machine: videos

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1. 1▶Intelligent Machines 884: Cyber JimTotal Leo (Video)2:35:33Notes
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2. 2▶Windows Weekly 997: Bear Swamp & The BoathouseTotal Leo (Video)2:30:32Notes
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3. 3▶Security Now 1092: Restraint AbliterationTotal Leo (Video)2:49:05Notes
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4. 4▶MacBreak Weekly 1038: The Silicon-Controlled RectifierTotal Leo (Video)2:29:36Notes
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5. 5▶This Week in Tech 1097: Gina and the GlueballsTotal Leo (Video)2:55:48Notes
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6. 6▶Intelligent Machines 883: Gates-GateTotal Leo (Video)2:35:27Notes
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7. 7▶Windows Weekly 996: Security Through Lack of FeaturesTotal Leo (Video)2:21:57Notes
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8. 8▶Security Now 1091: The Post BlackHat State of AITotal Leo (Video)2:51:12Notes
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9. 9▶MacBreak Weekly 1037: Mechanical DonutTotal Leo (Video)2:39:44Notes
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10. 10▶This Week in Tech 1096: Fluff for ArmorTotal Leo (Video)2:48:18Notes
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11. 11▶Security Now 1090: Black HatTotal Leo (Video)2:05:11Notes
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12. 12▶Windows Weekly 995: The Greatest DepressionTotal Leo (Video)2:43:45Notes
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13. 13▶Hardening Digital Infrastructure: Two ExamplesStrachey Lectures1:02:07Notes
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14. 14▶This app is full of bugsJimmy's blogNotes
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15. 15▶This app is full of bugsJimmy's blogNotes
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16. 16▶An AI stack: from scaling AI workloads to evaluating LLMsStrachey Lectures55:58Notes
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17. 17▶Advances in Garbled CircuitsStrachey Lectures48:12Notes
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18. 18▶Emoji phonetic alphabetJimmy's blogNotes
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19. 19▶Emoji phonetic alphabetJimmy's blogNotes
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20. 20▶Vibe doodlingJimmy's blogNotes
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21. 21▶Vibe doodlingJimmy's blogNotes
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22. 22▶Will Computers prove theorems?Strachey Lectures46:25Notes
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23. 23▶Formalizing the Future: Lean’s Impact on Mathematics, Programming, and AIStrachey Lectures47:14Notes
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24. 24▶Privacy, Verification, Robustness: A Cryptographer's perspective on MLStrachey Lectures1:04:18Notes
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25. 25▶From probabilistic bisimulation to representation learning via metricsStrachey Lectures55:03Notes
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26. 26▶Mastering Accuracy in your DIY wire EDM : SquarenessBAXEDMNotes
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27. 27▶Paris Perdikaris - PirateNets: Physics informed Deep Learning with Residual Adaptive NetworksPhysics-informed machine learning meets engineering seminar seriesNotes
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28. 28▶Tobias Heinrich Nagel - Kalman Bucy informed Neural Networks for System IdentificationPhysics-informed machine learning meets engineering seminar seriesNotes
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29. 29▶Sascha Ranftl - A Connection between Probability, Physics and Neural NetworkPhysics-informed machine learning meets engineering seminar seriesNotes
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30. 30▶Thomas Markovich - Quantum Diffusion Convolution Kernels on GraphsPhysics-informed machine learning meets engineering seminar seriesNotes
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31. 31▶Strachey Lecture: The Computer in the SkyStrachey Lectures1:02:09Notes
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32. 32▶AI/ML+Physics: Preview of Upcoming Modules and Bootcamps [Physics Informed Machine Learning]Physics Informed Machine LearningNotes
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33. 33▶AI/ML+Physics: Recap and Summary [Physics Informed Machine Learning]Physics Informed Machine LearningNotes
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34. 34▶AI/ML+Physics Part 5: Employing an Optimization Algorithm [Physics Informed Machine Learning]Physics Informed Machine LearningNotes
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35. 35▶AI/ML+Physics Part 4: Crafting a Loss Function [Physics Informed Machine Learning]Physics Informed Machine LearningNotes
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36. 36▶AI/ML+Physics Part 3: Designing an Architecture [Physics Informed Machine Learning]Physics Informed Machine LearningNotes
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37. 37▶AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]Physics Informed Machine LearningNotes
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38. 38▶Ameya Jagtap Enhancing Scientific Computing Through Physics informed Neural NetworksPhysics-informed machine learning meets engineering seminar seriesNotes
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39. 39▶Karan Taneja - Feature Encoded and Multi-Resolution Physics-Informed Machine Learning Approaches...Physics-informed machine learning meets engineering seminar seriesNotes
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40. 40▶AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]Physics Informed Machine LearningNotes
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41. 41▶Lecture 12.1 - New Research Direction (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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42. 42▶Lecture 11.2 - Transference - Part2 (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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43. 43▶Lecture 9.2 - New Generative Models (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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44. 44▶Lecture 9.1 - Multimodal Generation (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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45. 45▶Lecture 7.2 - Multimodal Inference and Knowledge (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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46. 46▶Lecture 7.1 - Multimodal Interaction (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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47. 47▶Lecture 6.1 - Multimodal Transformers - Part2 (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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48. 48▶Lecture 5.2 - Structured Representations and Reasoning (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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49. 49▶Lecture 5.1 - Multimodal Transformers - Part1 (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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50. 50▶Lecture 4.2 - Aligned Representation (CMU Multimodal Machine Learning, Fall 2023)LP MorencyNotes
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