Brandon Rohrer who obtained his Ph.D from MIT is driven by understanding algorithms ALL the way down to their nuts and bolts, so he can make them accessible to everyone by first explaining them in the way HE himself would have wanted to learn!
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Brandon Rohrer is a seasoned data science leader and educator with a rich background in creating robust, efficient machine learning algorithms and tools. With a Ph.D. in Mechanical Engineering from MIT, his expertise encompasses a broad spectrum of AI applications — from computer vision and natural language processing to reinforcement learning and robotics. Brandon's career has seen him in Principle-level roles at Microsoft and Facebook. An educator at heart, he also shares his knowledge through detailed tutorials, courses, and his forthcoming book, "How to Train Your Robot."
YT version: https://www.youtube.com/watch?v=4Ps7ahonRCY
Brandon's links:
https://github.com/brohrer
https://www.youtube.com/channel/UCsBKTrp45lTfHa_p49I2AEQ
https://www.linkedin.com/in/brohrer/
How transformers work:
https://e2eml.school/transformers
Brandon's End-to-End Machine Learning school courses, posts, and tutorials
https://e2eml.school
Free course:
https://end-to-end-machine-learning.teachable.com/p/complete-course-library-full-end-to-end-machine-learning-catalog
Blog: https://e2eml.school/blog.html
Ziptie: Learning Useful Features [Brandon Rohrer]
https://www.brandonrohrer.com/ziptie
TOC should be baked into the MP3 file now
00:00:00 - Intro to Brandon
00:00:36 - RLHF
00:01:09 - Limitations of transformers
00:07:23 - Agency - we are all GPTs
00:09:07 - BPE / representation bias
00:12:00 - LLM true believers
00:16:42 - Brandon's style of teaching
00:19:50 - ML vs real world = Robotics
00:29:59 - Reward shaping
00:37:08 - No true Scotsman - when do we accept capabilities as real
00:38:50 - Externalism
00:43:03 - Building flexible robots
00:45:37 - Is reward enough
00:54:30 - Optimization curse
00:58:15 - Collective intelligence
01:01:51 - Intelligence + creativity
01:13:35 - ChatGPT + Creativity
01:25:19 - Transformers Tutorial
