Interesting that they're using TensorFlow. Is TensorFlow still common for new projects or is it because Google is sponsoring the class?
It is not common for new projects. The vast majority of new projects use PyTorch, with some using tensorflow and some using JAX.
MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
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Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#32Earlier quoted context omitted.
It is not common for new projects. The vast majority of new projects use PyTorch, with some using tensorflow and some using JAX.
Can PyTorch be used to implement LLMs / GPT?
Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#33Which is the best course or set of videos to learn the basics of neural networks and deep learning? Something that really gets the best explanation of things like backprop?
cs231n is still a really solid course, despite the more recent lecture videos not being publicly available.
Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#34Bit of a side tangent, but why does MIT upload (or allow the upload) of these videos under the staff member's youtube. Alexander Amini in this case. It makes it hard to find and subscribe to. And also a bit weird from an ownership perspective. For better or worse I think it's how Lex Fridman got his initial boost, I believe his personal youtube channel contained some popular MIT lectures of him at the start.
When I worked in higher ed, I learned that professors retain a lot more ownership of their content than I expected. I don’t know if this is how it works everywhere, but I wouldn’t be surprised if that was the case here.
For example, I work at ETH and we have a large internal video archive of lectures (as do many universities pre- and post-covid), but some lecturers choose to post material on YouTube too. It's not a blanket yes/no policy at the institutional level, as far as I'm aware.
Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#35Which is the best course or set of videos to learn the basics of neural networks and deep learning? Something that really gets the best explanation of things like backprop?
Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#36[flagged]
Exactly. Unfortunately hackernews these days is huge fans of the military and the richest classes without much question. Psyops don't exist, research journalism is tinfoilhattery and all science is awesome science. Question one state and you're apparently fan of another, it's become the perfect setup for the status quo. In reality the US intelligentsia is tiny and unfathomably powerful, an octopus with its arms deep…
Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#37Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#38Earlier quoted context omitted.
It is not common for new projects. The vast majority of new projects use PyTorch, with some using tensorflow and some using JAX.
Can PyTorch be used to implement LLMs / GPT?
Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#39I wonder why that parameter is called "h"? Hmmm ... Why not just say the word "hysteresis" and bring some magnets to class for show-and-tell to help your students develop an intuition for the "h" parameter in RNNs.
Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]
#40I wonder why that parameter is called "h"? Hmmm ... Why not just say the word "hysteresis" and bring some magnets to class for show-and-tell to help your students develop an intuition for the "h" parameter in RNNs.
hysteresis is also important to understand for working with radio networking.