---
title: "I read every major CS paper of the last 100 years..."
url: https://daily.dev/posts/i-read-every-major-cs-paper-of-the-last-100-years--crvfpmxgi
source_url: https://www.youtube.com/watch?v=ML3q7Ok4hJg
type: video:youtube
source: "Fireship"
published: 2026-06-17T16:30:05.702Z
updated: 2026-06-17T16:30:23.724Z
tags: ["machine-learning", "llm", "deep-learning", "neural-networks"]
reading_time: 10
upvotes: 48
comments: 5
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# I read every major CS paper of the last 100 years...

**[Fireship](https://daily.dev/sources/fireship)** · 10 min read · 48 upvotes · 5 comments

## Summary

A whirlwind tour through 10 landmark computer science papers spanning nearly 100 years, from Alan Turing's 1936 work on computable numbers and the halting problem, to Claude Shannon's information theory, Rosenblatt's perceptron, Lamport's logical clocks, backpropagation, PageRank, AlexNet, the Transformer architecture, and GPT-3. Each paper is explained accessibly, showing how each breakthrough built on the last to produce modern AI. The throughline: Turing defined computation, Shannon quantified information, neural network pioneers taught machines to learn, Google provided data and architecture, and OpenAI scaled everything to the limit.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=ML3q7Ok4hJg>

## Community discussion

Top comments from developers on daily.dev.

**@jadzix** · 3 upvotes

> Very solid summary, albo presented in a digestible way. Thank you!

**@ezpie** · 2 upvotes

> when I heard claude shannon it took me a whole second to realize it wasn't the claude I was thinking

**@seyoungcho** · 0 upvotes

> Fireship is back

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#llm](https://daily.dev/tags/llm), [#deep-learning](https://daily.dev/tags/deep-learning), [#neural-networks](https://daily.dev/tags/neural-networks)

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