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costco

2,441 karma · joined December 30, 2019

chrisjtarry \at\ gmail.com

https://github.com/chris124567

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costco··on Show HN: Automatically hide flamebait/shallow/political comments on HN
Wow that was quick :) Meh, I feel like comment points have become somewhat untethered to comment quality (at least assuming threads are roughly sorted by comment score). It’s a good heuristic usually but it’s wrong often enough for it to be difficult to rely on.

I want to improve the classifier scores too. There’s some parameters in the loss function I could play around with more when training which basically optimize for more false negatives or false positives. Problems with no ground truth are very frustrating lol (though I suppose dang/tomhow’s manually written warnings could be treated as labels instead of using labels from GPT, but I suspect there’s not enough of them).

costco··on Nvidia agrees to acquire Hugging Face for $13B
This is the last time I will engage in self promotion for a while but the above comment and some of its replies are a perfect demonstration of my latest guidelines violations project… https://classify.stylometry.net/violations/49458425?threshol...
costco··on Show HN: Automatically hide flamebait/shallow/political comments on HN
That’s very nice. Feel free to integrate if you want :) Just request https://classify.stylometry.net/violations/49458161 or whatever item ID (as long as it was posted later than a few weeks ago) and it will return the scores for that post/comment and all its children.
costco··on U of Michigan drops first-semester grades to ‘curb mental health crisis’
I'm pretty sure you would get into Berkeley with that profile. Also you can just major in math and get a job as a software engineer anyways. I agree that the system has reached the point of absurdity though. ETH Zurich and KU Leuven have the best solution to this issue in my mind, which is to let everyone in but make the classes ridiculously hard so that 50% leave in the first year.
costco··on Writing by hand is good for your brain
Very interesting. Hunter S. Thompson described the same technique for learning to write. I'll try it even if it only gets applied to technical blog posts...
costco··on How to stop Claude from saying load-bearing
If you put important Anthropic blog posts like the Fable announcement or J-Space through Pangram, you get 100% human written. Considering that the overwhelming majority of the code there is written by AI, I think this is an admission that AI writing is slop and AI code is pretty good.
costco··on To study how chips work, MIT researchers built their own operating system
Related (2019):

https://gamozolabs.github.io/metrology/2019/08/19/sushi_roll...

https://gamozolabs.github.io/metrology/2019/12/30/load-port-...

costco··on Security through obscurity is not bad
reCAPTCHA is a great success story of security through obscurity because probably less than 100 people have reverse engineered it and much less than that have produced a working solver for it that doesn't require a headless browser. Snapchat would be another good example - almost no one is going to put in the work to understand this [0]. Most companies just half ass it though and accordingly achieve nothing with the obscurity at all besides worse performance.

[0] https://web.archive.org/web/20201128060507/https://hot3eed.g...

costco··on Airline adds bunk beds for economy travelers but bans snacks, smells and cuddles
I wish we lived in a world where price wasn't the only way to filter out annoying passengers... if this experiment works maybe it will prove you can offer amenities more widely if you set high standards. I want an airline where at the end of the flight you rate the people next to you thumbs up or thumbs down and if someone gets >= 3 thumbs downs they are banned from the airline for 5 years. Eventually ordinary people would be able have the serene experience that only those in first class can presently enjoy as the people who get up thirty times to retrieve items from carry on or eat obnoxiously are removed.
costco··on Show HN: I built an SDK that scrambles HTML so scrapers get garbage
This is an interesting idea... it'd be a fun side project to implement enough of a CSS engine to undo this
costco··on Xweather Live – Interactive global vector weather map
This is awesome and very fast especially given all the data displayed!
costco··on Dark web agent spotted bedroom wall clue to rescue girl from abuse
This wouldn't have helped here but there is a related field of research called hotel recognition. Many of these videos are filmed in hotels so being able to recognize if it was a Mariott or even better a non chain local hotel can be very helpful to investigators. They basically train CNNs that learn to pick up on the bathroom fixtures or kind of bedding used by different hotels. One researcher in particular has done a tone of work on this: https://scholar.google.com/citations?user=mNoB9SgAAAAJ&hl=en

I wonder if you could get the interior of every house from Zillow/realtor websites and then do something like this for every house in the country... Clearview for bedrooms?

costco··on Why does SSH send 100 packets per keystroke?
I think he's referring to CPU mitigations: https://en.wikipedia.org/wiki/Transient_execution_CPU_vulner...
costco··on Court report detailing ChatGPT's involvement with a recent murder suicide [pdf]
Protip: Settings -> Personalization -> Base style and tone -> Efficient largely solves this for ChatGPT
costco··on Counter Galois Onion: Improved encryption for Tor circuit traffic
The malleability of the ciphertext matters because it enables certain circuit tagging attacks as the article explains. It means that the exit relay could confirm you are using a guard relay also controlled by them and thus discover your origin IP address.

There are many reasons that these cryptographic tagging attacks are a lot worse than just the timing correlation attacks that are possible if you control the guard and exit of a client: https://archive.torproject.org/websites/lists.torproject.org...

costco··on Building a Minimal Viable Armv7 Emulator from Scratch
Nice article and especially so for including the parsing that most people just outsource. What's great about using an emulator is that you can also do fun things with the syscalls like implementing your own "virtual filesystem" instead of just translating directly to the x86_64 equivalent syscall: https://github.com/gamozolabs/fuzz_with_emus/blob/master/src... (not my code but basically something like this)
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
OK, I think the problem was that you are only supposed to input the user ID number. I just limited the form to numbers only and updated the description to make this more clear.
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
Hi, I just realized that the confusion here was that you are only supposed to input the numeric user ID. I just limited the form to numbers only and updated the description to make this more clear.
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
I am not familiar with Cinematch, is there a writeup about it? When training I used every input book and did not include ratings as a feature. In the future I want to experiment with treating 1 or 2 star ratings as negative feedback.
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
Can you access your profile page in incognito (ie is your account public)? Alternatively, if you have more than 5000 books in your shelf, that might break it. I just tried a number of users and I was able to import them all.
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
I did not add what you requested exactly because I think in many cases authors have written less popular books that people may not be aware of but if you try again you should see less highly repetitive things like 5 of the same series in a row in the results.
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
I just introduced something [1] which should give you much less repetitive recommendations if you want to try again.

[1] https://www.cs.cmu.edu/~jgc/publication/The_Use_MMR_Diversit...

costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
Hi, I just added something called maximal marginal relevance which should give you much less repetitive recommendations.
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
Do you just adding the similar button that the input books have to the output books?
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
What do you think the probability that someone else read 15 books you also read is? It’s very unlikely unless they are all staples of a genre, part of the same series, or just extremely popular in general. 3-5 books is how much I would use on that page. I have found interesting accounts of medievalists, people who work at think tanks, etc with it.

Fake users I would agree should be filtered, but I don’t think filtering out users who gave it a bad review is necessarily the intended behavior. If I put in 3 semi obscure Russian history books, I am presumably looking for someone who is an expert in Russian history to see what else they read. In that case I don’t care if they didn’t like one of the books or not. Approximate matches would require something like LSH or cosine similarity of average input book embedding against average embedding of read books of every user which I think wouldn’t work well anyone for retrieving anyone with a moderately long interaction history.

costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
Yeah, the latter are just because they are popular. If you have 3+ books you tend to get less random popular books included
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
You may find these better:

https://book.sv/similar?id=211570

> Note 1: If you only provide one or two books, the model doesn't have a lot to work with and may include a handful of somewhat unrelated popular books in the results. If you want recommendations based on just one book, click the "Similar" button next to the book after adding it to the input book list on the recommendations page.

costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
This is a result of the use of positional embeddings, which typically results in the final item being weighted very highly. The problem is that this information is shown to be very relevant to the task of predicting the next item interacted with. If you add more books the effect of this is somewhat diluted.
costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
Thank you for the kind remarks. I would say your request is reasonable and it’s something I thought about but it’s worth noting that if you scroll down on a Goodreads book page you can see all of the users who gave it 1 star, 2 stars, etc (not just reviews, ratings too). And in fact Goodreads does not tell people this but these lists include private users. So someone looking to cause controversy would probably just find an incendiary book and look for everyone who gave it 5 stars. My data does not include people who marked their account as private or only visible to those who are signed in and also does not give information on stars. It is also very easy to remove your data if you are so inclined. I only log request URLs but I can tell that many thousands of people visited the site and less than 10 opted out despite “Remove My Data” being prominently displayed and referenced in the attached text to my post.

Also, I don’t use them but based on forum posts I read I think other services like LibraryThing or Storygraph do expose similar information about book readers.

costco··on Show HN: I scraped 3B Goodreads reviews to train a better recommendation model
You don't have to import your Goodreads profile. You can type titles and authors in the box and find books to add to the list that way.
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