Transformers, the tech behind LLMs | Deep Learning Chapter 5
April 1, 2024
10,420,975
225,040
4,060
2.20%
Search the Record
IndexedEvery word spoken in this episode is indexed. Type any phrase to jump straight to the moment it was said.
Type any word or phrase that may have been spoken. Click a result to seek the player to that exact moment.
Try a name, a topic, or a quoted line
3blue1brown Episodes Around April 1, 2024
See what was published immediately before and after this episode.
27:14Now PlayingTransformers, the tech behind LLMs | Deep Learning Chapter 5
Chapters
YouTube Description
as posted by the channelBreaking down how Large Language Models work, visualizing how data flows through.
Instead of sponsored ad reads, these lessons are funded directly by viewers
---
Here are a few other relevant resources
Build a GPT from scratch, by Andrej Karpathy
If you want a conceptual understanding of language models from the ground up, @vcubingx just started a short series of videos on the topic:
If you're interested in the herculean task of interpreting what these large networks might actually be doing, the Transformer Circuits posts by Anthropic are great. In particular, it was only after reading one of these that I started thinking of the combination of the value and output matrices as being a combined low-rank map from the embedding space to itself, which, at least in my mind, made things much clearer than other sources.
History of language models by Brit Cruise, @ArtOfTheProblem
An early paper on how directions in embedding spaces have meaning:
Звуковая дорожка на русском языке: Влад Бурмистров.
---
Timestamps
Guests & Subjects Covered
Sentinel Indexing in Progress
Metadata and chapters are available. Claim extraction for this episode is pending.
All video content is delivered via YouTube embedded players in accordance with the YouTube Terms of Service. Sentinel provides research tools that promote discovery and accountability across political media.