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?

But given the sudden wide audience, a quick "here's what this is for" at the top might be helpful.

why do you care? this is a disingenuous question.

Then the foreground content is doing an in/out undulation on top. So you’re seeing an undulating in/out in every possible direction + the background. And the foreground animations are all at the same time. So it’s not that we’re emphasizing any one thing. We’re emphasizing all of it.

The key with animations is in what they’re trying to draw attention to, the character of the movement, and the timing of it. You usually don’t want everything to equally animate at once.

I would: • Use background movement that also isn’t a “wave” • Stagger the timing of foreground animations so the main content is emphasized, followed by a pause, followed by the sidebars • Change the nature of the animations so they’re not doing the same essentially thing “zoom and pan” - so have the center zoom and pan, but do something different for the sides.

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 think the biggest problem people / I had when reading the list was the "based on a rumoured list of papers that Ilya Sutskever gave to John Carmack."

Where did you get the "rumoured list" from ? Why should a reader trust the rumours ? That seems to be a pretty big appeal to authority, and it's okay if it's only "word of mouth" (as most papers seems legit), but it's really weird not to give a source, or a backstory, or references, etc...

Especially since you claim to only have 27 ;)

If there are any suggestions that anyone has for things that would help them with the papers I will definitely add them. My main goal is to make this as easy as possible for people to use

I would request the author to consider something that does not distract us from this educational and informative website ( I have bookmarked it ).

> 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

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.

>∏ 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

It's unknown whether it has anything to do with Ilya Sutskever.

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/

  for x in 1611.02731 1511.06391 1811.06965 1512.03385 1511.07122 1704.01212 1409.2329 1512.02595 1706.01427 1410.5401 1806.01822 1706.03762 1409.0473 1506.03134 2001.08361 1405.6903 1603.05027 math/0406077; do curl -fL https://arxiv.org/pdf/$x -o ${x##*/}.pdf; done
  for u in https://www.cs.toronto.edu/~hinton/absps/colt93.pdf https://proceedings.neurips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf https://www.vetta.org/documents/Machine_Super_Intelligence.pdf https://www.lirmm.fr/~ashen/kolmbook-eng-scan.pdf https://scottaaronson.blog/?p=762 https://karpathy.github.io/2015/05/21/rnn-effectiveness/ https://colah.github.io/posts/2015-08-Understanding-LSTMs/ https://nlp.seas.harvard.edu/annotated-transformer/ https://cs231n.github.io/; do curl -fLO "$u"; done

https://www.zotero.org/

https://www.zotero.org/support/adding_items_to_zotero#add_it...

[1] https://www.youtube.com/watch?v=AKMuA_TVz3A

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...

``` console.log( Object.values(jsonObj) .map(v => `${v.title} - ${v.sourceUrl}`) .join('\n\n') ); ```

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

Then someone makes a shitty comment. Is that correct?

From my point of view the Jedi are Evil

This page is an LLM prompt response as a list of jpegs with a fake title. In fact you can probably just add "and prepare it as a webpage with image previews for each" ...

I think we can do better than someone shitposting a sentence into openclaw and posting it to the hn frontpage.

People on here are like, you know, actually building 100 billion dollar companies and publishing in prestigious journals, maintaining transcontinental infrastructures with global reach... let's hear from them instead of a mac mini going burr for 15 seconds.

More seriously though, in many ways HN is a pretty broad church. You're always going to get a spectrum of opinions, and some portion of people are always going to be particularly forceful about putting forth their opinion. Maybe it's a bad day, maybe it's habit, varies from person to person and day to day, etc.

But I think, if you're posting something to HN (or, really, any large internet forum), negative feedback - and dismissive feedback - is something you need to be prepared for as part and parcel of the experience because it often is going to happen.

Not that I agree with the person you're responding to - their remark struck me as quite a mean-spirited and unnecessary comment, and I very much prefer your perspective.

Anyway, I've bookmarked the site so make of that what you will.

I'm relatively immune to a lot of things, but we're also entering a world where a lot of people can build and might not expect to have potentially millions of people critiquing their work to the level they do.

OK. Let's RFM: first line = "Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes."

So, no, it's not HN-OK for rude & unfounded feedback to make it to the top comment.

Even if the website is "bad" (i.e. those 30 papers were never linked to Ilya etc.), the proper way of handling this is to call it out in a neutral way.

What I'm saying is that in large online forums - regardless of terms of use - some people are unkind, and that it's a good idea to be prepared for that when you post something publicly.

I have no problem that someone had a bad reaction to this and needs to vent, I have a problem that the community deems it the most noteworthy comment and keeps it voted to the very top of the thread.

You would think a university student would understand the importance of citing sources.

If he was really excited he would have put an effort and he wouldn't clickbate submission title.

But alas here we are, perhaps we should give him particpation star for effort.

...who somehow hasn't yet learned the importance of citing sources?

Any and all criticism is deserved.

close enough imo

any apparently 400 voters too.

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...

Text to speech summarizing is a dime a dozen. Your audience here prefers reading a blog and is already annoyed by ai vs written by a human content so what you are offering is the opposite of what they want.

I think it'd work better if you featured the animated background effect toward the top of the page and shifted toward static graphics (or much subtler animations) as the user scrolls.

And I don't think the zoom-out effect on the listing cards has the intended effect; I found myself wanting to get a better look at the papers and was a little disappointed/annoyed when they got smaller and harder to see as I pulled them into view.

The colors/shadows/layout all looks really nice, but I feel like the animations (as-is) ultimately detract from the experience rather than add to it. Thanks for sharing, though!

A large number of people complained about how intense some of the backgrounds/animations were (I might have been a bit too focused on making something that looked cool over usability). In response I have added toggles for both the movement on the page and the backgrounds for the papers.

Other people mentioned that they would have liked some more personalised reflections on each paper. I currently have already done some of these for the more popular papers on my X @notmcrowley . I would have no problem adding these to the site if people think it will help. I feel the need to warn that I have not been formally educated on ML or AI so any interpretation will just be mine and may not necessarily be the correct one. (If anyone with more experience would like to contribute to this feel free to reach out).

It actually made me check my browser wasn't set to zoom out. But then using zoom changes nothing, which breaks accessibility.

Also why does the header need to take up 3/4 of the screen?

[edit] Clicking on a paper doesn't even bring the paper up. I have to hit another click to get to it.

https://x.com/keshavchan/status/1787861946173186062

In my opinion, whether it was actually by Ilya or not is not worthy of debate. Many of them are widely recognized for being good pedagogical resources (e.g. annotated transformer, unreasonable effectiveness of RNNs, understanding LSTM networks), and others are landmark papers which anyone interested in the field would benefit from reading:

- Krizhevsky et al. (2012) introduced AlexNet

- Bahdanau et al. (2014) introduced attention

- He et al. (2015) introduced ResNet

- Vaswani et al. (2017) introduced the Transformer

Other papers are more specialized. Of them, I think Kaplan et al. (2020) by OpenAI is probably most important.

in case folks are interested, i wrote up a ~layman's review of each paper over the course of two years a while back. Several of those reviews ended up doing reasonably well on hn. Full analysis of the ~23 docs that were papers and not massive books

https://12gramsofcarbon.com/p/ilyas-30-papers-to-carmack-tab...

If you want to improve it I would recommend coming up with a sequential "reading list" including a few classic papers, some intermediate advancements (frequently referenced), and then a few new, cutting edge articles.

https://mfaulk.github.io/2024/06/19/ilya-papers.html

The list is simply made up, as confirmed by John Carmack.

""" John Carmack @ID_AA_Carmack I rather expected @ilyasut to have made a public post by now after all the discussion of the AI reading list he gave me. A canonical list of references from a leading figure would be appreciated by many. I would be curious myself about what he would add from the last three years. """

https://x.com/ID_AA_Carmack/status/1622673143469858816