Below is the "Attention is all you need" paper. Transformers and their attention mechanism was the major breakthrough for modern LLMs. ML has been around for a long time, I'd suggest joining kaggle or something and learn by doing. You'll retain more and realize how broad the category is anymore.
Below is the "Attention is all you need" paper. Transformers and their attention mechanism was the major breakthrough for modern LLMs. ML has been around for a long time, I'd suggest joining kaggle or something and learn by doing. You'll retain more and realize how broad the category is anymore.
https://arxiv.org/abs/1706.03762
Maybe https://youtube.com/playlist?list=PLbg3ZX2pWlgKV8K6bFJr5dhM7...
Which contains "The 35 Year History of ChatGPT" and "How LLMs Took Over The World"
Believe it or not, there is none.
Somebody ought to write it.
This is probably closest, but it's not an entertaining narrative history, more of a reference: https://mitpress.mit.edu/9780262552691/large-language-models...
This is decent on history, good on contemporary: https://www.youtube.com/watch?v=_R83pFpUWyM
roughly
1. word2vec ('13)
2. transformers ('18)
3. chatgpt ('22)
4. claude code, i.e. tools / bash (mid '25)
5. llms trained for agentic workflow (nov '25)
6. cost reckoning ('26)
7. open weight models break the financial models of Big Ai ('26?)
Adding to your 6 and 7, Ed Zitron's Better Offline podcast has a good series on how the path was paved to the cost reckoning of the present day.
Is the youtube link correct?
Bookmarking this for later. I had a similar agent debugging mess last week.
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