luminati

How is auth implemented? Is keycloak or another oss package used or was it custom written?

That explains the current state of full stack developers.

This was a great article but unfortunately it made a very glaring error at the beginning which made me quite dismissive of the whole thing. Thankfully I took a second look at it.

The error is that the referenced rfc was not written in 1945 (the internet was not even in existence back then!) It was written in 1996. Maybe the author got confused by the rfc number which is 1945, thinking that was the year that it was written.

What’s the difference between this title and the previously posted one? https://middle-out.io/posts/genghis

Just a title change? Noticed the subtitle and graphics were similar. IMHO, the “genghis” title was much better.

Agree - Slava’s article has gotten a lot of action on hn over the years.

(https://hn.algolia.com/?q=http%3A%2F%2Fwww.defmacro.org%2Fra... 0)

Li-Chen Wang is an amazing person! https://en.m.wikipedia.org/wiki/Li-Chen_Wang

We stand on the giant shoulders of a lot of the early hackers/engineers in the Homebrew club. Hope they get the credit that they deserve.

@dang - can you switch the title to the original.

You do know that the “generosity” is heavily VC funded? Don’t be misled by the .org in Coursera - it’s a for-profit company that has raised to the tune of 400+MM.

[0] https://www.crunchbase.com/organization/coursera

Now how are you planning to return loyalty to the employees whom you’ve hired who work the same way as you?

How is that a sour grapes comment? Is it wrong to point out the Baidu cheating scandal that happened under his watch?

Look - seems like you benefited from his M00C and you’re his fan boy/girl. Good for you but let’s not commit the fatal error of pandering/worshipping at the altar of authority.

Mods, this violates the ‘no editorializing’ rule for posts.

Some feedback - please make it easy to visit your home page or atleast link it on your blog posts. While it was interesting, I was curious to know more about what your company did and couldn’t figure out an easy way to visit your main page to find that out.

The top nav bar links to a sign up page on a different domain which doesn’t mention anything about what you guys do. And the company logo on the blog just links to the main blog page.

s/disclaimer/disclosure

*not every European

For heaven’s sake, European names are not universal

Since you guys are us incorporated and hq-Ed, how were you able to get the legal permits sorted out? Iirc, India has very strict foreign ownership controls on ISPs and telcos.

Also in one of the comments you briefly mentioned that you can help democratize/prevent censorship? But aren’t you guys by law supposed to block certain websites? And wouldn’t your foreign ownership be under scrutiny if some incident were to happen?

First thanks so much for writing this. The gilded world of unicorn CEOs seems all roses and wine from the Techcrunch armchair VC/outside world, so it was eye-opening to read an intimate account of the cold, brutal reality of being one.

That said, I have one question. What on earth was the co-founder doing? Isn't it the whole point of having co-founders so that you can share the trauma? Why did the CEO have to suffer through so much pain all alone?

I know clickbait, hyperbolic titles allow for more, hmm, clicks, but they rarely help make the case for your article.

Since he uses the word "worthless", how does that compare it to folks who graduated in History or anthropology or (running joke in the US) graduated in English?

Think of this: People in poor country, need to do what it takes to better their prospects. So they go for the one industry that pays relatively better. Nothing illogical about it and seems perfectly rational to me. And I can see similar trends in the US too. A lot of lamenting on "how I wished I learned to code, major in CS, etc.", given how drastically better the tech industry pays. https://levels.fyi ICYMI. Oh, the poor worthless English majors.

Also the lack of empathy was quite striking given the author himself is a recent "worthless" graduate of a technical degree - https://www.linkedin.com/in/nilesh-christopher-20831784/ Maybe he comes from an upper-middle class background and was able to pivot into journalism, but the fact that he didn't mention his own background meant that I couldn't take this article seriously.

On a more meta topic, does education always have to "worthful"?

There is also an app/project out of MIT called 'Private Kit', which is primarily designed to address the privacy issue.

[1] https://www.wsj.com/articles/mit-researchers-launch-location...

[2] https://safepaths.mit.edu/

Honest question [not trying to act controversial], especially with all the US-China spat.

Zoom's engineering team is based in China - the product is primarily built out of there. [1]

What guarantee is there that the CCP is not intercepting/backdooring all video communications? Especially in current situations, where so much sensitive information is being discussed via Zoom?

[1] https://www.cnbc.com/2019/03/26/zoom-key-profit-driver-ahead...

See also

[1] Interesting Codebases: https://news.ycombinator.com/item?id=15371597

[2] Show HN: Awesome-code-reading - A curated list of high-quality codebases to read https://news.ycombinator.com/item?id=18293159

Very interesting! I never knew that! Did a bit of googling to verify it. [1]

[1] https://fosdem.org/2019/schedule/event/kubernetesclusterfuck...

See my above comment: https://news.ycombinator.com/item?id=20508786

As you pointed out, since this is an adversarial use case, a robust cryptographic hash function is the way to go. [For a non-cryptographic Hash function, SeaHash [1] would be the best choice, which is violently fast!]

BLAKE2b would have been the perfect choice given the adversarial nature, as it much secure and faster than MD5. [2]

MD5 is so broken, it's really poor choice for any use case - cryptographic (fundamentally broken) or not (fundamentally slow).

[1] http://ticki.github.io/blog/seahash-explained/

[2] https://leastauthority.com/blog/BLAKE2-harder-better-faster-...

You can just try it with this: https://thispersondoesnotexist.com

Summary:

18 papers/algorithms were tested

11 weren't reproducible

7 were repoducible with considerable effort but only 1 clearly outperformed the baseline but still didn't outperform a well-tuned linear ranking method

--

Travis Ebesu et al. 2018. Collaborative Memory Network for Recommendation Systems. In Proceedings SIGIR ’18. 515–524. was the only paper out 18 that was both reproducible and outperformed the baseline but did not consistently outperform a well-tuned non-neural linear ranking method

Reproducible with considerable effort but outperformed by comparably simple heuristic methods, e.g., based on nearest-neighbor or graph-based techniques.

====================

They are:

kDD:

[17] Binbin Hu, Chuan Shi, Wayne Xin Zhao, and Philip S Yu. 2018. Leveraging meta- path based context for top-n recommendation with a neural co-attention model. In Proceedings KDD ’18. 1531–1540. [SIGIR]

[23] Xiaopeng Li and James She. 2017. Collaborative variational autoencoder for recommender systems. In Proceedings KDD ’17. 305–314.

[48] Hao Wang, Naiyan Wang, and Dit-Yan Yeung. 2015. Collaborative deep learning for recommender systems. In Proceedings KDD ’15. 1235–1244.

RecSys:

[53] LeiZheng,Chun-TaLu,FeiJiang,JiaweiZhang,andPhilipS.Yu.2018.Spectral Collaborative Filtering. In Proceedings RecSys ’18. 311–319.

WWW:

[14] Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017. Neural collaborative filtering. In Proceedings WWW ’17. 173–182.

[24] Dawen Liang, Rahul G Krishnan, Matthew D Hoffman, and Tony Jebara. 2018. Variational Autoencoders for Collaborative Filtering. In Proceedings WWW ’18. 689–698.

Non-reproducible:

====================

KDD:

[43] Yi Tay, Luu Anh Tuan, and Siu Cheung Hui. 2018. Multi-Pointer Co-Attention Networks for Recommendation. In Proceedings SIGKDD ’18. 2309–2318.

RecSys:

[41] Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Long-Kai Huang, and Chi Xu. 2018. Recurrent Knowledge Graph Embedding for Effective Recommendation. In Proceedings RecSys ’18. 297–305.

[6] Homanga Bharadhwaj, Homin Park, and Brian Y. Lim. 2018. RecGAN: Recurrent Generative Adversarial Networks for Recommendation Systems. In Proceedings RecSys ’18. 372–376.

[38] Noveen Sachdeva, Kartik Gupta, and Vikram Pudi. 2018. Attentive Neural Archi- tecture Incorporating Song Features for Music Recommendation. In Proceedings RecSys ’18. 417–421.

[44] Trinh Xuan Tuan and Tu Minh Phuong. 2017. 3D Convolutional Networks for Session-based Recommendation with Content Features. In Proceedings RecSys ’17. 138–146.

[21] Donghyun Kim, Chanyoung Park, Jinoh Oh, Sungyoung Lee, and Hwanjo Yu. 2016. Convolutional Matrix Factorization for Document Context-Aware Recom- mendation. In Proceedings RecSys ’16. 233–240.

[45] Flavian Vasile, Elena Smirnova, and Alexis Conneau. 2016. Meta-Prod2Vec: Prod- uct Embeddings Using Side-Information for Recommendation. In Proceedings RecSys ’16. 225–232.

SIGIR:

[32] Jarana Manotumruksa, Craig Macdonald, and Iadh Ounis. 2018. A Contextual Attention Recurrent Architecture for Context-Aware Venue Recommendation. In Proceedings SIGIR ’18. 555–564.

[7] Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, and Tat- Seng Chua. 2017. Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention. In Proceedings SIGIR ’17. 335–344.

WWW:

[42] Yi Tay, Luu Anh Tuan, and Siu Cheung Hui. 2018. Latent relational metric learn- ing via memory-based attention for collaborative ranking. In Proceedings WWW ’18. 729–739.

[11] Ali Mamdouh Elkahky, Yang Song, and Xiaodong He. 2015. A multi-view deep learning approach for cross domain user modeling in recommendation systems. In Proceedings WWW ’15. 278–288.

Considering the choice of hash function of md5, not so bright I guess..

Since both companies' root cause analysis are currently trending on HN, it's pretty apparent that Stripe's engineering culture has a long ways to go catch up with Cloudflare's.

This was quite interesting thanks!

On a related note, does anyone have a good recommendations/blog post that explains how IP addressing, ports, subnetting, etc. all work?

This is one of these things where I know that I'm just working off of empirical knowledge without knowing the fundamentals.

Here is a nice post about this problem: https://keyj.emphy.de/balanced-shuffle/