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1. 1▶MIT 6.S191: Secrets of Massively Parallel TrainingAlexander AminiNotes
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2. 2▶MIT 6.S191: AI for ScienceAlexander AminiNotes
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3. 3▶MIT 6.S191: The Three Laws of AIAlexander AminiNotes
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4. 4▶MIT 6.S191: Language Models and New FrontiersAlexander AminiNotes
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5. 5▶MIT 6.S191: Reinforcement LearningAlexander AminiNotes
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6. 6▶MIT 6.S191: Deep Generative ModelingAlexander AminiNotes
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7. 7▶MIT 6.S191: Convolutional Neural NetworksAlexander AminiNotes
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8. 8▶MIT 6.S191: Recurrent Neural Networks, Transformers, and AttentionAlexander AminiNotes
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9. 9▶MIT Introduction to Deep Learning | 6.S191Alexander AminiNotes
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10. 10▶I BUILT A FULLY AUTOMATIC MANSPLAINERYannic KilcherNotes
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11. 11▶Traditional X-Mas StreamYannic KilcherNotes
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12. 12▶Traditional Holiday Live StreamYannic KilcherNotes
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13. 13▶TiDAR: Think in Diffusion, Talk in Autoregression (Paper Analysis)Yannic KilcherNotes
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14. 14▶MMXXV: Exit Berlin{ lucidbeaming: "dev" }Notes
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15. 15▶Titans: Learning to Memorize at Test Time (Paper Analysis)Yannic KilcherNotes
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16. 16▶[Paper Analysis] The Free Transformer (and some Variational Autoencoder stuff)Yannic KilcherNotes
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17. 17▶[Video Response] What Cloudflare's code mode misses about MCP and tool callingYannic KilcherNotes
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18. 18▶[Paper Analysis] On the Theoretical Limitations of Embedding-Based Retrieval (Warning: Rant)Yannic KilcherNotes
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19. 19▶AGI is not coming!Yannic KilcherNotes
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20. 20▶Context Rot: How Increasing Input Tokens Impacts LLM Performance (Paper Analysis)Yannic KilcherNotes
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21. 21▶Energy-Based Transformers are Scalable Learners and Thinkers (Paper Review)Yannic KilcherNotes
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22. 22▶MIT 6.S191 (2025): AI for Biology (Microsoft)Alexander AminiNotes
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23. 23▶On the Biology of a Large Language Model (Part 2)Yannic KilcherNotes
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24. 24▶MIT 6.S191 (2025): A Hipocratic Oath, for *your* AI (Comet ML)Alexander AminiNotes
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25. 25▶MIT 6.S191 (2025): Large Language Models (Liquid AI)Alexander AminiNotes
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26. 26▶MIT 6.S191 (2025): Large Language Models (Google)Alexander AminiNotes
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27. 27▶MIT 6.S191 (2025): Language Models and New FrontiersAlexander AminiNotes
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28. 28▶On the Biology of a Large Language Model (Part 1)Yannic KilcherNotes
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29. 29▶MIT 6.S191 (2025): Reinforcement LearningAlexander AminiNotes
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30. 30▶[GRPO Explained] DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsYannic KilcherNotes
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31. 31▶Traditional Holiday Live StreamYannic KilcherNotes
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32. 32▶MMXXIV: Turpentine and tea{ lucidbeaming: "dev" }Notes
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33. 33▶Does Sora understand physics? A few simple observationsSeverely TheoreticalNotes
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34. 34▶MMXXIII: Beyond Berlin{ lucidbeaming: "dev" }Notes
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35. 35▶MMXXII: Berlin{ lucidbeaming: "dev" }Notes
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36. 36▶MMXXI: art in the age of COVID{ lucidbeaming: "dev" }Notes
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37. 37▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 15 - Add Knowledge to Language ModelsStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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38. 38▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 14 - T5 and Large Language ModelsStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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39. 39▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 13 - Coreference ResolutionStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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40. 40▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 12 - Natural Language GenerationStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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41. 41▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 12 - Question AnsweringStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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42. 42▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 10 - Transformers and PretrainingStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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43. 43▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 9 - Self- Attention and TransformersStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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44. 44▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 8 - Final Projects; Practical TipsStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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45. 45▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 7 - Translation, Seq2Seq, AttentionStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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46. 46▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 6 - Simple and LSTM RNNsStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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47. 47▶Stanford CS224N - NLP w/ DL | Winter 2021 | Lecture 5 - Recurrent Neural networks (RNNs)Stanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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48. 48▶Stanford CS224N - NLP w/ DL | Winter 2021 | Lecture 4 - Syntactic Structure and Dependency ParsingStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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49. 49▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 3 - Backprop and Neural NetworksStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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50. 50▶Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 2 - Neural ClassifiersStanford CS224N: Natural Language Processing with Deep Learning | Winter 2021Notes
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