429 karma · joined December 3, 2015
To address _a_ particular negative comment in this thread.
1. I am often weary of browsing subreddits for their episode discussions because it's quite easy to see spoilers by using the search field, since it will bring up future discussions of episodes where spoilers are allowed. YMMV but this has definitely happened to me before.
2. Some subreddits conveniently have episodes on their sidebar, some only have for the most recent season, some don't have at all
3. _Sigh_ Yes you could of course do this manually: Hacker news hasn't changed a bit lol https://news.ycombinator.com/item?id=9224
If this picks up traction it would be great to see an api so that apps like track.tv and others could pull data from reddit discussions in an structured way :)
A while ago I created something adjacent to this that looks for hacker news review of books on goodreads (https://github.com/spookyuser/hacker-reads)
So I'm very curious how you managed to find book titles, I ran into a lot of issues trying to figure out, for example, with "Clean Code" whether to search for "Clean Code" or "Clean Code: A Handbook of Agile Software Craftsmanship" since people mentioning the book used both instances. And of course someone mentioning just "Clean Code" might be referring to the concept not the book. I ended up settling on `${titleMinusColon} - ${author}` but I'd love to know what your approach was given that you used deep learning to search.
EDIT: Just read your comment below on your approach, very interesting!
Same! Some of my favorite book recommendations have especially come from this one, I don't know why but a one line comment on a HN thread of "what book changed your life" has become my favorite way for discovering books.
I can't speak to whether or not using copilot in long lasting projects would be a good idea, but even if you just tagged the copilot generated code with a comment that said '#TODO: Verify this is correct' I still think it would help you get a lot of work done that you would normally have to switch to stackoverflow to do.
One thing that I found very interesting from the article was the idea of anchoring bias, I definitely felt this a lot. When I used copilot to generate some nontrivial functions that were directly related to my problem, if the code did not work and I ended up erasing the generated code completely, I am just realising now that when I reimplemented it myself I was still essentially using the algorithm copilot had come up with.
I've recently been watching Look Around You and I have to assume that season 2 was directly inspired by this clip, the similarity is uncanny.
An example: https://www.dailymotion.com/video/x7t2yhw
def build_agi(CEV):
"""Build an AGI with the specified CEV"""(2) In march I spent way to long on an extension that adds Hacker News Comments to Goodreads https://chrome.google.com/webstore/detail/hacker-reads-for-g...
If people are interestead in reading it, I would highly recommend the audio book/podcast, it's extremely well produced and features an insane amount of good voice acting [1]. Though I would definitely recommend _not_ listening to it in podcast player, and instead use one of the stitched together mp3s.
It uses the Algolia search API to find comments that match the title and author of a book page on Goodreads. Initially I wanted to use ISBN numbers but there are too many comments mentioning books on HN that don't use the ISBN number and for some reason Amazon links are rarely indexed without truncation by Algolia, which means the end bit of a long Amazon url that contains the ISBN isn't searchable.
The hardest part of this extension was figuring out how people write book titles. For instance, most people don't seem to write out full book titles rather they write out the title minus any subtitles. Because of this, if you search for the exact Goodreads title on Hacker news you won't find that many comments, and what turns out to work much better is searching for books without any subtitles.
Also worth mentioning that this is similar to https://hackernewsbooks.com/ (which I enjoy a lot) except instead of seeing HN's favorite books you see all opinions good and bad, and you can also see them directly in Goodreads.
You can download it for Chrome [1] or Firefox [2] or see the source code on Github [3].
Hope you like it :)
[1] https://chrome.google.com/webstore/detail/ohkekgnmihdgcfflhe...
[2] https://addons.mozilla.org/en-GB/firefox/addon/hacker-reads-...
I've personally been using this in my browser while I've been building it and have definitely enjoyed having it around.
One of my favorite things about HN are the book recommendations you can find from other users, especially in those long "Ask HN: What are you reading" threads. I've found some of my favorite books by going through those kinds of threads. At the same time, while I am a Goodreads user, I almost never look at the user reviews at the bottom of Goodreads because I find they do such a bad job at selling me on why I should read a certain book. Often, they're just beat by beat summaries of what occurs in a book and don't say anything about why you might want to read it. Whereas, I think the opposite is true on HN. When people recommend books here it's, in my experience, brief and much more meaningful, and seeing a single person on HN saying: "this is my favorite book ever" + child comments that say the same thing, makes me much more interested in reading a book than almost anything else could. So, I wanted to bring that experience to Goodreads and that is why I decided to build this.
It's far from perfect, and will display comments that aren't relevant just as soon as it will not display enough comments. However, after quite a bit of tweaking, I think the extension is at the point where it's pretty useful - even with these issues.
I would love to hear any feedback or suggestions you might have. Thanks!