Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 1 - Transformer
1.1M views · Oct 17, 2025 · Education
Comments · 233
@LedioBerdellima · 9 months ago
Bros A/B tested MIT/Stanford
501
@TristanChambers · 2 months ago
Note: The transformer architecture outlined in this lecture is an encoder-decoder design, whereas the typical modern LLM (like GPT) is a decoder only design. The original Attention is All You Need paper was focused on a translation use case exclusively. LLMs like GPT are general purpose models that do not benefit from an encoder stage.
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@bongkem2723 · 10 months ago
thanks Standford for making this public !!!
175
@DarrylRuggles · 11 months ago
Thanks for providing this fundamental content for free online!!
127
@sfguy4739 · 9 months ago
Basically one person in two bodies
39
@rabbithole9853 · 5 months ago
Thanks for sharing the excellent course. Please keep the video focused on the slides instead of the speaker. In the whole scene view, I can barely see anything on the slides. Thanks again.
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@apeksytchannel · 7 months ago
I am very pleased that such valuable information is publicly available! Thanks!
33
@DhruvGhulatiG · 1 month ago
In self-attention its not just attention of one word over other words, but across multiple dimensions (grammar, style etc)
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@sahaneakanayaka3394 · 3 months ago
This is pure gold for anyone learning LLMs. Thanks for sharing your knowledge!
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@LON310 · 11 months ago
never knew transformers could be this deep
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@thekingspider241 · 11 months ago
never thought transformers were so cool
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@vrajpat3lll · 11 months ago
Hey Stanford, I am really grateful to you guys for giving out such golden lectures that have helped me gain some understanding about AI and deep learning! Thanks so much.
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