anton_tarasenko

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

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.

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.

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.

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...

[2] https://en.wikipedia.org/wiki/Carlson_curve

[3] https://en.wikipedia.org/wiki/List_of_laws#Technology

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

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:

* Berlin http://www.meetup.com/Berlin-Hacker-News-Meetup/

* Munich https://www.meetup.com/Hacker-News-Munich/

"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.

[1] https://www.cs.cornell.edu/home/kleinber/w23180.pdf

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...

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...

Also Landau and Lifshitz, Course of Theoretical Physics.[1]

Released to public domain on archive.org: https://www.reddit.com/r/Physics/comments/1dmxq7/our_beloved...

[1] https://en.wikipedia.org/wiki/Course_of_Theoretical_Physics

I've updated your links. Thanks!

I maintain the list of offline Hacker News communities.[1]

I have one Japan group.[2] Is it you guys? Otherwise, I'd like to add your permanent page to the list.

[1] https://github.com/antontarasenko/hacker-news-groups [2] https://www.facebook.com/Tokyo-Hacker-News-Community-1696102...

Wayback Machine allows browsing website history by year. Press year, instead of arrows:

— The New York Times: http://web.archive.org/web/19961112181513/http://www.nytimes...

— WaPo: http://web.archive.org/web/19961220172326/http://www.washing...

— Financial Times: http://web.archive.org/web/19970607125328/http://www.ft.com:...

The previous thread: https://news.ycombinator.com/item?id=9362252

A cached copy: http://webcache.googleusercontent.com/search?q=cache:v36n9t1...

Most schools follow Socrates, sort of. Tests and textbook exercises are a conveyor version of "teaching by asking". Just like grades, they works in a perverse way until someone patiently explains the child what's the real purpose of the whole affair.

Direct link: https://www.snappr.co/ycdb

Looks relevant since http://yclist.com/ lacks the three latest batches. YCList has fellowships though.

Very nice!

Imgur allows browsing Reddit subreddits too. For example:

* https://imgur.com/r/dataisbeautiful/top/all

* https://imgur.com/r/EngineeringPorn/top/all

* https://imgur.com/r/TechnologyPorn/top/all

It shows only images hosted by Imgur. Supports Reddit-like path requests, like:

* https://imgur.com/r/dataisbeautiful/top/all

* https://imgur.com/r/dataisbeautiful/hot/all

* https://imgur.com/r/dataisbeautiful/new

* https://imgur.com/r/dataisbeautiful/top/month

Twitter Search does pretty much the same: "(hiring OR job)"[1]. Easy to get relevant results with right keywords.

Also, Twitter already has filters for location and followers.

[1] https://twitter.com/search?q=(hiring%20OR%20job)

Search docs[1], Reddit Wiki in general and their API docs.

[1] https://www.reddit.com/wiki/search

Reddit can also send RSS:

* https://www.reddit.com/r/shutupandtakemymoney.rss?sort=top&t...

AmazonTopRated is invite-only. Hence, no 403.

Reddit Search can do a similar trick: "subreddit:gadgets site:amazon.com", sorted by "top"[1]

It finds only posts, not comments. That's a good thing. Comment karma accounts for a comment's entire content. What if the comment gets upvotes for something other than an Amazon link inside it? Post karma is a bit better in this respect.

Reddit Search supports any domain. So you can search any shop. Like vat19.com and etsy.com.

Reddit allows browsing by domain. Like https://www.reddit.com/domain/amazon.com/top/

Secondly, some subreddits are specifically devoted to product recommendations:

* https://www.reddit.com/r/shutupandtakemymoney/

* https://www.reddit.com/r/IdBuyThat/

* https://www.reddit.com/r/AmazonTopRated/

And Reddit has a JSON output: https://www.reddit.com/r/shutupandtakemymoney.json?sort=top&...

[1] https://www.reddit.com/search?q=subreddit%3Agadgets+site%3Aa...

I once plotted the TSPDT Top 1000 movies by year. That's an all-time ranking voted by critics. The distribution plot peaks around the 1970s and declines since then. For one, post-war European cinema was really great and influenced the American industry.

Now all major movies originate in the same place. The last fresh blood had come mostly from Latin America, Mexico in particular.

And the place for experiments changed. Now it's TV series. If the concept works, they make another season. Two-hour feature films are reserved for proven concepts. For moviegoers, it turns to be more like a social experience, not an arty one.

The SEC uses quite a mild language here. Issuers often avoid mentioning even what they sell: revenue flow, profit, or just hashes. White papers has no traces of legal entities involved, dispute resolution jurisdiction, financial statements.

A proper prospectus:

- https://www.sec.gov/Archives/edgar/data/1447599/000119312515...

And how ICO white papers look like:

- https://detectortoken.com/docs/DetectorToken_White_Paper.pdf

- https://magos.io/bluepaper.pdf

LyX[1] can be a better intro to LaTeX. It was posted on HN before. But really, it's the most powerful WYSIWYG editor for LaTeX, and it still provides access to the .tex source of the document. You can use the interface and learn the language at the same time.

Besides, custom shortcuts make LyX much faster than writing TeX directly with autocomplete.

[1] https://www.lyx.org/

In response, Berkeley is planning to release new and compliant content. Their official statement[1]:

"[W]e have determined that instead of focusing on legacy content that is 3-10 years old, much of which sees very limited use, we will work to create new public content that includes accessible features ... This move will also partially address recent findings by the Department of Justice which suggests that the YouTube and iTunesU content meet higher accessibility standards as a condition of remaining publicly available. Finally, moving our content behind authentication allows us to better protect instructor intellectual property from “pirates” who have reused content for personal profit without consent.

... Berkeley will maintain its commitment to sharing content to the public through our partnership with EdX (edx.org)."

They also released FAQ regarding the old content.[2]

[1] http://news.berkeley.edu/2017/03/01/course-capture/

[2] http://news.berkeley.edu/2017/02/24/faq-on-legacy-public-cou...

I found many must-see movies on these lists:

1. Directors Guild of America's The 80 Best-Directed Films: http://www.dga.org/Craft/DGAQ/All-Articles/1602-Spring-2016/...

2. TSPDT's The 1,000 Greatest Films: http://www.theyshootpictures.com/gf1000_all1000films_table.p...

They aren't about hackers, for sure. But these two lists are more diverse than IMDb 250.

Try movies from the 60s and 70s on these lists. Lots of gems among them.

Any reason for the blind to use this over earbuds paired with Siri, Alexa, or any other voice-based interface?

Previous thread (featuring Ben Horowitz on 21.co): https://news.ycombinator.com/item?id=13485488

Two takeaways:

1. A response looks like this: https://monosnap.com/file/CbRNrj7TUUhaLolVTLYJhrPxUdsYOK

2. A16Z invested in 21.co when it still was a Bitcoin mining hardware startup: https://techcrunch.com/2015/05/18/what-is-21-co-really-doing...

BigQuery also has the public dataset of Wikipedia page views. Handy for quick SQL and sampling.

An intro by Felipe Hoffa (Google): https://www.reddit.com/r/bigquery/comments/3dg9le/analyzing_...

The tone of tech companies does not resonate with the electorate. The Bay Area basically says to America: We have foreigners here who founded some companies and got rich, so we don't want your visa restrictions.

How do tech executives motivate the average American to support this stance? Taxes? IT companies and their owners enjoy a very friendly tax treatment. Jobs? The largest IT companies employ only 20-60k people each (for comparison, Walmart employs 2mn). Product? Software is a tradeable good, so Americans can buy it from anywhere. Pumping GDP numbers? The industry is flat for the last 10+ years.

Tech companies must put something on the table to get better immigration laws.