Someone posts on X, "These are Ilya’s 30 papers", gives no source, doesn't say where he got it from, and isn't connected to either Ilya or Carmack (Ilya gave him the list).
Then someone vibe codes a barely usable website based on that, and it lands on the HN front page? Is this correct?
After seeing this for the first time, I've build PdfToMp3 to listen to these papers. It has now evolved into ListenDock. Fun fact: PdfToMp3 existed before NotebookLM and I already had "overviews", but I called them teacher explanations.
Here is an example of a "Teacher Explanation" of the paper "Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton"
I wish this were organized according to suggested/logical reading order. For example, the paper introducing the attention mechanism probably ought to precede "attention is all you need".
Noting the theory papers on Kolmorogov complexity. For those not familiar, Ilya argues that the reason why neural networks generalize -- why they work at all -- is because they are effectively finding a simple description of their training data, converging down onto the limit of the Kolmorogov complexity. [1]
Author here. First year CS student at Trinity College Dublin. I Built this because when I was getting into reading research papers I ended up burning a ton of my Claude usage asking questions other people have probably already asked. The website is just a side project and definitely a WIP. Happy to answer questions or take PRs on GitHub.
As an aside, I've seen folks mention respecting reduced animation hints and such in the past and was always curious about this because I've never had any negative experiences with animations... until now!
Something about the animations on this site did my brain in while scrolling through the papers, and now I "get it."
I was confused for a minute, I thought this was "top 30 papers by Ilya" and was then wondering why "Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton" is on the list.
> In additition, even though I have read the vast majority of the papers featured on the website, I have not read through each of the website's versions end to end.
Website's versions, as in - the actual text or the "explanations"? Either way this is a big red flag.
I thought the actual 30 papers have never been disclosed. Do you have a source tying the recommendations back to Ilya, or did you come up with this list?
If you find this interesting, you should look into Solomonoff induction. It combines Kolmogorov complexity with Bayes rule to provide a general framework for inductive inference, and naturally formalizes Occam's razor.
I wouldn't say so about Occam's Razor which is a heuristic.
The relationship between compression and intelligence, while not equal is definitely there. It looks like 3Blue1Brown is going to be doing some videos on this aspect.
The formatting of the articles on this website is bad. I've opened the first one and all the LaTeX formulas are messed up. The subscripts and superscripts are all flattened rendering the math hard to comprehend. Did the author actually try to read any of the articles?
>∏ plocal(x|z) = i p(xi|z,xWindowAround(i))
Images and tables are not rendered at all. What is the point of this? Just keep the links to arxiv and leave it at that, otherwise render the articles properly
Why on earth would you deliberately choose to do whatever the fuck it is you did with the scroll and the animations for each paper when scrolling through the landing page? What are those animations supposed to be? I use firefox but I also visited on chrome, and the page is even more broken there. Scroll doesn't "take" unless I scroll hard enough, otherwise it bounces back. But on chrome, at least, it seems like the animation for each paper is clearer - it's supposed to be animating the scale of the paper as you scroll to it.. but it seems that your background animation is lagging everything so much it just doesn't work.
Then someone vibe codes a barely usable website based on that, and it lands on the HN front page? Is this correct?
" rumoured list of papers that Ilya Sutskever gave to John Carmack. "
there is aslo manning book called illya list
https://www.manning.com/books/sutskevers-list
Here is an example of a "Teacher Explanation" of the paper "Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton"
https://listendock.com/e/quantifying_the_rise_and_fall_of_co...
[1] https://www.youtube.com/watch?v=AKMuA_TVz3A
As an aside, I've seen folks mention respecting reduced animation hints and such in the past and was always curious about this because I've never had any negative experiences with animations... until now!
Something about the animations on this site did my brain in while scrolling through the papers, and now I "get it."
Is it just rehosting the list, plus a reformatted copy of the papers? I was hoping you'd have at least annotated them with what you'd learned?
> In additition, even though I have read the vast majority of the papers featured on the website, I have not read through each of the website's versions end to end.
Website's versions, as in - the actual text or the "explanations"? Either way this is a big red flag.
I'd recommend watching a few of his talks/podcasts before during reading these to get the overview and how all the bits in these works tie together.
https://www.dwarkesh.com/p/ilya-sutskever
https://simons.berkeley.edu/talks/ilya-sutskever-openai-2023...
https://www.dwarkesh.com/p/ilya-sutskever-2
CS231n: Convolutional Neural Networks for Visual Recognition - https://cs231n.github.io/
The Unreasonable Effectiveness of Recurrent Neural Networks - https://karpathy.github.io/2015/05/21/rnn-effectiveness/
Understanding LSTM Networks - https://colah.github.io/posts/2015-08-Understanding-LSTMs/
ImageNet Classification with Deep Convolutional Neural Networks - https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436...
Deep Residual Learning for Image Recognition - https://arxiv.org/abs/1512.03385
Multi-Scale Context Aggregation by Dilated Convolutions - https://arxiv.org/abs/1511.07122
Identity Mappings in Deep Residual Networks - https://arxiv.org/abs/1603.05027
Recurrent Neural Network Regularization - https://arxiv.org/abs/1409.2329
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin - https://arxiv.org/abs/1512.02595
Order Matters: Sequence to Sequence for Sets - https://arxiv.org/abs/1511.06391
Neural Machine Translation by Jointly Learning to Align and Translate - https://arxiv.org/abs/1409.0473
Pointer Networks - https://arxiv.org/abs/1506.03134
Attention Is All You Need - https://arxiv.org/abs/1706.03762
The Annotated Transformer - https://nlp.seas.harvard.edu/annotated-transformer/
Neural Turing Machines - https://arxiv.org/abs/1410.5401
A Simple Neural Network Module for Relational Reasoning - https://arxiv.org/abs/1706.01427
Relational Recurrent Neural Networks - https://arxiv.org/abs/1806.01822
Neural Message Passing for Quantum Chemistry - https://arxiv.org/abs/1704.01212
Scaling Laws for Neural Language Models - https://arxiv.org/abs/2001.08361
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism - https://arxiv.org/abs/1811.06965
Keeping Neural Networks Simple by Minimizing the Description Length of the Weights - https://www.cs.toronto.edu/~hinton/absps/colt93.pdf
A Tutorial Introduction to the Minimum Description Length Principle - https://arxiv.org/abs/math/0406077
The First Law of Complexodynamics - https://scottaaronson.blog/?p=762
Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton - https://arxiv.org/abs/1405.6903
Kolmogorov Complexity - https://onlinelibrary.wiley.com/doi/book/10.1002/047174882X
Variational Lossy Autoencoder - https://arxiv.org/abs/1611.02731
Machine Super Intelligence - https://www.vetta.org/documents/Machine_Super_Intelligence.p...
It's unknown whether it has anything to do with Ilya Sutskever.
The relationship between compression and intelligence, while not equal is definitely there. It looks like 3Blue1Brown is going to be doing some videos on this aspect.
https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436... https://papers.nips.cc/paper_files/paper/2012/file/c399862d3...
https://arxiv.org/pdf/1512.03385
https://arxiv.org/pdf/1511.07122
https://arxiv.org/pdf/1603.05027
https://arxiv.org/pdf/1409.2329
https://arxiv.org/pdf/1512.02595
https://arxiv.org/pdf/1409.0473
https://arxiv.org/pdf/1506.03134
https://arxiv.org/pdf/1706.03762
https://nlp.seas.harvard.edu/annotated-transformer/
https://arxiv.org/pdf/1410.5401
https://arxiv.org/pdf/1706.01427
https://arxiv.org/pdf/1806.01822
https://arxiv.org/pdf/1704.01212
https://arxiv.org/pdf/2001.08361
https://arxiv.org/pdf/1811.06965
https://www.cs.toronto.edu/~hinton/absps/colt93.pdf
https://arxiv.org/pdf/math/0406077
https://scottaaronson.blog/?p=762
https://arxiv.org/pdf/1405.6903
https://onlinelibrary.wiley.com/doi/10.1002/047174882X.ch14 https://github.com/Bladefidz/information-theory/blob/master/...
https://arxiv.org/pdf/1611.02731
https://www.vetta.org/documents/Machine_Super_Intelligence.p...
https://karpathy.github.io/2015/05/21/rnn-effectiveness/
https://cs231n.github.io/
https://www.zotero.org/
https://www.zotero.org/support/adding_items_to_zotero#add_it...
>∏ plocal(x|z) = i p(xi|z,xWindowAround(i))
Images and tables are not rendered at all. What is the point of this? Just keep the links to arxiv and leave it at that, otherwise render the articles properly
I would request the author to consider something that does not distract us from this educational and informative website ( I have bookmarked it ).