40 Matching Annotations
  1. Last 7 days
    1. The world is currently overflowing with hard problems, so it is overflowing with grift as well.

      The prevalence of hard problems opens up the door to individuals promoting action that masquerades as a solution, but does nothing to solve the problem – grifters and grifts.

    2. Grifts often rely on narrative vacuums. When the real story is too complicated or boring or requires numbers and graphs to understand, people reach for the simpler story. Grifters supply it.

      The law of triviality (the bicycle-shed effect) says that when something is too complicated, we focus on the parts we understand, irrespective of their importance to the whole.

      Grifters supply this simpler story.

    1. A remarkable phenomenon commented on in the Moynihan report of thirty years ago goes unnoticed in The Bell Curve--the prevalence of females among blacks who score high on mental tests. Others who have done studies of high- IQ blacks have found several times as many females as males above the 120 IQ level. Since black males and black females have the same genetic inheritance, this substantial disparity must have some other roots, especially since it is not found in studies of high-IQ individuals in the general society, such as the famous Terman studies, which followed high-IQ children into adulthood and later life. If IQ differences of this magnitude can occur with no genetic difference at all, then it is more than mere speculation to say that some unusual environmental effects must be at work among blacks. However, these environmental effects need not be limited to blacks, for other low-IQ groups of European or other ancestries have likewise tended to have females over-represented among their higher scorers, even though the Terman studies of the general population found no such patterns. One possibility is that females are more resistant to bad environmental conditions, as some other studies suggest. In any event, large sexual disparities in high-IQ individuals where there are no genetic or socioeconomic differences present a challenge to both the Herrnstein- Murray thesis and most of their critics.

      Other studies not cited by the Bell Curve found many times as many females among the highest IQ cohorts among lower IQ populations. This would refute the genetic explanation since genetics don't change from female to male. Instead it seems to point to environmental factors. One possible explanation being that women are more resistant to bad environmental conditions.

    2. Strangely, Herrnstein and Murray refer to "folklore" that "Jews and other immigrant groups were thought to be below average in intelligence. " It was neither folklore nor anything as subjective as thoughts. It was based on hard data, as hard as any data in The Bell Curve. These groups repeatedly tested below average on the mental tests of the World War I era, both in the army and in civilian life. For Jews, it is clear that later tests showed radically different results--during an era when there was very little intermarriage to change the genetic makeup of American Jews.

      Apparently jews scored lower than average on IQ tests administered in the WW I era.

  2. Jun 2020
    1. Anyway! Your only responsibility is to do stuff that’s actually in Japanese; the remainder of the responsibility rests entirely with the Japanese stuff — media — itself. The media has a responsibility to entertain you. You don’t have to find the value in it; it has to demonstrate its value to you by being so much fun that you don’t notice time going by — by sucking you in. It has to make you wish that eating and sleep and bodily hygiene could take care of themselves because they cut into your media time. And if it doesn’t do that or it stops doing that, then you “fire” it by changing to something else. You are the boss and there are no labor laws. Fire the mother. You do the work of setting up and showing up to the environment, but after that the environment must work for you.

      This strategy reminds me of Niklas Luhmann who allegedly said that he never did anything that he didn't feel like doing.

      This is like following your curiosity 100% and it goes against a lot of the other advice out there e.g. like sitting down every day and writing.

      This also reminds me of this idea of starting as many books as possible. Drop them when they're no longer interesting to you.

    2. DO NOT, DO NOT, DO NOT turn Japanese into work. Don’t turn it into “study”; don’t turn it into 勉強 (a word that refers to scholastic study in Japanese, but actually carries the rather negative meaning of “coercion” in Chinese). Just play at it. PLAY. That’s why I keep telling people: don’t make all these rules about what is and is not OK for you to do in Japanese, or how Gokusen is over-coloured by the argot of juvenile delinquents or watching Love Hina will make you talk like a girl — it doesn’t matter, you need to learn all that vocabulary in order to truly be proficient in Japanese anyway, so whatever you watch is fine — as long as you’re enjoying it right now. Write this on your liver: just because anything is OK to watch in Japanese, that doesn’t mean that everything is worth watching…to you that is. One person’s Star Trek is another person’s…well, I can’t imagine how any human being could fail to love Star Trek, but you get the idea.

      If you want to learn something, make sure that you keep it in the realm of play. If you make it work, you will kill it.

      This reminds me of Mark Sisson talking about incorporating play.

      This also reminds me of the concept of Flow.

    1. Most people think you build the product then you market it. Thinking in loops means you build the marketing into the product. The product doesn't precede the marketing. The product is the marketing.

      By thinking in loops Harry Dry refers to a way of thinking about your acquisition strategy as being part of your product.

      This reminds me of Brian Balfour's idea of product-channel fit and how stresses that the product gets shaped by its acquisition channel.

  3. May 2020
    1. The task of "making a thing satisfying our needs" as a single responsibility is split into two parts "stating the properties of a thing, by virtue of which it would satisfy our needs" and "making a thing guaranteed to have the stated properties". Business data processing systems are sufficiently complicated to require such a separation of concerns and the suggestion that in that part of the computing world "scientific thought is a non-applicable luxury" puts the cart before the horse: the mess they are in has been caused by too much unscientific thought.

      Dijkstra suggested that instead of concerning ourselves with a software system that meets the user's needs, we should first separate our concerns.

      We should first concern ourselves with the user's needs and draw up careful specifications – properties to which the system should adhere should it satisfy the user's needs.

      With those specifications in hand we can concern ourselves with making a system guaranteed to have stated properties.

      The problem with this thinking, which the software industry would later discover, is that a user's needs cannot be accurately or completely determined before building the system. We learn more about what is needed by the process of building.

      This is an instance of the [[Separation of concerns]] not working.

      This is also why the industry has settled on a technique to build iteratively (Agile), always leaving the option open to change course.

    2. Some time ago I visited the computing center of a large research laboratory where they were expecting new computing equipment of such a radically different architecture, that my colleagues had concluded that a new programming language was needed for it if the potential concurrency were to be exploited to any appreciable degree. But they got their language design never started because they felt that their product should be so much like FORTRAN that the casual user would hardly notice the difference "for otherwise our users won't accept it". They circumvented the problem of explaining to their user community how the new equipment could be used at best advantage by failing to discover what they should explain. It was a rather depressing visit.... The proper technique is clearly to postpone the concerns for general acceptance until you have reached a result of such a quality that it deserves acceptance. It is the significance of your message that should justify the care that you give to its presentation, it may be its "unusualness" that makes extra care necessary.

      When you've developed an idea, you will typically want to communicate that idea so that it can be understood and used more generally. Dijkstra calls this reaching "general acceptance".

      To do so, you must communicate the idea in a way so that it can be properly understood and used. For certain ideas this becomes a challenging problem in and of itself.

      Many forgo this challenge, and instead of figuring out what new language they need to invent to most accurately communicate the idea, they use legacy language and end up communicating their idea less effectively, in pursuit of general acceptance.

      Dijkstra says that the proper way of dealing with this dilemma is to separate your concerns. You separate your concern of the solution from the concern of communicating the solution.

      When you've reached a solution that is of such high quality that it deserves communicating – and only then – do you concern yourself with its presentation.

    1. When someone asks if you have time for a meeting next Tuesday, you may have nothing on your calendar, so you say “sure.” If you hadn’t agreed to the meeting, you would have done something with that time - but what? By getting clear on what the “what” was that I could be doing made me better at saying no. When you say yes that one hour phone call next week, you are saying no to revamping your sales page or going to the gym or getting home an hour earlier. There is not always a right or wrong answer, but if you realize what you are saying no to every time you say yes, then you can make a judgement call: “Is this phone call more important to me than going to the gym today?”

      By blocking in your calendar in advance you make future tradeoffs explicit. You are no longer saying yes to a meeting on Thursday. You are saying yes to swapping out your gym session for that meeting (or not).

    1. We have come to a place where thanks to many libraries and frameworks, and overall improving software, what would’ve once used many developers to build from scratch is now more often than not, a bunch of people plumbing different things together. Software is creating software faster than we can use it. This is also why you are seeing so many of these “no-code” or “low-code” solutions pop up all over the place. There are increasingly fewer reasons to write code, and those who are writing code should, and do, increasingly write less of it. This will only be more accelerated by shifting to remote work due to how it’s going to change how we decide what code to write.

      There are increasingly less reasons to write code, so less code should be written.

      How Can relates this to remote work is unclear to me here.

    2. Anyone who’s spent a few months at a sizable tech company can tell you that a lot of software seems to exist primarily because companies have hired people to write and maintain them. In some ways, the software serves not the business, but the people who have written it, and then those who need to maintain it. This is stupid, but also very, very true.

      A company with a software development team writing its own software often creates inertia for itself. They will be biased to write software, because they have that capability – not because it's necessary.

    3. In a world where most employees are remote, this can be harder to do. Not only employees could be in touch with each other less, and in less personal ways, they might not be even able to do so without having non-monitored places. There will always be ways to employees to sneak around monitoring and surveillance, but it’ll be harder when everything is fully remote, and you’ll have less trust in those who will bond (or conspire with, depending on your POV) with you.

      Can believes it will be harder for employees to coordinate collectively when the company goes remote-first (and this maybe part of the reason it is happening).

    4. The remote-first mentality will be a god-send simply because you’ll no longer be restricted to a tiny piece of land with a questionable housing policy to source your talent. People estimate 40% of all VC funding going to landlords in the Bay, and I think that’s too conservative.

      If you remove the requirement on an employee to be located near their employer, the following happens.

      Less upward pressure on housing prices (because employees aren't required to live near their employers).

      Downward pressure on salaries. Because employees don't need to live in the expensive locality of their employer and can live with less.

    5. Obviously, things can get quite weird when you take this model to its logical end. In the Bay Area, where the companies are giant, the geography tiny and the housing policies extremely questionable, this has resulted in salaries ballooning to insane levels. Getting a six-figure salary straight out of college barely raises an eyebrow anymore at many big firms. Companies have gone to great lengths, including some illegal ones to curb this competitive behavior to depress the salaries.

      Salaries become ridiculously high when:

      (1) The difference between value provided by the employee and value derived from the employer is high (a lot of latitude to increase) (2) There are many such employers able and willing to compete for an employee

      One consequence of this is that housing prices go up (because the employees can afford to pay more).

    6. Most people would like to believe salaries are determined by a cost-plus model, where you get a tiny bit less than the value you add to the company. However, in reality, they are really determined by the competition. Companies are forced to pay as much as possible to keep the talent for leaving. In a competitive labor market, this is often a good thing for the employees.

      The height of salaries is determined by competitive pressure. How much do you need to give an employee to make sure they stay?

    1. With limited or no access to technol-ogy, limited capacity to cope and adapt, limited or no savings, inadequate access to social services, and un-certainty about their legal status and potential to ac-cess healthcare services, tens of thousands of migrants and non-nationals have left Thailand over the past weeks.

      With little certainty and little to fall back on, many refugees have left Thailand in the last weeks.

    1. Insight through making suggests that you’ll need to make simultaneous progress in theory-space and system-space to spot the new implications in their conjoined space. Effective system design requires insights drawn from serious contexts of use: you must constantly instantiate new theoretical ideas in new systems, then observe their impact in some serious context of use.

      Very powerful way of wording the implications of Insights through making and the need for serious contexts of use.

      You need to advance in theory-space as well as in system-space to spot the implications for their conjoined space.

      Pragmatically, you must constantly instantiate new theoretical ideas in the system, then observe the effects in some serious context of use.

    1. Whether in music (Bach, Lennon), art (Picasso, Bernini), film (Tarantino, Anderson), games (Blow, Lantz), fiction (Kundera, Tolstoy), the most eminent work is usually the result of a single person’s creative efforts. Occasionally it’s a very small group (Eames, Wrights).

      Great creative work is usually the product of a single person.

    1. Per Michael: you probably would rather have Stradivarius make your violin than Joshua Bell, but you’d probably rather hear Joshua Bell play. Each activity—violin-making and violin-playing—requires virtuosic skill and a lifetime of practice. It’s very unlikely to find both abilities in the same person!

      Great tool-makers are often not great tool-users. You would want Stradivarius to make your violin, but not to play it. You want Joshua Bell to play it, but not to make it.

    1. One huge advantage to scaling up is that you’ll get far more feedback for your Insight through making process. It’s true that Effective system design requires insights drawn from serious contexts of use, but it’s possible to create small-scale serious contexts of use which will allow you to answer many core questions about your system.

      Even though a larger user base will increase your odds of getting more feedback, you can still get valuable contextual feedback with less users.

    2. WhyGeneral infrastructure simply takes time to build. You have to carefully design interfaces, write documentation and tests, and make sure that your systems will handle load. All of that is rival with experimentation, and not just because it takes time to build: it also makes the system much more rigid.Once you have lots of users with lots of use cases, it’s more difficult to change anything or to pursue radical experiments. You’ve got to make sure you don’t break things for people or else carefully communicate and manage change.Those same varied users simply consume a great deal of time day-to-day: a fault which occurs for 1% of people will present no real problem in a small prototype, but it’ll be high-priority when you have 100k users.Once this playbook becomes the primary goal, your incentives change: your goal will naturally become making the graphs go up, rather than answering fundamental questions about your system.

      The reason the conceptual architecture tends to freeze is because there is a tradeoff between a large user base and the ability to run radical experiments. If you've got a lot of users, there will always be a critical mass of complaints when the experiment blows up.

      Secondly, it takes a lot of time to scale up. This is time that you cannot spend experimenting.

      Andy here is basically advocating remaining in Explore mode a little bit longer than is usually recommended. Doing so will increase your chances of climbing the highest peak during the Exploit mode.

    3. This is obviously a powerful playbook, but it should be deployed with careful timing because it tends to freeze the conceptual architecture of the system.

      One a prototype gains some traction, conventional Silicon Valley wisdom says to scale it up. This, according to Andy Matuschak has certain disadvantages. The main drawback is that it tends to freeze the conceptual architecture of the system.

    1. Part of the problem of social media is that there is no equivalent to the scientific glassblowers’ sign, or the woodworker’s open door, or Dafna and Jesse’s sandwich boards. On the internet, if you stop speaking: you disappear. And, by corollary: on the internet, you only notice the people who are speaking nonstop.

      This quote comes from a larger piece by Robin Sloan. (I don't know who that is though)

      The problem with social media is that the equivalent to working with the garage door open (working in public) is repeatedly talking in public about what you're doing.

      One problem with this is that you need to choose what you want to talk about, and say it. This emphasizes whatever you select, not what would catch a passerby's eye.

      The other problem is that you become more visible by the more you talk. Conversely, when you stop talking, you become invisible.

    1. You should construct evergreen (permanent) notes based on concepts, not related to a source (e.g. a book) or an author.

      Your mental models are compression functions. You make them more powerful by trying to use them on new information. Are you able to compress the new information with an already acquired function? Yes, then you've discovered an analogous concept across two different sources. Sort of? Then maybe there's an important difference, or maybe it's a clue that your compression function needs updating. And finally, no? Then perhaps this is an indication that you need to construct a new mental model – a new compression function.

    1. If painting is an aesthetic medium of vision, music an aesthetic medium of sound, and cooking an aesthetic medium of taste, then games are an aesthetic medium of action, Frank Lantz observes.
    1. Annotations—even inline marginalia which include your own writing—have very little informational value. They’re atomized; they don’t relate to each other; they don’t add up to anything; they’re ultra-compressed; they’re largely unedited. That’s fine: think of them as just a reminder. They say “hey, look at this passage,” with a few words of context to jog your memory about what the passage was about.Since you’re going to write lasting notes anyway, annotations need carry just enough information to recreate your mental context in that moment of reading. You wouldn’t want to rely on that long-term, since then you’d just have a huge pile of hooks you’d have to “follow” anytime you wanted to think about your experience with that book.

      Classical marginalia in books, according to Andy Matuschok, have little informational value. They are not interlinked, they're very compressed and usually unedited. But that's okay.

      Their purpose is to help you get back to the mental context you were in when you thought the passage was worth returning to.

    1. Update 2020-01-14: I now store my outlines as Structure Zettel. For more information what a Structure Zettel is see this post.

      An important update to this piece as Sascha's method evolved. Instead of using outlines to capture new notes, he started using structured notes.

      I suspect the reason for this is that a system with atomic notes and structured notes is more clear cut than a system that relies on work-in-progress outlines. The main difference being that a structured note will contain only notes and not some floating, un-evolved ideas.

    1. Instead of having a task like “write an outline of the first chapter,” you have a task like “find notes which seem relevant.” Each step feels doable. This is an executable strategy (see Executable strategy).

      Whereas Dr. Sönke Ahrens in How to Make Smart Notes seemed to be saying that the writing of a permanent note (~evergreen note) is a unit of knowledge work with predictable effort & time investment (as well as searching for relevant notes), Andy emphasizes only the note searching activity in this context.

    1. In a classroom or professional setting, an expert might perform some of these tasks for a learner (Metacognitive supports as cognitive scaffolding), but when a learner’s on their own, these metacognitive activities may be taxing or beyond reach.

      In a classroom setting a teacher may perform many of the metacognitive tasks that are necessary for the student to learn. E.g. they may take over monitoring for confusion as well as testing the students to evaluate their understanding.

    2. To successfully learn something new, people must evaluate their understanding, monitor for confusion or inconsistency, plan what to do next based on those observations, and coordinate that plan’s execution. This often falls under the category of “metacognition,” though prefer to unbundle its phenomena.

      To learn something people need to use certain faculties that are often referred to as metacognition.

      They need to evaluate their understanding, monitor for confusion or inconsistency, plan what to do next and coordinate that plan's execution.

    1. Ericsson claims (2016, p. 98) that there is no deliberate practice possible for knowledge work because there are no objective criteria (so, poor feedback), because the skills aren’t clearly defined, and because techniques for focused skill improvement in these domains aren’t known.

      According to Ericsson deliberate practice for knowledge work is not possible because the criteria are not objective (you don't know if you're doing well).

      This collides with Dr. Sönke Ahrens' contention that note taking, specifically elaboration, instantiates two feedback loop. One feedback loop in that you can see whether you're capturing the essence of what you're trying to make a note on and a second feedback loop in that you can see whether your note is not only an accurate description of the original idea, but also a complete one.

      Put differently, note taking instantiates two feedback loops. One for precision and one for recall.

    1. One common choice is to set daily goals for a certain number of hours at work. Success with this strategy requires a clear theory of how those hours will inexorably accumulate to the desired outcome. Simply spending some number of hours on a project is a fairly weak constraint: it’s easy to work with focus many hours unproductively.

      I've run into this problem.

      You can spend time in flow state, very focused, but this time still doesn't bring you closer to your goal.

    1. Incremental writing is a method of writing in which ideas are written down and assembled incrementally. Incremental writing requires no linearity. It adapts to your way of thinking. Many great writers and scientists of the past used a variant of incremental writing using their own systems of notes. In SuperMemo, incremental writing is integral with the creative process and learning itself

      Incremental writing is a method of writing where you keep adding elements to a piece in a "creative phase". In this phase the manuscript progressively increases in size. This is followed by a "consolidation phase", a process in which the manuscript gets to the point and decreases in size.

    1. By contrast, when we’re working on a large work-in-progress manuscript, we’re juggling many ideas in various states of completion. Different parts of the document are at different levels of fidelity. The document is large enough that it’s easy to lose one’s place or to forget where other relevant points are when one returns. Starting and stopping work for the day feel like heavy tasks, drawing heavily on working memory.

      One key difference between working with atomic, evergreen notes compared to a draft manuscript is that the ideas in the manuscript are at different levels of evolution / fidelity. The ideas in the evergreen notes are all evolved components.

    1. Instead, nurture the wild idea and let it develop over time by incrementally writing Evergreen notes about small facets of the idea.

      If you cannot tackle a subject head on, tackle it obliquely by writing evergreen notes about facets of the idea.

      This is an interesting way of reducing the scope of, say, an essay, without sacrificing quality. Instead of writing the whole thing, just write an atomic piece about one of the concepts you need for the larger piece.

    1. The issue of the different layers is similar. If you chose software that doesn’t deal with those layers in a sophisticated way, you will not reap the benefits in the long term. Your archive will note work as a whole. I think that this is one of the reasons why many retreat to project-centered solutions, curating one set of notes for each book, for example. The problems that come with big and organic (= dynamic and living) systems is avoided. But so is the opportunity to create something that is greater than you.

      Interesting point where the author compares the barrier that is created between the editing and the writing mode in a wiki (which makes it more cumbersome to continue lines of thought) to the barriers that appear when you're not using the right software or conventions to structure your knowledge items, as well as to structure your knowledge items' structure.

    2. After a while, I did not only have structure notes that structure content notes, I also had structure notes that mainly structured sets of structure notes. They became my top level structure notes because they began to float on the top of my archive, so to say.

      After the need for a layer of Hub Notes a new need may emerge: to better organize the Hub Notes themselves. At this point you may want to introduce structure notes that structure sets of structured notes.

    3. Structure notes share a similarity to tags: Both point to sets of notes. Structure notes just add another element. They are sets with added structure. This added structure provides a better overview and adds to the utility of the archive.

      Structure notes or Hub Notes are similar to tags (or pages in Roam) in that they point to a collection of other notes (or pages in Roam). The only difference being that structure notes contain within themselves a structure which provides hierarchy and context.

    4. But after a while, you won’t be able to keep up. When I search for tags I get a couple hundred of notes. I have to review them to connect a note to some of them, or get a grasp of what I wrote and thought about a specific topic. Naturally, a need to organize the archive arises at this point. I can’t remember how many notes I had when I experienced this. I introduced hub-like notes when I had between 500 and 700 notes.1 I gave myself an overview of the most important notes on that topic.

      There seems to be an inflection point where your initial approach to organizing your Zettelkasten starts to fail (perhaps 500-700 notes). You'll simply have too many tags to choose from.

      At this point hub-like notes will be the next stage in the evolution of your Zettelkasten organization.