wrhn

Recent submissions

Comment · 4 months ago
It's not just you! Here's a lovely quote from an influential paper, "We offer no explanation as to why these architectures seem to work; we attribute their success, as all else, to divine benevolence." I think people went through a similar phase with steam engines. Lot's of practical engineering and heuristics to explain what works, before the emergence of a solid theoretical foundation (thermodynamics) to explain why.

https://arxiv.org/pdf/2002.05202

Comment · 5 months ago
Cool. It looks like you're packaging the data as json files in the repo. Would be neat to see the pipeline that collects it.
Comment · 7 months ago
This is very cool!

I was wondering why there's factor of ~50 in the ICE index formula. It turns out that factor was selected when the changeover from local currencies to euro happened. The multiplier makes the old formulation agree with the new formulation on the change date. According to Claude, the old formulation had exponents on DEM, FRF, ITL, NLG, BEF that sum up to the current euro exponent. I couldn't find a multiplier for the old formulation (I'm guessing it's selected to make the level 100 at some start date). I guessed a value around 12.5.

I did my best to make a DXY with a long history by stitching together free FRED data here: https://github.com/pandas-user/dxy/blob/main/dxy.ipynb

It's really interesting to see how much of an effect the Plaza Accord had on DXY. One thing I didn't check but might be cool is the ratio between dollar devaluation and positive stock market return during the three 1 year periods starting with the end of Breton Woods, the Plaza Accord, and the 2024 tariff thing.

Comment · 9 months ago
Still happens all the time in certain finance tasks (eg trying to predict stock prices), but I'm not sure how long that will hold. As for why that might be, I don't think I can do any better than linking to this comment about a comment about your question: <https://news.ycombinator.com/item?id=45306256>.

I suspect that locating the referenced comment would require a semantic search system that incorporates "fancy models with complex decision boundaries". A human applying simple heuristics could use that system to find the comment.

In the "Dictionary of Heuristic" chapter, Polya's "How to Solve it" says this: *The feeling that harmonious simple order cannot be deceitful guides the discover in both in mathematical and in other sciences, and is expressed by the Latin saying simplex sigillum veri (simplicity is the seal of truth).*

Comment · 9 months ago
Sorry, what I was clumsily trying to say is something like: "As an outsider to the startup world, your project has made me curious about the shape of the startup ecosystem as a whole. I bet you have the data to generate that picture! It is unfortunate that our market system is not yet sophisticated enough to compensate people for the difficult/valuable work of data collection, while also maximizing availability of data for those curious to use it."

At first I did not explore the tree visualizations in your web app: I simply noticed an index of company trees. Using the tree visualizer (which shows founders' names and pictures), I immediately realized that these trees represent complex human stories involving thousands of years of individual people's hard work. Interpreted that way, the data deserve a degree of awed respect that I did not show in my original comment. Truly sorry for that.

If you're curious about the shape of the startup ecosystem the way I am, there are a few things you could try. (In what follows I'm assuming "full graph" means company-company links with timestamps, not stories about individual people). pyvis has a feature that allows you to build a static html file with an embedded interactive representation of a graph. The data is embedded in the file, so you might not be able to share that unless you dropped enough information to conform such sharing to your data license. IIRC the static file has limited query/filter functionality so it can be difficult to make large graphs manageable for visualization. If that happens you can try using a graph database with a query UI. I remember another HN submission last year that (IIRC) used neo4j as a backend and provided a web UI with this kind of query/visualize workflow. I believe they also shared Github repos with the front-end/back-end code.

Anyway, thank you for sharing your project and sorry for the shit comment.

https://news.ycombinator.com/item?id=45066060

Comment · 9 months ago
Very cool! It looks like you've purchased the data from a vendor, is that right? I love graphs of all kinds, so I was hoping to fetch the raw data and have a look at it with pyvis/networkx.
Comment · 10 months ago
For some reason the article made me think about this quote from one of the 2025 MacArthur Fellowship videos, "I think there are some mathematicians who are kind of like the hiker who choose this massive peak they want to scale and they do everything they can to make it up the mountain. I'm more like the kind of hiker who wanders through the forest and stops to look at a pretty stone or flower and reflect on whether it's similar to a stone or flower that I've seen before."
Comment · 10 months ago
Very cool appendix describing how they collected the data. I was kind of surprised to learn that they collected arXiv abstracts + metadata from Kaggle, but it definitely makes sense. I was also surprised that 6 years of SSRN papers was only ~1.3m documents. If you assume 20 pages/document and 400 words/page and 1.3 tokens/word, then it would only cost (ballpark) $1000 to pass the full corpus through the 4o-mini completions API. I think it would be really neat to build out a "Dataset Used", "Model Used" etc table for SSRN papers. I imagine more complicated questions would be harder to answer (because you might have to analyze non-text parts of the documents).

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