Research for Practice: Expert-curated guides to the best of CS research | Hacker News Reader

Research for Practice: Expert-curated guides to the best of CS research

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162 pointsingve13 comments

I love this idea! I'm just a working programmer, but right now I'm trying to read through the highlights on research into temporal databases. People have been writing papers for 25-30 years, but it seems like not a lot has made its way into everyday practice or commercial products. Something was almost added to the SQL standard around 1997-2000, but was eventually rejected. SQL:2011 added something but it is pretty incomplete. I have been thinking I should put together a bibliography and a talk: temporal databases for web developers. A list curated by an expert would have saved me a lot of time!

I'm also (less professionally) interested in the overlap between the results from Turing and Godel. I would love a guide and/or annotations for Turing's "On Computable Numbers", because it is not easy going. Also a list of papers for quantum computing....

Such a thing exists. It's called "The Annotated Turing" by Charles Petzold (of "Programming Windows" fame). It's very good, although the machinery of setting up the Turing machine can be tedious.

Wow, purchased, thank you!

Code starts out tedious too but is worth it by the end. I guess for any technical subject you have to make sure you cover sufficient preliminaries to get all your readers up to speed.

Pretty sure sap has temporal query support? At least I remember reading a research paper from them about some temporal extensions they've implemented.

I attempted this at some point. It went pretty well until I stopped having time.

The first one was actually "On Computable Numbers" -> http://swizec.com/blog/week-1-turings-on-computable-numbers/...

It helps that I had 2 semesters in college on essentially "What did Godel and Turing create for us"

You will like The limits of mathematics by Gregory Chaitin.

An old review I did: http://shebang.ws/the-limits-of-mathematics.html

Thanks, I enjoyed your review! This article calls Ramanujan an "experimental" mathematician:

https://backchannel.com/who-was-ramanujan-83b4d5b05665

Also Prime Obsession by John Derbyshire kind of describes Riemann in similar terms: working via playful exploration and intuition. It seems like the complex zeros of his equation are a practical example of "is it random?" and truths that "just are for no reason."

Adrian Colyer does something similar with his blog which I highly recommend:

https://blog.acolyer.org/

Every weekday he posts a digestible summary of an influential paper, typically with a link to the paper itself.

+1 for this; Colyer's blog has been incredibly eye-opening.

Just reading the summaries is pretty interesting, but having a curated set of papers to dig into as time permits is fantastic as well.

This is a good idea, but how were those experts and "best papers" chosen? It's a well known fact that for each research domain, there are a few 'competing' labs. How can we be sure the experts aren't biased and decide to promote their papers to increase their visibility?

What would be cool is some sort of Hackernews style ranking per research domain, with voting ring detection, the only voters would be "recognized experts" (from academia or industry) with enough karma in their respective domain.

As it's just public engagement, I don't see that it's a critical problem that the papers are perfectly representative of the best work. It's not for tenure.

You could go crazy setting up some kind of voting system, or you could just get on with it and get some widely respected people to pick some papers, which is what they've done here.

We already have that, it's called citations...

Citations give a ranking of how often work is mentioned, but not how valuable the work is. For example " Ileal-lymphoid-nodular hyperplasia, non-specific colitis, and pervasive developmental disorder in children" , otherwise known as "Vaccines Cause Autism" has (according to google scholar) over 2000 citations, but is known to be wrong and based on bad science.

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