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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]

#11
post #7

I 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.

And for analog electronics in general!

Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]

#12

Earlier quoted context omitted.

Might as well be complete, and filter out websites based on MIT developed programming languages https://en.wikipedia.org/wiki/Hacker_News (Note the programming language, and find what it's based on) https://en.wikipedia.org/wiki/Lisp_(programming_language)

[flagged]

Your nickname is lit. We live in a world where we are not the only superpower. If we will stop developing capable tools for dealing with adversaries, adversaries will use that to their benefit and take advantage of our inferior toolings. Please try to understand what I am trying to say: no-one wants to have blood on their hands, but the reality is that we are not the ones who decide, whether it will be spilled, all we can do is make sure it is not going to be ours. And on a sidenote, the companies you mentioned have achieved some astonishing from the engineering point of view achievements, which I personally admire just because it is state of the art in so many ways.

Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]

#15
post #5

[flagged]

MIT has a lot of great students, staff, and faculty. The MIT Open Courseware and other publicly shared instruction videos are of great benefit to the world. Boycotting any of that sounds silly.

What happened to Aaron Swartz is tragic. Afterwards, there was an internal push to investigate what happened, and the report was made public. I think you'll find a lot of MIT affiliates who share good qualities with Swartz.

Marvin Minsky sadly died in 2016. People interested in the big picture and history of AI might do well to read some of his writings.

There are many valid criticisms, concerns, and opinions about MIT. But MIT is a big place, which attracts people from around the world, for various reasons. If you boycott people due to association with MIT, you're depriving yourself, and also depriving the world of the benefit of collaborations/synergies.

Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]

#16
post #5

[flagged]

> They have blood on their hands and history of silencing and oppressing dissidents such as Aaron Schwartz.

I guess what you have in mind is that Aaron Swartz was arrested by the MIT Campus Police (together with a Secret Service agent). This is not oppression by MIT. The MIT Campus Police received the arrest warrant from a federal prosecutor (Carmen Ortiz) and they needed to carry out the arrest. They did not have a choice in the matter.

If anything MIT was the opposite of what you portray them to be. They had an open campus policy at the time (they stopped that during Covid). Anyone could wander inside the campus and walk through the MIT buildings, and in some cases could access computers, which Aaron Swartz did in order to download articles. Actually, MIT helped Aaron in carrying out his mission.

As for MIT helping the US military, yes, they did and they do that. I'm proud of it. If you think the military is bad, you haven't been paying attention lately, especially in the last one year and a bit.

Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]

#18

Which 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?

I’ve been watching https://karpathy.ai/zero-to-hero.html and they seem amazing so far, literally go to gpt from basic math and programming - he first codes the libs from scratch to show you how the internals work, and only then uses an off the shelf production lib.

Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]

#19
post #18

Which 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?

I’ve been watching https://karpathy.ai/zero-to-hero.html and they seem amazing so far, literally go to gpt from basic math and programming - he first codes the libs from scratch to show you how the internals work, and only then uses an off the shelf production lib.

Yes this is a great course, on every level. I recommend to do the exercises after each lecture to cement the concepts too. The exercises are good too. Stretching but achievable.

Re: MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention [video]

#20
Bit 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.

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