anton_tarasenko
Joined 11 years ago
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149
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Feb 2
https://github.com/antontarasenko
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Comment · 6 years ago
Maker here. I've put together several custom search engines that helped me fight poor Google search performance on certain queries. The search engines use Google Custom Search Engine configured for selected websites and return succinct results on general queries, especially the queries attracting SEO spammers.
The engines are listed on https://searchcommons.org/engines.html and here are some of them:
— The web minus Alexa top 1000 most visited websites https://searchcommons.org/?e=most-visited-websites-excluded
— Official docs for Python and its libraries https://searchcommons.org/?e=python-docs (feel free to request an engine for your programming language)
— Universities with Nobel Prize, Fields Medal, and Turing Award laureates https://searchcommons.org/?e=universities-with-laureates
The lists of selected websites are public and open to contributions: https://github.com/antontarasenko/searchcommons
Comment · 6 years ago
The AIP also maintain free access to their oral histories: https://www.aip.org/history-programs/niels-bohr-library/oral...
They interviewed many famous physicists. Mostly autobiographical, but unlike in books, the interviewees don't have time to edit the answer, so the reading experience is generally better.
Comment · 6 years ago
Subreddit /r/askscience does a good job at explaining science in plain words. I usually google "site:reddit.com/r/askscience/ __QUESTION__".
The StackExchange sites have less coverage and answers tend to be more technical.
University websites return reliable answers, but often neither short nor accessible.
Comment · 7 years ago
Thank you for going after primary sources.
The sample letter refers to the press. Executives tend to be general with the press. Investors make them talk specifics. That happens during quarterly earning calls. Which would be a good source. Seeking Alpha has the transcripts.
The SEC filings are another liable source. Though not personal quotes, they include perspectives on tech trends.
Comment · 7 years ago
The Wikipedia page on Moore's law includes similar observations.[1] For example, the DNA sequencing cost.[2]
And another list that features laws, some of which describe exponential processes.[3]
[1] https://en.wikipedia.org/wiki/Moore%27s_law#Other_formulatio...
Comment · 7 years ago
In terms of depth and breadth, the Princeton companions get close to Feynman.[1][2]
A more formal approach appears in handbooks.[3][4]
[1] Gowers et al., The Princeton Companion to Mathematics. https://press.princeton.edu/books/hardcover/9780691118802/th...
[2] Higham and Dennis, The Princeton Companion to Applied Mathematics. https://press.princeton.edu/books/hardcover/9780691150390/th...
[3] Zwillinger, CRC Standard Mathematical Tables and Formulae. https://www.crcpress.com/CRC-Standard-Mathematical-Tables-an...
[4] Bronshtein, Handbook of Mathematics. https://www.springer.com/gp/book/9783540721222
Comment · 7 years ago
I'm collecting HN meetup groups on GitHub: https://github.com/antontarasenko/hacker-news-groups (BTW, thanks to all contributors from HN)
@lainon HN meetups in Germany:
Comment · 7 years ago
"Algorithmic justice" reminded me of a study where researchers predicted the risk of a crime better than judges:[1]
> Millions of times each year, judges must decide where defendants will await trial—at home or in jail. By law, this decision hinges on the judge’s prediction of what the defendant would do if released. This is a promising machine learning application because it is a concrete prediction task for which there is a large volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the single variable that the algorithm focuses on; for instance, judges may care about racial inequities or about specific crimes (such as violent crimes) rather than just overall crime risk. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: a policy simulation shows crime can be reduced by up to 24.8% with no change in jailing rates, or jail populations can be reduced by 42.0% with no increase in crime rates.
Comment · 7 years ago
Milton Friedman on doing this in the 1940s:[1]
> One of my problems was to provide statistical advice to the people who were developing metals to be used in the blades of turbines. I had an enormous amount of data, and I had to construct a regression with five or six different variables having to do with the chemical composition of the metals.
> We estimated that it would take us three months to solve this problem using our desk calculators. In the whole country there was only one calculator—one computer, if you want to call it that—which could do this problem more quickly.
> It was up at Harvard. It wasn’t electronic. It was a whole collection of IBM card sorters. It was in a big, air-conditioned gymnasium, a tremendous collection of sorters all linked by wires. It did our problem for us in forty hours.
As he mentioned elsewhere, it did not work as expected back then.
[1] https://miltonfriedman.hoover.org/friedman_images/Collection...
Comment · 7 years ago
Freeman Dyson reviews and extends "What is Life?" in his "Origins of Life," both a lecture[1] and a book.
[1] http://inspirehep.net/record/1268726/files/978-4-431-77056-5...