glifchits

Joined 13 years ago

Karma

289

Submissions

131

Member since

Feb 26

georgelifchits.ca

[ my public key: https://keybase.io/george; my proof: https://keybase.io/george/sigs/hwxSi5Atx6NOhCijnZD0Dx_ftH5IXEXIOXY226_eIZs ]

View on Hacker News

Recent submissions

Comment · 5 years ago

Looks like Rust is the "good" solution for all of these?

Comment · 5 years ago

Those are examples of why it is so incredible. To have it in your notes application as seamlessly as Roam does it is a game changer for notes.

Comment · 7 years ago

Right, this sentence made it unclear to me whether they only used the popularity features to compute past-performance, or whether they included past-performance in addition to other popularity features.

To your question, other work on success prediction of tweets [1, 2] demonstrates that past-performance is indeed much more predictive than the typical content features. This way of looking at success of "cultural products" assumes it depends to varying extents on both inherent "quality" (measured by content features), and the social processes of sharing (which are much harder to understand ahead of time, as the paper I referenced in my parent post shows).

[1] Martin, T., Hofman, J. M., Sharma, A., Anderson, A., & Watts, D. J. (2016). Exploring Limits to Prediction in Complex Social Systems. Proceedings of the 25th International Conference on World Wide Web - WWW ’16, 683–694. https://doi.org/10.1145/2872427.2883001

[2] Bakshy, E., Hofman, J. M., Mason, W. A., & Watts, D. J. (2011). Everyone’s an Influencer: Quantifying Influence on Twitter. Proceedings of the Fourth ACM International Conference on Web Search and Data Mining - WSDM ’11, 65. https://doi.org/10.1145/1935826.1935845

Comment · 7 years ago

Did I miss something or does this project include popularity measures as features?

In the section on dataset features, they include "popularity" (calculated by Spotify) as well as Billboard chart stats like weeks, rank, and a custom-made "score". To me it's not clear whether these features were hidden from the train/test sets or whether the popularity features were only used in their "artist past performance" measures.

If they included these popularity features, it's like asking "can we predict whether a song is a hit just by looking at how popular it is?" If it is the case that they peeked into the future and observed ex-post song popularity, obtaining just 89% accuracy hints at how unpredictable song success truly is. Check out [1] for a famous study of song success which experimentally demonstrates the unpredictability of song success.

[1] Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006). Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market. Science, 311(5762), 854–856. https://doi.org/10.1126/science.1121066

Comment · 8 years ago

I would like to see more on the zeta distribution aspect of this, but it doesn't appear anywhere obvious in this repo.

Comment · 8 years ago

I was just thinking that something similar to this would be really interesting for reading/peer-reviewing scientific papers. Scientific knowledge is built atop of claims made in previous papers, each claim having its own statistical strength. It would be awesome if each footnote in a paper was not just a citation to another publication, but a link to the first time that claim was made, with its p-value and sample size prominently displayed.

Comment · 8 years ago

Totally agree, this is just about employing affirmative action, how, and why. And yes, I get the criticism but I haven't heard anything convincing as of yet. The only baffling thing to me is that its critics believe that pure meritocracy is still the flagship solution, when the flaws seem so obvious. I think the author does a great job explaining why for this case.

Comment · 8 years ago

This blog post is good evidence of the quality of thought that exists on the political left, and revives my belief that the left will eventually win the misguided attacks on “political correctness” culture. The comment section reinforces this even further.

Comment · 8 years ago

Interesting! I figured the `as` in a `with` statement was handled uniquely, but I learned something new about Python today:

   x = open('filename')
   x.closed  # False
   with x:
     print(x.readline())
   x.closed  # True

I think you're right. I prefer the `as` variant for readability.

Comment · 8 years ago

In my opinion, you're one of the most entertaining and approachable writers on mathematical topics like QC. How did you get good at writing?

Comment · 8 years ago

This is really vague. Javascript is necessary for building rich web applications. What are the uninteresting problems you see as Javascript's main purpose?

Comment · 8 years ago

I wouldn't have checked this out if I knew it would burn a Medium article access for me.

Comment · 8 years ago

Normally I would agree with you completely, indeed AI is (very) far from perfect. However, I think we're hung up on the home property example. As Vitalik suggests, this proposal works a lot better in situations where the underlying property is more fungible, and the participants in the market are more or less equal. The property example I like from the article is radio spectrum licenses.

I'd also add that using an AI also doesn't necessarily mean something opaque. A hand-made decision tree would be preferable to a neural net, for example. The decision tree could prompt you for your human decision if it encounters an outlying, uncertain instance.

Comment · 8 years ago

Recall there are two goals: - allocative efficiency (property belongs to whomever can derive most value from it) - investment efficiency (people have incentives to invest in property, build Gigafactories, etc)

If I understand, your argument is that self-assessed taxes would eliminate investment efficiency.

The property owner should factor transaction costs into their own value of the building. This would increase their assessment of the land-value, and increase their taxes. This works because, keeping land valuations constant, the one with the highest transaction costs is the one who can derive the most efficiency from the land.

Comment · 8 years ago

I think the property/personal home example is hard to defend. Consider industrial property, such as a factory or warehouse. The most reasonable application of self-assessed tax would be to any property that can be valued on purely economic/objective bases.