manipulate natural language. These models rely on deep…

Understanding the Layers of Large Language Models (LLMs) and How Data Passes Through Them

Editor3 years ago8 months ago012 mins

Large Language Models (LLMs) such as GPT (Generative Pre-trained Transformer) are a class of deep learning models that have revolutionized natural language processing (NLP).