A poor man’s instapaper

I’ve stopped using Instapaper for a long time now, but I’m still reading longreads. Let me explain how.

I go through my links in Chrome on my desktop. I close and read whatever I can and anything that’s too long stays in an open tab and floats slowly to the left.

On Chrome on my phone whenever I’m in transit or when I want to read something longer that isn’t a book, I go to the “Recent tabs” screen. Besides those you can also find synced open tabs from all your other Chrome browsers. I then pick something that I want to read.

Now, ideally it would allow me to close the tab on my desktop from my phone but understandably that’s not a feature. So I read a couple of articles, remember those and close the tabs manually next time I’m back on my desktop.

This works surprisingly well. Except for LRB articles. I have no clue what to do about those.

Highlights for Designing Data-Intensive Applications

Amazon RedShift is a hosted version of ParAccel. More recently, a plethora of open source SQL-on-Hadoop projects have emerged; they are young but aiming to compete with commercial data warehouse systems. These include Apache Hive, Spark SQL, Cloudera Impala, Facebook Presto, Apache Tajo, and Apache Drill [52, 53].
In these situations, as long as people agree on what the format is, it often doesn’t matter how pretty or efficient the format is. The difficulty of getting different organizations to agree on anything outweighs most other concerns.
Therefore, to maintain backward compatibility, every field you add after the initial deployment of the schema must be optional or have a default value.
That means you can only remove a field that is optional (a required field can never be removed), and you can never use the same tag number again (because you may still have data written somewhere that includes the old tag number, and that field must be ignored by new code).
If you are using a system with multi-leader replication, it is worth being aware of these issues, carefully reading the documentation, and thoroughly testing your database to ensure that it really does provide the guarantees you believe it to have.
Today, most data systems are not able to automatically compensate for such a highly skewed workload, so it’s the responsibility of the application to reduce the skew.
Unfortunately, these tools don’t directly translate to distributed systems, because a distributed system has no shared memory—only messages sent over an unreliable network.
Safety is often informally defined as nothing bad happens, and liveness as something good eventually happens.
A much better solution is to build a brand-new database inside the batch job and write it as files to the job’s output directory in the distributed filesystem, just like the search indexes in the last section. Those data files are then immutable once written, and can be loaded in bulk into servers that handle read-only queries. Various key-value stores support building database files in MapReduce jobs, including Voldemort [46], Terrapin [47], ElephantDB [48], and HBase bulk loading [49].
A complex system that works is invariably found to have evolved from a simple system that works. The inverse proposition also appears to be true: A complex system designed from scratch never works and cannot be made to work. John Gall, Systemantics (1975)
When copies of the same data need to be maintained in several storage systems in order to satisfy different access patterns, you need to be very clear about the inputs and outputs: where is data written first, and which representations are derived from which sources? How do you get data into all the right places, in the right formats?
It would be very natural to extend this programming model to also allow a server to push state-change events into this client-side event pipeline. Thus, state changes could flow through an end-to-end write path: from the interaction on one device that triggers a state change, via event logs and through several derived data systems and stream processors, all the way to the user interface of a person observing the state on another device.
But this choice is not free either: if a service is so popular that it is “regarded by most people as essential for basic social participation” [99], then it is not reasonable to expect people to opt out of this service—using it is de facto mandatory.

The Theory of Society

I was arguing against Systems Theory today (a necessary evil when you live in Germany) which prompted the thought of searching for the conjunction of Bruno Latour and Niklas Luhmann. That led me to this gem.

It turns out that they met each other for a debate in 1996 in Bielefeld and Latour DESTROYED his opponent (full article).

Luhmann, as expected, failed to engage with the theme of the conference, Science and Technology Studies and didn’t come out of his bubble. The same bubble that he has managed to trap most of the German humanities in.

[Luhmann] only managed to address the theme of the conference—science and its sociological study—with half a sentence where he curtly asserted that science is an autopoietic subsystem of modern society.

An autopoietic subsystem, my ass. Latour quickly riposted into a frontal assault at the entirety of Luhmann-ism.

No, according to Latour, this theory didn’t have anything to offer to him and neither he concluded any of those gathered there. A quick perusal of the conference program should have sufficed to ascertain that the empirically obsessed STSers could not recover their objects in this theory. This may be bemoaned from the high vantage point of the Theory of Society as poor, theoretically “flat” sociology, nonetheless, Latour replied, this empirical Zoology of STS gives an account of this society as it is and not how it may appear from the distance of the chilling heights of systems theory.
Latour clarified that fundamentally, systems theory represents everything that he and his colleagues in science studies have been battling for 20 years—yes, really battle and not just criticize. The purification of science, the simplification of the social by a demarcation with its environment, Luhmann’s work as the embodiment of the “cognitive turn” in epistemology—for Latour these were the old buzzwords that had to miss what’s special about science: its materiality. And in doing so of course also what’s specific for modern society, the large technological networks.

Latour battling ‘the purification of science [and] the simplification of the social’, a true hero of science and society.

Highlights for Interpreter of Maladies

In her estimation, I knew, I was assured a safe life, an easy life, a fine education, every opportunity. I would never have to eat rationed food, or obey curfews, or watch riots from my rooftop, or hide neighbors in water tanks to prevent them from being shot, as she and my father had.
In my son’s eyes I see the ambition that had first hurled me across the world. In a few years he will graduate and pave his way, alone and unprotected. But I remind myself that he has a father who is still living, a mother who is happy and strong. Whenever he is discouraged I tell him that if I can survive on three continents than there is no obstacle he cannot conquer.

Highlights for How to Measure Anything in Cybersecurity Risk

What risks are acceptable is often not documented, and when they are, they are stated in soft, unquantified terms that cannot be used clearly in a calculation to determine if a given expenditure is justified or not.
Measurement: A quantitatively expressed reduction of uncertainty based on one or more observations.
If a decision maker or analyst engages in what they believe to be measurement activities, but their estimates and decisions actually get worse or don’t at least improve, then they are not actually reducing their error and are not conducting a measurement according to the stated definition.
What you want to know is whether you have less uncertainty after considering some source of data and whether that reduction in uncertainty warrants some change in actions.
We can measure the value of art, free time, or reducing risk to your life by assessing how much people actually pay for these things.
If your concern is that upper management won’t understand this, we can say we have not observed this—even when we’ve been told that management wouldn’t understand it. In fact, upper management seems to understand having to determine which risks are acceptable at least as well as anyone in cybersecurity.
Since we know at least one (if not both) must be wrong, then we know qualifications and expertise in cybersecurity alone are not sufficient to determine if a given opinion on this topic is correct.
More fundamentally, does it even matter whether risk analysis works? And by “works,” do we really just mean whether it succeeds in putting on a show for compliance, or should we mean it actually improves the identification and management of risks?
They are all based in part on the idea that not knowing exact quantities is the same as knowing nothing of any value.
All of the operations just described require some source of an input. In this example, we will be using the calibrated estimates of the CISO. Since the CISO is using his previous experience and his calibrated probability-assessment skill to generate the inputs, we call them an “informative prior.”
Practically speaking, there are only so many models that can be run and maintained at any given time.

A lot of very salient thinking on books, metacognition, double-loop learning and the deliberate design of new forms by Andy Matuschak in “Why Books Don’t Work”.

I acknowledged earlier that of course, some people do absorb knowledge from books. Indeed, those are the people who really do think about what they’re reading. The process is often invisible. These readers’ inner monologues have sounds like: “This idea reminds me of…,” “This point conflicts with…,” “I don’t really understand how…,” etc. If they take some notes, they’re not simply transcribing the author’s words: they’re summarizing, synthesizing, analyzing.

I’ve been thinking of doing a talk about how to get the most out of your reading both quantitatively and qualitatively. Many people do not even know how much is possible, let alone that they would have an inkling of how to get there. I think anybody can easily get to at least a doubling of reading quantity and conceptual retention.

Readers must decide which exercises to do and when. Readers must run their own feedback loops: did they clearly understand the ideas involved in the exercise? If not, what should they do next? What should students do if they’re completely stuck? Some issues are subtler. For example, textbook exercises are often designed to yield both a solution to that specific problem and also broader insights about the subject. Will readers notice if they solved a problem but missed the insights it was supposed to reveal?

Work in new aesthetic and educational forms along with opening up systems to allow people to make their own rules for going through them, is all of the stuff we had been occupied with in Hubbub as well.

Americans feel ripped off by the Corres’s bait and switch and it seems now we’re going to seeing a free for all where they will mercilessly rip the site.

It was disappointing to realize — to actually see in the numbers — that while The Correspondent raised $2.6 million in part by stressing diversity and inclusivity, tapping ambassadors like DeRay Mckesson and Baratunde Thurston, the Dutch site is not a model of that diversity.

There is a lot of criticism and hate in the Netherlands as well but it’s not so pronounced because:

  1. The site has its provenance in the Netherlands.
  2. It’s a small country and you never know who you’ll need again in the future (“the media in The Netherlands is more tight-knit, insular, and male than it is in the U.S.”).

The USA is not bothered by either of those and that creates a more honest environment because frankly a lot of the criticism is valid.