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AI Language Models & Transformers - Computerphile

Rob Miles explains on Computerphile how language models generate plausible text and how transformers improved on recurrent networks, with a look at what comes next.

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Why HN readers recommended it

Pointed to as an accessible early explanation of transformers and attention for newcomers.

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

Video & recommendation details

Creator / channel
Computerphile
Topic
transformers and language models
Format
explainer
Level
intro
HN recommenders in dataset
3
HN mentions in dataset
3
Recommendation years in dataset
2022–2025

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 video by Computerphile is a great overview of transformers and how we got to this point [0]. Basically the networks we used before, recurrent neural networks, "forgot" prior information so they're not good at long tasks. The transformer architecture however does not forget (or …

    cercatrova on Hacker News · 2022-08
    In A demo of GPT-3's ability to understand long instructions

  • Those Computerphile videos[0] by Rob Miles helped me understand transformers. He specifically references the "Attention is all you need" paper. And for a deeper dive, Andrej Kharpaty has this hands-on video[1] where he builds a transformer from scratch. You can check-out his other videos on …

    FranklinMaillot on Hacker News · 2023-05
    In Ask HN: Can someone ELI5 Transformers and the “Attention is all we need” paper

  • If you want to get a better understanding of this I recommend playing around in the "chat playgrounds" on some of the engines. The Google one allows for some free use before you have to pay for tokens. (Usually you can buy $5 worth of …

    mhast on Hacker News · 2025-02
    In Modern-Day Oracles or Bullshit Machines? How to thrive in a ChatGPT world

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.

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