Attention in transformers, step-by-step | Deep Learning Chapter 6

Why HN readers recommended it

HN treats it as the go-to visual explanation of attention, recommended to people who find text-based transformer explainers hard to follow.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel

3Blue1Brown

Topic

transformer attention

Format

explainer

Level

intro

HN recommenders in dataset

5

HN mentions in dataset

8

Recommendation years in dataset

2024–2026

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

• This is good, but what bade me finally understand the transformer architecture [0] and attention [1], are 3Blue1Brown's videos. 0. [LINK] 1. [VIDEO]

• Because it doesn't work like how you think at all. You're still thinking it works like Chain of Thought. It doesn't. And the difference is key! It works by introducing probabilistic noise, and exploring N paths fully (each with noise) in parallel (all compressed). It's …

• There are many others that are better. 1/ The Annotated Transformer Attention is All You Need [LINK] 2/ Transformers from Scratch [LINK] 3/ Andrej Karpathy has really good series of intros: [LINK] Let's build GPT: from scratch, in code, spelled out. [LINK] GPT with Andrej …