Nathan Lambert and Sebastian Raschka are machine learning researchers, engineers, and educators. Nathan is the post-training lead at the Allen Institute for AI (Ai2) and the author of The RLHF Book. Sebastian Raschka is the author of Build a Large Language Model (From Scratch) and Build a Reasoning Model (From Scratch).
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Mentioned Books
“I think I've tried it in and out of this myself especially trying to like be a manager full-mode training it's a crazy job doing this the book apple in china by Patrick McGee he talked about the how hard the apple engineers work to set up the supply chains in china and he was like they had”
Build a Large Language Model from Scratch
“Sebastian is the author of two books, I highly recommend for beginners and experts alike. First is build a large language model from scratch and build a reasoning model from scratch. I truly believe in the machine learning computer science world, the best way to learn and”
Build a Reasoning Model from Scratch
“Sebastian is the author of two books, I highly recommend for beginners and experts alike. First is build a large language model from scratch and build a reasoning model from scratch. I truly believe in the machine learning computer science world, the best way to learn and”
Reinforcement Learning from Human Feedback
“Nathan is the post-training lead at the Allen Institute for AI and author of the definitive book on reinforcement learning from human feedback. Both of them have great ex-accounts, great sub-stacks, Sebastian has courses on YouTube, Nathan”
Salon founder David Talbot chronicles the cultural history of San Francisco and from the late 1960s to the early 1980s when figures such as Harvey Milk, Janis Joplin, Jim Jones, and Bill Walsh helped usher from backwater…
“I think I would say one of my one people I worked with is moving to SF and it's like I need to get a copy of the season of the witch which is a history of SF from like 1960 to 1985 which goes like the hippie revolution like they all the gays kind of taking over the city and that culture”
The Bitter Lesson
“that was a major like scientific innovation that enabled the next chapter of this and I don't know if it comes in one year or in 15 years yeah well I wonder if the bitter lesson holds true for the next 100 years what that looks like if scaling laws are fundamental and deep learning I think the”