Econstudentlog

Californium (Periodic Videos)

May 11, 2022 Posted by | Chemistry, Physics | Leave a comment

Code Complete (I)

Here’s what I wrote about the book elsewhere not long ago: “I recently started reading the book Code Complete by Steve McConnell. I’ve only read the first 100 pages so far (Kindle estimate of time remaining: 27 hours… – then again, it is ‎960 pages..) but I can already confidently say at this point that if you’re a software developer or programmer or similar, or plan to be, then you’ll want to read this book – it’s awesome. (…and even just reading the first 50 pages of this book would probably make you a better programmer, even if you read no more than that…)”

I enjoy reading it and I learn something new on many of the pages here, or perhaps get a new angle on a topic I have familiarity with – I’ve already come across multiple important insights that I’d really wish I’d have known about when involved in projects in the past, and I’m trying to share some of these learnings also with my coworkers. It’s just a good book. The fact that it’s already almost 20 years old of course means that there isn’t a great deal of coverage about, say, the topics touched upon in the lecture below this post, but a lot of this stuff is about fundamentals, concepts, and tradeoffs, which means that this aspect actually matters probably significantly less than you’d think. Not all suggestions made are the sort of suggestions I feel tempted to immediately follow/implement in my daily work, but most of them at the very least makes you think a bit more about the choices you might be making, often subconsciously – and as the quotes below should incidentally serve to illustrate it’s not just a book about coding.

I have added some sample quotes from the chapters I’ve read so far below.

“Construction is a large part of software development. Depending on the size of the project, construction typically takes 30 to 80 percent of the total time spent on a project. […] Construction is the central activity in software development. Requirements and architecture are done before construction so that you can do construction effectively. System testing (in the strict sense of independent testing) is done after construction to verify that construction has been done correctly. […] With a focus on construction, the individual programmer’s productivity can improve enormously. A classic study by Sackman, Erikson, and Grant showed that the productivity of individual programmers varied by a factor of 10 to 20 during construction (1968). Since their study, their results have been confirmed by numerous other studies (Curtis 1981, Mills 1983, Curtis et al. 1986, Card 1987, Valett and McGarry 1989, DeMarco and Lister 1999, Boehm et al. 2000). This book helps all programmers learn techniques that are already used by the best programmers.”

“As much as 90 percent of the development effort on a typical software system comes after its initial release, with two-thirds being typical (Pigoski, 1997).”
“It generally doesn’t make sense to code things you can buy ready-made.”
“Choosing the right tool for each problem is one key to being an effective programmer.”
“Good architecture makes construction easy. Bad architecture makes construction almost impossible.”
“Good software architecture is largely machine- and language-independent.”
“Part of a programmer’s job is to educate bosses and coworkers about the software-development process, including the importance of adequate preparation before programming begins.”

“Both building construction and software construction benefit from appropriate levels of planning. If you build software in the wrong order, it’s hard to code, hard to test, and hard to debug. It can take longer to complete, or the project can fall apart because everyone’s work is too complex and therefore too confusing when it’s all combined. Careful planning doesn’t necessarily mean exhaustive planning or over-planning. You can plan out the structural supports and decide later whether to put in hardwood floors or carpeting, what color to paint the walls, what roofing material to use, and so on. A well-planned project improves your ability to change your mind later about details. The more experience you have with the kind of software you’re building, the more details you can take for granted. You just want to be sure that you plan enough so that lack of planning doesn’t create major problems later.”

“The overarching goal of preparation is risk reduction: a good project planner clears major risks out of the way as early as possible so that the bulk of the project can proceed as smoothly as possible. By far the most common project risks in software development are poor requirements and poor project planning […] You might think that all professional programmers know about the importance of preparation and check that the prerequisites have been satisfied before jumping into construction. Unfortunately, that isn’t so. A common cause of incomplete preparation is that the developers who are assigned to work on the upstream activities do not have the expertise to carry out their assignments. The skills needed to plan a project, create a compelling business case, develop comprehensive and accurate requirements, and create high-quality architectures are far from trivial, but most developers have not received training in how to perform these activities. […] Some programmers do know how to perform upstream activities, but they don’t prepare because they can’t resist the urge to begin coding as soon as possible. […] It takes only a few large programs to learn that you can avoid a lot of stress by planning ahead. Let your own experience be your guide. A final reason that programmers don’t prepare is that managers are notoriously unsympathetic to programmers who spend time on construction prerequisites.”

“One of the key ideas in effective programming is that preparation is important. It makes sense that before you start working on a big project, you should plan the project. Big projects require more planning; small projects require less. […] Researchers at Hewlett-Packard, IBM, Hughes Aircraft, TRW, and other organizations have found that purging an error by the beginning of construction allows rework to be done 10 to 100 times less expensively than when it’s done in the last part of the process, during system test or after release […]. In general, the principle is to find an error as close as possible to the time at which it was introduced. The longer the defect stays in the software food chain, the more damage it causes further down the chain. Since requirements are done first, requirements defects have the potential to be in the system longer and to be more expensive. Defects inserted into the software upstream also tend to have broader effects than those inserted further downstream. That also makes early defects more expensive. […] for example, an architecture defect that costs $1000 to fix when the architecture is being created can cost $15,000 to fix during system test. […] The cost to fix a defect rises dramatically as the time from when it’s introduced to when it’s detected increases. This remains true whether the project is highly sequential (doing 100 percent of requirements and design up front) or highly iterative (doing 5 percent of requirements and design up front). […] Dozens of companies have found that simply focusing on correcting defects earlier rather than later in a project can cut development costs and schedules by factors of two or more […]. This is a healthy incentive to find and fix your problems as early as you can.”

“Accommodating changes is one of the most challenging aspects of good program design. The goal is to isolate unstable areas so that the effect of a change will be limited to one routine, class, or package. […] Business rules tend to be the source of frequent software changes. […] Business systems projects tend to benefit from highly iterative approaches, in which planning, requirements, and architecture are interleaved with construction, system testing, and quality-assurance activities. […] Iterative approaches tend to reduce the impact of inadequate upstream work, but they don’t eliminate it. […] Iterative approaches are usually a better option for many reasons, but an iterative approach that ignores prerequisites can end up costing significantly more than a sequential project that pays close attention to prerequisites. […] One common rule of thumb is to plan to specify about 80 percent of the requirements up front, allocate time for additional requirements to be specified later, and then practice systematic change control to accept only the most valuable new requirements as the project progresses. Another alternative is to specify only the most important 20 percent of the requirements up front and plan to develop the rest of the software in small increments, specifying additional requirements and designs as you go. […] One key to successful construction is understanding the degree to which prerequisites have been completed and adjusting your approach accordingly […] The extent to which prerequisites need to be satisfied up front will vary with the project type […], project formality, technical environment, staff capabilities, and project business goals. […] Software being what it is, iterative approaches are useful much more often than sequential approaches are. […] Some projects do too much up front; they doggedly adhere to requirements and plans that have been invalidated by down-stream discoveries, and that can also impede progress during construction.”

“[D]ata from numerous organizations indicates that on large projects an error in requirements detected during the architecture stage is typically 3 times as expensive to correct as it would be if it were detected during the requirements stage. If detected during coding, it’s 5–10 times as expensive; during system test, 10 times; and post-release, a whopping 10–100 times as expensive as it would be if it were detected during requirements development. On smaller projects with lower administrative costs, the multiplier post-release is closer to 5–10 than 100 (Boehm and Turner 2004). […] Specifying requirements adequately is a key to project success, perhaps even more important than effective construction techniques. […] Stable requirements are the holy grail of software development. With stable requirements, a project can proceed from architecture to design to coding to testing in a way that’s orderly, predictable, and calm. […] It’s fine to hope that once your customer has accepted a requirements document, no changes will be needed. On a typical project, however, the customer can’t reliably describe what is needed before the code is written. The problem isn’t that the customers are a lower life form. Just as the more you work with the project, the better you understand it, the more they work with it, the better they understand it. The development process helps customers better understand their own needs, and this is a major source of requirements changes […]. A plan to follow the requirements rigidly is actually a plan not to respond to your customer. How much change is typical? Studies at IBM and other companies have found that the average project experiences about a 25 percent change in requirements during development […], which accounts for 70 to 85 percent of the rework on a typical project […] Make sure everyone knows the cost of requirements changes. […] say, “Gee, that sounds like a great idea. Since it’s not in the requirements document, I’ll work up a revised schedule and cost estimate so that you can decide whether you want to do it now or later.” The words “schedule” and “cost” are more sobering than coffee and a cold shower […] Set up a change-control procedure. […] Having a built-in procedure for controlling changes makes everyone happy. You’re happy because you know that you’ll have to work with changes only at specific times. Your customers are happy because they know that you have a plan for handling their input.””Use development approaches that accommodate changes. Some development approaches maximize your ability to respond to changing requirements. An evolutionary prototyping approach helps you explore a system’s requirements before you send your forces in to build it. Evolutionary delivery is an approach that delivers the system in stages. You can build a little, get a little feedback from your users, adjust your design a little, make a few changes, and build a little more. The key is using short development cycles so that you can respond to your users quickly. […] Keep your eye on the business case for the project. Many requirements issues disappear before your eyes when you refer back to the business reason for doing the project. Requirements that seemed like good ideas when considered as “features” can seem like terrible ideas when you evaluate the “incremental business value.””

“The amount of time to spend on problem definition, requirements, and software architecture varies according to the needs of your project. Generally, a well-run project devotes about 10 to 20 percent of its effort and about 20 to 30 percent of its schedule to requirements, architecture, and up-front planning […]. These figures don’t include time for detailed design—that’s part of construction. […] If requirements are unstable and you’re working on a small, informal project, you’ll probably need to resolve requirements issues yourself. Allow time for defining the requirements well enough that their volatility will have a minimal impact on construction. If the requirements are unstable on any project — formal or informal — treat requirements work as its own project. Estimate the time for the rest of the project after you’ve finished the requirements. This is a sensible approach since no one can reasonably expect you to estimate your schedule before you know what you’re building. It’s as if you were a contractor called to work on a house. Your customer says, “What will it cost to do the work?” You reasonably ask, “What do you want me to do?” Your customer says, “I can’t tell you, but how much will it cost?” You reasonably thank the customer for wasting your time and go home.”

“When software-project surveys report causes of project failure, they rarely identify technical reasons as the primary causes of project failure. Projects fail most often because of poor requirements, poor planning, or poor management. But when projects do fail for reasons that are primarily technical, the reason is often uncontrolled complexity. The software is allowed to grow so complex that no one really knows what it does. When a project reaches the point at which no one completely understands the impact that code changes in one area will have on other areas, progress grinds to a halt. […] Managing complexity is the most important technical topic in software development. In my view, it’s so important that Software’s Primary Technical Imperative has to be managing complexity. […] The goal is to minimize the amount of a program you have to think about at any one time. […] The goal of all software-design techniques is to break a complicated problem into simple pieces. The more independent the subsystems are, the more you make it safe to focus on one bit of complexity at a time. Carefully defined objects separate concerns so that you can focus on one thing at a time. Packages provide the same benefit at a higher level of aggregation. Keeping routines short helps reduce your mental workload. Writing programs in terms of the problem domain, rather than in terms of low-level implementation details, and working at the highest level of abstraction reduce the load on your brain. The bottom line is that programmers who compensate for inherent human limitations write code that’s easier for themselves and others to understand and that has fewer errors. […] Once you understand that all other technical goals in software are secondary to managing complexity, many design considerations become straightforward.”

November 23, 2021 Posted by | Books, Computer science | Leave a comment

Best practices for CI/CD using AWS Fargate and Amazon ECS

September 29, 2021 Posted by | AWS | Leave a comment

Imitation Games – Avi Wigderson

If you wish to skip the introduction the talk starts at 5.20. The talk itself lasts roughly an hour, with the last ca. 20 minutes devoted to Q&A – that part is worth watching as well.

Some links related to the talk below:

Theory of computation.
Turing test.
COMPUTING MACHINERY AND INTELLIGENCE.
Probabilistic encryption & how to play mental poker keeping secret all partial information Goldwasser-Micali82.
Probabilistic algorithm
How To Generate Cryptographically Strong Sequences Of Pseudo-Random Bits (Blum&Micali, 1984)
Randomness extractor
Dense graph
Periodic sequence
Extremal graph theory
Szemerédi’s theorem
Green–Tao theorem
Szemerédi regularity lemma
New Proofs of the Green-Tao-Ziegler Dense Model Theorem: An Exposition
Calibrating Noise to Sensitivity in Private Data Analysis
Generalization in Adaptive Data Analysis and Holdout Reuse
Book: Math and Computation | Avi Wigderson
One-way function
Lattice-based cryptography

August 23, 2021 Posted by | Computer science, Cryptography, Data, Lectures, Mathematics, Science, Statistics | Leave a comment

Books 2021

Last year I failed to track my reading throughout the year on goodreads, but this year I managed reasonably well – here’s an auto-generated list with cover images from goodreads.

If I had to pick out any of the books on the list as ‘must-reads’, it’d be #4 and the last two books included, in combination with the first book I read in 2022. The last part of the list looks full of fiction books and zero non-fiction but this is not a true picture of my reading patterns in November and December; Code Complete probably represents 50 hours of work alone. Worth every second: Read it!

1. Thinking in Systems: A Primer (2, nf. Chelsea Green Publishing). Goodreads review here.

2. Open Access (3, nf. MIT Press)

3. The Parasitic Mind: How Infectious Ideas Are Killing Common Sense (nf., Regnery Publishing).

4. Algorithms To Live By: The Computer Science of Human Decisions (5, nf. William Collins). Blog coverage here. I added this book to my list of favorite books on goodreads.

5. How to Have Impossible Conversations: A Very Practical Guide (nf., Da Capo Lifelong Books). Goodreads review here.

6. Spaceflight: A Concise History (3, nf. MIT Press)

7. Information and the Modern Corporation (2, nf. MIT Press)

8. Difficult Conversations: How to Discuss What Matters Most (5, nf. Penguin Books). I added this book to my list of favorite books on goodreads.

9. Understanding Beliefs (2, nf. MIT Press)

10. The Holy Roman Empire: A Very Short Introduction (3, nf. Oxford University Press)

11. The Habsburg Empire: A Very Short Introduction (2, nf. Oxford University Press)

12. Night Watch (5, f. Terry Pratchett). This book is on my list of favorite books on goodreads for a reason. A wonderful book, in my opinion perhaps the best book Terry Pratchett ever wrote.

13. Interesting Times (4, f. Terry Pratchett).

14. Moving Pictures (3, f. Terry Pratchett).

15. Against the Grain: A Deep History of the Earliest States (5, nf. Yale University Press). I added this book to my list of favorite books on goodreads.

16. Machine Translation (3, nf. MIT University Press).

17. Clinical Psychology: A Very Short Introduction (1, nf. Oxford University Press). Goodreads review here.

18. Handbook on the Neuropsychology of Aging and Dementia (5, nf. Springer). Short goodreads review here. I added this book to my list of favorite books on goodreads).

19. Human Anatomy: A Very Short Introduction (3, nf. Oxford University Press)

20. Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed (3, nf. Yale University Press). Quotes from the book are included in this blog-post.

21. Ancient Warfare (2, nf. Oxford University Press)

22. Not Born Yesterday: The Science of Who We Trust and What We Believe (3, nf. Princeton University Press)

23. Exit, voice, and loyalty (4, nf.). Quotes from the book are included in this blog-post.

24. The Napoleonic Wars: A Very Short Introduction (2, nf. Oxford University Press).

25. Decision Making under Deep Uncertainty: From Theory to Practice (3, nf. Springer).

26. Private Truths, Public Lies: The Social Consequences of Preference Falsification (5, nf. Harvard University Press). Goodreads review here. I added this book to my list of favorite books on goodreads. Some quotes from the book are included in this blog-post.

27. Data Pipelines Pocket Reference: Moving and Processing Data for Analytics (3, nf. O’Reilly Media).

28. The Adventures of Sally (4, f). P. G. Wodehouse.

29. The Inimitable Jeeves (4, f). P. G. Wodehouse.

30. Blandings Castle …and Elsewhere (5, f). P. G. Wodehouse.

31. Summer Lightning (5, f). P. G. Wodehouse.

32. Thank You, Jeeves (5, f). P. G. Wodehouse.

33. The Code of the Woosters (4, f). P. G. Wodehouse.

34. Right Ho, Jeeves (5, f). P. G. Wodehouse.

35. A Damsel in Distress (3, f). P. G. Wodehouse.

36. Carry On, Jeeves (5, f). P. G. Wodehouse.

37. Very Good, Jeeves! (4, f). P. G. Wodehouse.

38. Hot Water (5, f). P. G. Wodehouse.

39. Volcanoes: A Very Short Introduction (3, nf. Oxford University Press).

40. Jeeves in the Offing (4, f). P. G. Wodehouse.

41. Jeeves and the Feudal Spirit (4, f). P. G. Wodehouse.

42. Leave It to Psmith (5, f). P. G. Wodehouse.

43. Psmith in the City (3, f). P. G. Wodehouse.

44. Psmith, Journalist (3, f). P. G. Wodehouse.

45. Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines (nf. O’Reilly Media). Long, code-heavy, not an easy read. Very short goodreads review here.

46. Plague: A Very Short Introduction (2, nf. Oxford University Press). Very short goodreads review here.

47. Lord Edgeware Dies (5, f). Agatha Christie.

48. Enzymes: A Very Short Introduction (5, nf. Oxford University Press). Short goodreads review here.

49. After the Funeral (4, f). Agatha Christie.

50. Soft Matter: A Very Short Introduction (3, nf. Oxford University Press).

51. Poirot Investigates (f). Agatha Christie. A mixed bag.

52. Systems Biology: A Very Short Introduction (3, nf. Oxford University Press).

53. Biogeography: A Very Short Introduction (3, nf. Oxford University Press).

54. Why Didn’t They Ask Evans? (2, f). Agatha Christie.

55. Forests: A Very Short Introduction (2, nf. Oxford University Press).

56. Cat Among the Pigeons (2, f). Agatha Christie. Old goodreads review here, written after I first read this book – after finishing the book this year I downgraded the goodreads rating from 3 stars to 2.

57. One, Two, Buckle My Shoe (4,f). Agatha Christie.

58. The A.B.C. Murders (f). Agatha Christie.

59. Death in the Clouds (4, f). Agatha Christie.

60. Assessment and Treatment of Older Adults: A Guide for Mental Health Professionals (2, nf. American Psychological Association).

61. Evil Under the Sun (4, f). Agatha Christie.

62. Cards on the Table (5, f). Agatha Christie.

63. Synthetic biology (3, nf.) Oxford University Press.

64. Five Little Pigs (4, f). Agatha Christie.

65. Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness (3, nf. O’Reilly Media). Work-related.

66. Endless Night (3, f). Agatha Christie. Goodreads review here.

67. Peril at End House (4, f). Agatha Christie.

68. 4:50 from Paddington (3, f). Agatha Christie.

69. Murder in the Mews: Four Cases of Hercule Poirot (2, f). Agatha Christie.

70. At Bertram’s Hotel (3, f). Agatha Christie.

71. The Body in the Library (3, f). Agatha Christie.

72. Murder at the Vicarage (2, f). Agatha Christie.

73. The Moving Finger (2, f). Agatha Christie.

74. Sad Cypress (4, f). Agatha Christie.

75. The Thirteen Problems (2, f). Agatha Christie. I stand by the very short review I wrote in 2016.

76. The Hollow (4, f). Agatha Christie.

77. PLC Programming (2, nf). Nathan Clarke.

78. The Clocks (3, f). Agatha Christie.

79. Murder on the Orient Express (5, f). Agatha Christie.

80. Murder in Mesopotamia (4, f).

81. Dumb Witness (4, f). Agatha Christie. Very short goodreads review here.

82. Taken at the Flood (4, f). Agatha Christie.

83. Appointment with Death (3, f). Agatha Christie.

84. Hercule Poirot’s Christmas (5, f). Agatha Christie.

85. Death on the Nile (4, f). Agatha Christie. Updated (short) goodreads review here.

86. A Murder is Announced (2, f). Agatha Christie.

87. Black Coffee (2, f). Agatha Christie.

88. A Pocket Full of Rye (4, f). Agatha Christie.

89. The Mysterious Affair At Styles (3, f). Agatha Christie.

90. Blackout (5, f). Connie Willis. When I first read this book I gave it 5 stars but did not add it to my list of favorite books on goodreads. This was a grave mistake. This year I added the book to the list and wrote a new goodreads review, which included this observation: “my current assessment of the book is simply this: This book is one of the best books I’ve ever read.” I repeated this statement in my review of All Clear when I finished the latter book early in 2022. You need to read these books before you die.

91. Code Complete 2 (nf. 5, Microsoft Press). This book is the sole reason why I only read one non-fiction book in the last 6 weeks of 2021, and why there are so many fiction books in a row on this list towards the end of the year – it’s a 960 page book on coding/programming. It’s looong, it takes a lot of work to finish this book. But it’s so worth it – the book is by far the best book I’ve ever read on these topics. I added the book to my list of favorite books on goodreads and would strongly recommend the book to anyone who’s even thinking of working in the fields of programming/coding/software development/… Blog coverage here.

June 26, 2021 Posted by | Books, Personal | Leave a comment

Quotes

  1. “Originally, I set out to understand why the state has always seemed to be the enemy of “people who move around,” to put it crudely. […] Nomads and pastoralists (such as Berbers and Bedouins), hunter-gatherers, Gypsies, vagrants, homeless people, itinerants, runaway slaves, and serfs have always been a thorn in the side of states. Efforts to permanently settle these mobile peoples (sedentarization) seemed to be a perennial state project—perennial, in part, because it so seldom succeeded. The more I examined these efforts at sedentarization, the more I came to see them as a state’s attempt to make a society legible, to arrange the population in ways that simplified the classic state functions of taxation, conscription, and prevention of rebellion. Having begun to think in these terms, I began to see legibility as a central problem in statecraft. […] much of early modern European statecraft seemed […] devoted to rationalizing and standardizing what was a social hieroglyph into a legible and administratively more convenient format. The social simplifications thus introduced not only permitted a more finely tuned system of taxation and conscription but also greatly enhanced state capacity. […] These state simplifications, the basic givens of modern statecraft, were, I began to realize, rather like abridged maps. They did not successfully represent the actual activity of the society they depicted, nor were they intended to; they represented only that slice of it that interested the official observer. They were, moreover, not just maps. Rather, they were maps that, when allied with state power, would enable much of the reality they depicted to be remade. Thus a state cadastral map created to designate taxable property-holders does not merely describe a system of land tenure; it creates such a system through its ability to give its categories the force of law.” (James C. Scott, Seeing Like a State, pp.1-2)
  2. “No cynicism or mendacity need be involved. It is perfectly natural for leaders and generals to exaggerate their influence on events; that is the way the world looks from where they sit, and it is rarely in the interest of their subordinates to contradict their picture.” (-ll-, p.160)
  3. “Old-growth forests, polycropping, and agriculture with open-pollinated landraces may not be as productive, in the short run, as single-species forests and fields or identical hybrids. But they are demonstrably more stable, more self-sufficient, and less vulnerable to epidemics and environmental stress, needing far less in the way of external infusions to keep them on track. Every time we replace “natural capital” (such as wild fish stocks or old-growth forests) with what might be called “cultivated natural capital” (such as fish farms or tree plantations), we gain in ease of appropriation and in immediate productivity, but at the cost of more maintenance expenses and less “redundancy, resiliency, and stability.”[14] If the environmental challenges faced by such systems are both modest and predictable, then a certain simplification might also be relatively stable.[15] Other things being equal, however, the less diverse the cultivated natural capital, the more vulnerable and nonsustainable it becomes. The problem is that in most economic systems, the external costs (in water or air pollution, for example, or the exhaustion of nonrenewable resources, including a reduction in biodiversity) accumulate long before the activity becomes unprofitable in a narrow profit-and-loss sense.
    A roughly similar case can be made, I think, for human institutions — a case that contrasts the fragility of rigid, single-purpose, centralized institutions to the adaptability of more flexible, multipurpose, decentralized social forms. As long as the task environment of an institution remains repetitive, stable, and predictable, a set of fixed routines may prove exceptionally efficient. In most economies and in human affairs generally, this is seldom the case, and such routines are likely to be counterproductive once the environment changes appreciably.” (-ll-, pp. 353-354)
  4. “If the facts — that is, the behavior of living human beings — are recalcitrant to […] an experiment, the experimenter becomes annoyed and tries to alter the facts to fit the theory, which, in practice, means a kind of vivisection of societies until they become what the theory originally declared that the experiment should have caused them to be. (Isaiah Berlin, “On Political Judgment”)
  5. “Before a disaster strikes, all your preparation looks like waste. After a disaster strikes, it looks like you didn’t do enough. Every time.” (‘Coagulopath’, here)
  6. “The effort an interested party makes to put its case before the decisionmaker will be in proportion to the advantage to be gained from a favorable outcome multiplied by the probability of influencing the decision.” (Edward Banfeld, quote from Albert Otto Hirschman’s Exit, Voice and Loyalty, Harvard University Press)
  7. The argument to be presented [in this book] starts with the firm producing saleable outputs for customers; but it will be found to be largely — and, at times, principally — applicable to organizations (such as voluntary associations, trade unions, or political parties) that provide services to their members without direct monetary counterpart. The performance of a firm or an organization is assumed to be subject to deterioration for unspecified, random causes which are neither so compelling nor so durable as to prevent a return to previous performance levels, provided managers direct their attention and energy to that task. The deterioration in performance is reflected most typically and generally, that is, for both firms and other organizations, in an absolute or comparative deterioration of the quality of the product or service provided.1 Management then finds out about its failings via two alternative routes: (1) Some customers stop buying the firm’s products or some members leave the organization: this is the exit option. As a result, revenues drop, membership declines, and management is impelled to search for ways and means to correct whatever faults have led to exit. (2) The firm’s customers or the organization’s members express their dissatisfaction directly to management or to some other authority to which management is subordinate or through general protest addressed to anyone who cares to listen: this is the voice option.” (ibid.)
  8. “Voice has the function of alerting a firm or organization to its failings, but it must then give management, old or new, some time to respond to the pressures that have been brought to bear on it. […] In the case of any one particular firm or organization and its deterioration, either exit or voice will ordinarily have the role of the dominant reaction mode. The subsidiary mode is then likely to show up in such limited volume that it will never become destructive for the simple reason that, if deterioration proceeds, the job of destruction is accomplished single-handedly by the dominant mode. In the case of normally competitive business firms, for example, exit is clearly the dominant reaction to deterioration and voice is a badly underdeveloped mechanism; it is difficult to conceive of a situation in which there would be too much of it.” (-ll-)
  9. “The reluctance to exit in spite of disagreement with the organization of which one is a member is the hallmark of loyalist behavior. When loyalty is present exit abruptly changes character: the applauded rational behavior of the alert consumer shifting to a better buy becomes disgraceful defection, desertion, and treason. Loyalist behavior […] can be understood in terms of a generalized concept of penalty for exit. The penalty may be directly imposed, but in most cases it is internalized. The individual feels that leaving a certain group carries a high price with it, even though no specific sanction is imposed by the group. In both cases, the decision to remain a member and not to exit in the face of a superior alternative would thus appear to follow from a perfectly rational balancing of prospective private benefits against private costs.” (-ll-)
  10. “The preference that [an] individual ends up conveying to others is what I will call his public preference. It is distinct from his private preference, which is what he would express in the absence of social pressures. By definition, preference falsification is the selection of a public preference that differs from one’s private preference. […] It is public opinion, rather than private opinion, that undergirds political power. Private opinion may be highly unfavorable to a regime, policy, or institution without generating a public outcry for change. The communist regimes of Eastern Europe survived for decades even though they were widely despised. They remained in power as long as public opinion remained overwhelmingly in their favor, collapsing instantly when street crowds mustered the courage to rise against them.” (Timur Kuran, Private Truths, Public Lies, Harvard University Press).
  11. “Even in democratic societies, where the right to think, speak, and act freely enjoys official protection, and where tolerance is a prized virtue, unorthodox views can evoke enormous hostility. In the United States, for instance, to defend the sterilization of poor women or the legalization of importing ivory would be to raise doubts about one’s civility and morality, if not one’s sanity. […] strictly enforced, freedom of speech does not insulate people’s reputations from their expressed opinions. Precisely because people who express different opinions do get treated differently, individuals normally tailor their expressions to the prevailing social pressures. Their adjustments vary greatly in social impact. At one extreme are harmless, and possibly beneficial, acts of politeness, as when one tells a friend wearing a garish shirt that he has good taste. At the other are acts of spinelessness on issues of general concern, as when a politician endorses a protectionist measure that he recognizes as harmful to most of his constituents. The pressures generating such acts of insincerity need not originate from the government. Preference falsification is compatible with all political systems, from the most unyielding dictatorship to the most libertarian democracy.” (-ll-)
  12. “How will the individual choose what preference to convey? Three distinct considerations may enter his calculations: the satisfaction he is likely to obtain from society’s decision, the rewards and punishments associated with his chosen preference, and finally, the benefits he derives from truthful self-expression. If large numbers of individuals are expressing preferences on the issue, the individual’s capacity to influence the collective decision is likely to be negligible. In this case he will consider society’s decision to be essentially fixed, basing his own preference declaration only on the second and third considerations. Ordinarily, these offer a tradeoff between the benefits of self-expression and those of being perceived as someone with the right preference. Where the latter benefits dominate, our individual will engage in preference falsification.” (-ll-)
  13. “Issues of political importance present individuals with tradeoffs between outer and inner peace. Frequently, therefore, these matters force people to choose between their reputations and their individualities. There are contexts, of course, in which such tradeoffs are dealt with by remaining silent […]. Silence has two possible advantages and two disadvantages. On the positive side, it spares one the penalty of taking a position offensive to others, and it may lessen the inner cost of preference falsification. On the negative side, one gives up available rewards, and one’s private preference remains hidden. On some controversial issues, the sum of these various payoffs may exceed the net payoff to expressing some preference. Certain contexts present yet another option: abandoning the decision-making group that is presenting one with difficult choices. This option, “exit,” is sometimes exercised by group members unhappy with the way things are going, yet powerless to effect change. […] For all practical purposes, exit is not always a viable option. Often our choices are limited to expressing some preference or remaining silent.” (-ll-)
  14. “In a polarized political environment, individuals may not be able to position themselves on neutral ground even if they try. Each side may perceive a declaration of neutrality or moderation as collaboration with the enemy, leaving moderates exposed to attacks from two directions at once.” (-ll-)
  15. “[C]ontinuities [in societal/organizational structures] arise from obstacles to implementing change. One impediment, explored in Albert Hirschman’s Exit, Voice, and Loyalty, consists of individual decisions to “exit”: menacing elements of the status quo survive as people capable of making a difference opt to abandon the relevant decision-making group.2 Another such mechanism lies at the heart of Mancur Olson’s book on patterns of economic growth, The Rise and Decline of Nations: unpopular choices persist because the many who support change are less well organized than the few who are opposed.3 Here I argue that preference falsification is a complementary, yet more elementary, reason for the persistence of unwanted social choices. Hirschman’s exit is a form of public identification with change, as is his “voice,” which he defines as vocal protest. Preference falsification is often cheaper than escape, and it avoids the risks inherent in public protest. Frequently, therefore, it is the initial response of people who become disenchanted with the status quo.” (-ll-)
  16. “Public opinion can be divided yet heavily favor the status quo, with the few public dissenters being treated as deviants, opportunists, or villains. If millions have misgivings about a policy but only hundreds will speak up, one can sensibly infer that discussion on the policy is not free.” (-ll-)
  17. “…heuristics are most likely to be used under one or more of the following conditions: we do not have time to think carefully about an issue; we are too overloaded with information to process it fully; the issues at stake are unimportant; we have little other information on which to base a decision; and a given heuristic comes quickly to mind.” (-ll-)
  18. “What most people outside of analytics often fail to appreciate is that to generate what is seen, there’s a complex machinery that is unseen. For every dashboard and insight that a data analyst generates and for each predictive model developed by a data scientist, there are data pipelines working behind the scenes. It’s not uncommon for a single dashboard, or even a single metric, to be derived from data originating in multiple source systems. In addition, data pipelines do more than just extract data from sources and load them into simple database tables or flat files for analysts to use. Raw data is refined along the way to clean, structure, normalize, combine, aggregate, and at times anonymize or otherwise secure it. […] In addition, pipelines are not just built — they are monitored, maintained, and extended. Data engineers are tasked with not just delivering data once, but building pipelines and supporting infrastructure that deliver and process it reliably, securely, and on time.” (Data Pipelines Pocket Reference, James Densmore, O’Reilly Media)
  19. “The S in IoT stands for security.” (‘Windowsteak’, here)
  20. “Do not seek for information of which you cannot make use.” (Anna C. Brackett)

June 26, 2021 Posted by | Anthropology, Books, culture, Data, Quotes/aphorisms | Leave a comment

Quotes

i. “‘Intuition’ comes first. Reasoning comes second.” (Llewelyn & Doorn, Clinical Psychology: A Very Short Introduction, Oxford University Press)

ii. “We tend to cope with difficulties in ways that are familiar to us — acting in ways that were helpful to us in the past, even if these ways are now ineffective or destructive.” (-ll-)

iii. “We all thrive when given attention, and being encouraged and praised is more effective at changing our behaviour than being punished. The best way to increase the frequency of a behaviour is to reward it.” (-ll-)

iv. “You can’t make people change if they don’t want to, but you can support and encourage them to make changes.” (-ll-)

v. “You shall know a word by the company it keeps” (John Rupert Firth, as quoted in Thierry Poibeau’s Machine Translation, MIT Press).

vi. “The basic narrative of sedentism and agriculture has long survived the mythology that originally supplied its charter. From Thomas Hobbes to John Locke to Giambattista Vico to Lewis Henry Morgan to Friedrich Engels to Herbert Spencer to Oswald Spengler to social Darwinist accounts of social evolution in general, the sequence of progress from hunting and gathering to nomadism to agriculture (and from band to village to town to city) was settled doctrine. Such views nearly mimicked Julius Caesar’s evolutionary scheme from households to kindreds to tribes to peoples to the state (a people living under laws), wherein Rome was the apex […]. Though they vary in details, such accounts record the march of civilization conveyed by most pedagogical routines and imprinted on the brains of schoolgirls and schoolboys throughout the world. The move from one mode of subsistence to the next is seen as sharp and definitive. No one, once shown the techniques of agriculture, would dream of remaining a nomad or forager. Each step is presumed to represent an epoch-making leap in mankind’s well-being: more leisure, better nutrition, longer life expectancy, and, at long last, a settled life that promoted the household arts and the development of civilization. Dislodging this narrative from the world’s imagination is well nigh impossible; the twelve-step recovery program required to accomplish that beggars the imagination. I nevertheless make a small start here. It turns out that the greater part of what we might call the standard narrative has had to be abandoned once confronted with accumulating archaeological evidence.” (James C. Scott, Against the Grain, Yale University Press)

vii. “Thanks to hominids, much of the world’s flora and fauna consist of fire-adapted species (pyrophytes) that have been encouraged by burning. The effects of anthropogenic fire are so massive that they might be judged, in an evenhanded account of the human impact on the natural world, to overwhelm crop and livestock domestications.” (-ll-)

viii. “Most discussions of plant domestication and permanent settlement […] assume without further ado that early peoples could not wait to settle down in one spot. Such an assumption is an unwarranted reading back from the standard discourses of agrarian states stigmatizing mobile populations as primitive. […] Nor should the terms “pastoralist,” “agriculturalist,” “hunter,” or “forager,” at least in their essentialist meanings, be taken for granted. They are better understood as defining a spectrum of subsistence activities, not separate peoples […] A family or village whose crops had failed might turn wholly or in part to herding; pastoralists who had lost their flocks might turn to planting. Whole areas during a drought or wetter period might radically shift their subsistence strategy. To treat those engaged in these different activities as essentially different peoples inhabiting different life worlds is again to read back the much later stigmatization of pastoralists by agrarian states to an era where it makes no sense.” (-ll-)

ix. “Neither holy, nor Roman, nor an empire” (Voltaire, on the Holy Roman Empire, as quoted in Joachim Whaley’s The Holy Roman Empire: A Very Short Introduction, Oxford University Press)

x. “We don’t outgrow difficult conversations or get promoted past them. The best workplaces and most effective organizations have them. The family down the street that everyone thinks is perfect has them. Loving couples and lifelong friends have them. In fact, we can make a reasonable argument that engaging (well) in difficult conversations is a sign of health in a relationship. Relationships that deal productively with the inevitable stresses of life are more durable; people who are willing and able to “stick through the hard parts” emerge with a stronger sense of trust in each other and the relationship, because now they have a track record of having worked through something hard and seen that the relationship survived.” (Stone et al., Difficult Conversations, Penguin Publishing Group)

xi. “[D]ifficult conversations are almost never about getting the facts right. They are about conflicting perceptions, interpretations, and values. […] They are not about what is true, they are about what is important. […] Interpretations and judgments are important to explore. In contrast, the quest to determine who is right and who is wrong is a dead end. […] When competent, sensible people do something stupid, the smartest move is to try to figure out, first, what kept them from seeing it coming and, second, how to prevent the problem from happening again. Talking about blame distracts us from exploring why things went wrong and how we might correct them going forward.” (-ll-)

xii. “[W]e each have different stories about what is going on in the world. […] In the normal course of things, we don’t notice the ways in which our story of the world is different from other people’s. But difficult conversations arise at precisely those points where important parts of our story collide with another person’s story. We assume the collision is because of how the other person is; they assume it’s because of how we are. But really the collision is a result of our stories simply being different, with neither of us realizing it. […] To get anywhere in a disagreement, we need to understand the other person’s story well enough to see how their conclusions make sense within it. And we need to help them understand the story in which our conclusions make sense. Understanding each other’s stories from the inside won’t necessarily “solve” the problem, but […] it’s an essential first step.” (-ll-)

xiii. “I am really nervous about the word “deserve”. In some cosmic sense nobody “deserves” anything – try to tell the universe you don’t deserve to grow old and die, then watch it laugh at [you] as you die anyway.” (Scott Alexander)

xiv. “How we spend our days is, of course, how we spend our lives.” (Annie Dillard)

xv. “If you do not change direction, you may end up where you are heading.” (Lao Tzu)

xvi. “The smart way to keep people passive and obedient is to strictly limit the spectrum of acceptable opinion, but allow very lively debate within that spectrum.” (Chomsky)

xvii. “If we don’t believe in free expression for people we despise, we don’t believe in it at all.” (-ll-)

xviii. “I weigh the man, not his title; ’tis not the king’s stamp can make the metal better.” (William Wycherley)

xix. “Money is the fruit of evil as often as the root of it.” (Henry Fielding)

xx. “To whom nothing is given, of him can nothing be required.” (-ll-)

March 26, 2021 Posted by | Archaeology, Books, History, Psychology, Quotes/aphorisms | Leave a comment

Algorithms to live by…

“…algorithms are not confined to mathematics alone. When you cook bread from a recipe, you’re following an algorithm. When you knit a sweater from a pattern, you’re following an algorithm. When you put a sharp edge on a piece of flint by executing a precise sequence of strikes with the end of an antler—a key step in making fine stone tools—you’re following an algorithm. Algorithms have been a part of human technology ever since the Stone Age.

* * *

In this book, we explore the idea of human algorithm design—searching for better solutions to the challenges people encounter every day. Applying the lens of computer science to everyday life has consequences at many scales. Most immediately, it offers us practical, concrete suggestions for how to solve specific problems. Optimal stopping tells us when to look and when to leap. The explore/exploit tradeoff tells us how to find the balance between trying new things and enjoying our favorites. Sorting theory tells us how (and whether) to arrange our offices. Caching theory tells us how to fill our closets. Scheduling theory tells us how to fill our time. At the next level, computer science gives us a vocabulary for understanding the deeper principles at play in each of these domains. As Carl Sagan put it, “Science is a way of thinking much more than it is a body of knowledge.” Even in cases where life is too messy for us to expect a strict numerical analysis or a ready answer, using intuitions and concepts honed on the simpler forms of these problems offers us a way to understand the key issues and make progress. […] tackling real-world tasks requires being comfortable with chance, trading off time with accuracy, and using approximations.”

I recall Zach Weinersmith recommending the book, and I seem to recall him mentioning when he did so that he’d put off reading it ‘because it sounded like a self-help book’ (paraphrasing). I’m not actually sure how to categorize it but I do know that I really enjoyed it; I gave it five stars on goodreads and added it to my list of favourite books.

The book covers a variety of decision problems and tradeoffs which people face in their every day lives, as well as strategies for how to approach such problems and identify good solutions (if they exist). The explore/exploit tradeoff so often implicitly present (e.g.: ‘when to look for a new restaurant, vs. picking one you are already familiar with’, or perhaps: ‘when to spend time with friends you already know, vs. spending time trying to find new (/better?) friends?’), optimal stopping rules (‘at which point do you stop looking for a romantic partner and decide that ‘this one is the one’?’ – this is perhaps a well-known problem with a well-known solution, but had you considered that you might use the same analytical framework for questions such as: ‘when to stop looking for a better parking spot and just accept that this one is probably the best one you’ll be able to find?’?), sorting problems (good and bad ways of sorting, why sort, when is sorting even necessary/required?, etc.), scheduling theory (how to handle task management in a good way, so that you optimize over a given constraint set – some examples from this part are included in the quotes below), satisficing vs optimizing (heuristics, ‘when less is more’, etc.), etc. The book is mainly a computer science book, but it is also to some extent an implicitly interdisciplinary work covering material from a variety of other areas such as statistics, game theory, behavioral economics and psychology. There is a major focus throughout on providing insights which are actionable and can actually be used by the reader, e.g. through the translation of identified solutions to heuristics which might be applied in every day life. The book is more pop-science-like than any book I’d have liked to read 10 years ago, and there are too many personal anecdotes for my taste included, but in some sense this never felt like a major issue while I was reading; a lot of interesting ideas and topics are covered, and the amount of fluff is within acceptable limits – a related point is also that the ‘fluff’ is also part of what makes the book relevant, because the authors really focus on tradeoffs and problems which really are highly relevant to some potentially key aspects of most people’s lives, including their own.

Below I have added some sample quotes from the book. If you like the quotes you’ll like the book, it’s full of this kind of stuff. I definitely recommend it to anyone remotely interested in decision theory and related topics.

“…one of the deepest truths of machine learning is that, in fact, it’s not always better to use a more complex model, one that takes a greater number of factors into account. And the issue is not just that the extra factors might offer diminishing returns—performing better than a simpler model, but not enough to justify the added complexity. Rather, they might make our predictions dramatically worse. […] overfitting poses a danger every time we’re dealing with noise or mismeasurement – and we almost always are. […] Many prediction algorithms […] start out by searching for the single most important factor rather than jumping to a multi-factor model. Only after finding that first factor do they look for the next most important factor to add to the model, then the next, and so on. Their models can therefore be kept from becoming overly complex simply by stopping the process short, before overfitting has had a chance to creep in. […] This kind of setup — where more time means more complexity — characterizes a lot of human endeavors. Giving yourself more time to decide about something does not necessarily mean that you’ll make a better decision. But it does guarantee that you’ll end up considering more factors, more hypotheticals, more pros and cons, and thus risk overfitting. […] The effectiveness of regularization in all kinds of machine-learning tasks suggests that we can make better decisions by deliberately thinking and doing less. If the factors we come up with first are likely to be the most important ones, then beyond a certain point thinking more about a problem is not only going to be a waste of time and effort — it will lead us to worse solutions. […] sometimes it’s not a matter of choosing between being rational and going with our first instinct. Going with our first instinct can be the rational solution. The more complex, unstable, and uncertain the decision, the more rational an approach that is.” (…for more on these topics I recommend Gigerenzer)

“If you’re concerned with minimizing maximum lateness, then the best strategy is to start with the task due soonest and work your way toward the task due last. This strategy, known as Earliest Due Date, is fairly intuitive. […] Sometimes due dates aren’t our primary concern and we just want to get stuff done: as much stuff, as quickly as possible. It turns out that translating this seemingly simple desire into an explicit scheduling metric is harder than it sounds. One approach is to take an outsider’s perspective. We’ve noted that in single-machine scheduling, nothing we do can change how long it will take us to finish all of our tasks — but if each task, for instance, represents a waiting client, then there is a way to take up as little of their collective time as possible. Imagine starting on Monday morning with a four-day project and a one-day project on your agenda. If you deliver the bigger project on Thursday afternoon (4 days elapsed) and then the small one on Friday afternoon (5 days elapsed), the clients will have waited a total of 4 + 5 = 9 days. If you reverse the order, however, you can finish the small project on Monday and the big one on Friday, with the clients waiting a total of only 1 + 5 = 6 days. It’s a full workweek for you either way, but now you’ve saved your clients three days of their combined time. Scheduling theorists call this metric the “sum of completion times.” Minimizing the sum of completion times leads to a very simple optimal algorithm called Shortest Processing Time: always do the quickest task you can. Even if you don’t have impatient clients hanging on every job, Shortest Processing Time gets things done.”

“Of course, not all unfinished business is created equal. […] In scheduling, this difference of importance is captured in a variable known as weight. […] The optimal strategy for [minimizing weighted completion time] is a simple modification of Shortest Processing Time: divide the weight of each task by how long it will take to finish, and then work in order from the highest resulting importance-per-unit-time [..] to the lowest. […] this strategy … offers a nice rule of thumb: only prioritize a task that takes twice as long if it’s twice as important.”

“So far we have considered only factors that make scheduling harder. But there is one twist that can make it easier: being able to stop one task partway through and switch to another. This property, “preemption,” turns out to change the game dramatically. Minimizing maximum lateness … or the sum of completion times … both cross the line into intractability if some tasks can’t be started until a particular time. But they return to having efficient solutions once preemption is allowed. In both cases, the classic strategies — Earliest Due Date and Shortest Processing Time, respectively — remain the best, with a fairly straightforward modification. When a task’s starting time comes, compare that task to the one currently under way. If you’re working by Earliest Due Date and the new task is due even sooner than the current one, switch gears; otherwise stay the course. Likewise, if you’re working by Shortest Processing Time, and the new task can be finished faster than the current one, pause to take care of it first; otherwise, continue with what you were doing.”

“…even if you don’t know when tasks will begin, Earliest Due Date and Shortest Processing Time are still optimal strategies, able to guarantee you (on average) the best possible performance in the face of uncertainty. If assignments get tossed on your desk at unpredictable moments, the optimal strategy for minimizing maximum lateness is still the preemptive version of Earliest Due Date—switching to the job that just came up if it’s due sooner than the one you’re currently doing, and otherwise ignoring it. Similarly, the preemptive version of Shortest Processing Time—compare the time left to finish the current task to the time it would take to complete the new one—is still optimal for minimizing the sum of completion times. In fact, the weighted version of Shortest Processing Time is a pretty good candidate for best general-purpose scheduling strategy in the face of uncertainty. It offers a simple prescription for time management: each time a new piece of work comes in, divide its importance by the amount of time it will take to complete. If that figure is higher than for the task you’re currently doing, switch to the new one; otherwise stick with the current task. This algorithm is the closest thing that scheduling theory has to a skeleton key or Swiss Army knife, the optimal strategy not just for one flavor of problem but for many. Under certain assumptions it minimizes not just the sum of weighted completion times, as we might expect, but also the sum of the weights of the late jobs and the sum of the weighted lateness of those jobs.”

“…preemption isn’t free. Every time you switch tasks, you pay a price, known in computer science as a context switch. When a computer processor shifts its attention away from a given program, there’s always a certain amount of necessary overhead. […] It’s metawork. Every context switch is wasted time. Humans clearly have context-switching costs too. […] Part of what makes real-time scheduling so complex and interesting is that it is fundamentally a negotiation between two principles that aren’t fully compatible. These two principles are called responsiveness and throughput: how quickly you can respond to things, and how much you can get done overall. […] Establishing a minimum amount of time to spend on any one task helps to prevent a commitment to responsiveness from obliterating throughput […] The moral is that you should try to stay on a single task as long as possible without decreasing your responsiveness below the minimum acceptable limit. Decide how responsive you need to be — and then, if you want to get things done, be no more responsive than that. If you find yourself doing a lot of context switching because you’re tackling a heterogeneous collection of short tasks, you can also employ another idea from computer science: “interrupt coalescing.” If you have five credit card bills, for instance, don’t pay them as they arrive; take care of them all in one go when the fifth bill comes.”

February 10, 2021 Posted by | Books, Computer science, Economics, Game theory, Psychology | Leave a comment

Shock waves and gamma-ray bursts from neutron star mergers – Andrei Beloborodov

Some links related to stuff discussed in the lecture/talk:
GW170817.
Superluminal motion of a relativistic jet in the neutron starmerger GW170817 (Mooley et al., 2018).
GRB 170817A Associated with GW170817: Multi-frequency Observations and Modeling of Prompt Gamma-ray Emission (Pozanenko et al., 2018).
Lorentz factor.
Gamma-ray burst progenitors.
Kilonova.
ResearchGate download link: A First-principle Simulation of Blast-wave Emergence at the Photosphere of a Neutron Star Merger (Lundman & Beloborodov, 2020).
Adiabatic index.
Shock waves in astrophysics.
Diffusive Shock Acceleration: the Fermi Mechanism.
Inverse Compton scattering.

February 3, 2021 Posted by | Astronomy, Lectures, Physics | Leave a comment

Words

Amaurosis. Metanoia. Adit. Scansion. Gavage. Psephology. Sphaleron. Axonotmesis. Galena. Pingo. Girdling. Snag (ecology). Apophenia. Cenote. Neurotmesis. Acerose. Perseverant. Elapid. Aorist. Kana.

Intaglio. Hiragana. Palinal. Cathemerality. Calque. Numinous. Geas. Afforestation. Crumhorn. Senicide. Catenane. Extispicy/haruspex. Cataplerosis. Ophiolite. Diglossia. Hagiographer. Stylometry. Ossifrage. Pleuston/Neuston. Praline.

Saponification. Culet. Myiasis. Epithalamium. Thigmonasty. Stultiloquy. Thigmotropism. Aerospike. Calabash. Pandanus. Dumbwaiter. Doula. Hypocaust. Cynophobia. Flashover. Backdraft. Pyrolysis. Slat. Phugoid. Toxophily.

Irredentism. Crutching. Threnody. Petroglyph. Protologism. Aileron. Bunding. Phylactery. Guyot. Coupure. Barbette. Apophasis. Fissiparous. Marl. Syrinx. Bocage. Camouflet. Mulesing. Trypophobia. Berm.

January 17, 2021 Posted by | Books, Language | Leave a comment

James Simons interview


James Simons. Differential geometry. Minimal varieties in riemannian manifolds. Shiing-Shen Chern. Characteristic Forms and Geometric Invariants. Renaissance Technologies.

“That’s really what’s great about basic science and in this case mathematics, I mean, I didn’t know any physics. It didn’t occur to me that this material, that Chern and I had developed would find use somewhere else altogether. This happens in basic science all the time that one guy’s discovery leads to someone else’s invention and leads to another guy’s machine or whatever it is. Basic science is the seed corn of our knowledge of the world. …I loved the subject, but I liked it for itself, I wasn’t thinking of applications. […] the government’s not doing such a good job at supporting basic science and so there’s a role for philanthropy, an increasingly important role for philanthropy.”

“My algorithm has always been: You put smart people together, you give them a lot of freedom, create an atmosphere where everyone talks to everyone else. They’re not hiding in the corner with their own little thing. They talk to everybody else. And you provide the best infrastructure. The best computers and so on that people can work with and make everyone partners.”

“We don’t have enough teachers of mathematics who know it, who know the subject … and that’s for a simple reason: 30-40 years ago, if you knew some mathematics, enough to teach in let’s say high school, there weren’t a million other things you could do with that knowledge. Oh yeah, maybe you could become a professor, but let’s suppose you’re not quite at that level but you’re good at math and so on.. Being a math teacher was a nice job. But today if you know that much mathematics, you can get a job at Google, you can get a job at IBM, you can get a job in Goldman Sachs, I mean there’s plenty of opportunities that are going to pay more than being a high school teacher. There weren’t so many when I was going to high school … so the quality of high school teachers in math has declined, simply because if you know enough to teach in high school you know enough to work for Google…”

January 12, 2021 Posted by | Mathematics, Papers, Science | Leave a comment

Quotes

  • “It is not the answer that enlightens, but the question.” (Eugène Ionesco)
  • “Where would be the merit if heroes were never afraid?” (Alphonse Daudet)
  • “In wartime a man is called a hero. It doesn’t make him any braver, and he runs for his life. But at least it’s a hero who is running away.” (Jean Giraudoux)
  • “Love is worth whatever it costs.” (Françoise Sagan)
  • “It is healthier to see the good points of others than to analyze our own bad ones.” (-ll-)
  • “When a man has dreamed of winning something by a colossal stroke of luck, he is prone to neglect petty but more practical ways of attaining it.” (-ll-)
  • “I find war detestable but those who praise it without participating in it even more so.” (Romain Rolland)
  • “There is something sadder to lose than life – the reason for living; Sadder than to lose one’s possessions is to lose one’s hope.” (Paul Claudel)
  • “This is rather as if you imagine a puddle waking up one morning and thinking, ‘This is an interesting world I find myself in — an interesting hole I find myself in — fits me rather neatly, doesn’t it? In fact it fits me staggeringly well, must have been made to have me in it!’ This is such a powerful idea that as the sun rises in the sky and the air heats up and as, gradually, the puddle gets smaller and smaller, frantically hanging on to the notion that everything’s going to be alright, because this world was meant to have him in it, was built to have him in it; so the moment he disappears catches him rather by surprise. I think this may be something we need to be on the watch out for.” (Douglas Adams)
  • “The Englishman of 1750 was closer in material things to Caesar’s legionnaires than to his own great-grandchildren.” (Walter Scheidel, Escape from Rome (The Princeton Economic History of the Western World, Princeton University Press))
  • “In the Western world, […] mature male stature rose by five inches between the late eighteenth and the late twentieth centuries.” (-ll-)
  • People exaggerate both happiness and unhappiness; we are never so fortunate nor so unfortunate as people say we are. (/On amplifie également le malheur et le bonheur, nous ne sommes jamais ni si malheureux, ni si heureux qu’on le dit.) (Honoré de Balzac)
  • “When women love, they forgive everything, even our crimes; when they do not love, they cannot forgive anything, not even our virtues.” (/Lorsque les femmes nous aiment, elles nous pardonnent tout, même nos crimes; lorsqu’elles ne nous aiment pas, elles ne nous pardonnent rien, pas même nos vertus!) (-ll-)
  • “Those who spend too fast never grow rich.” (/Qui dépense trop n’est jamais riche) (-ll-)
  • “Numerical results of mathematical problems can be tested by comparing them to observed numbers, or to a commonsense estimate of observable numbers. […] Yet every teacher knows that students achieve incredible things in this respect. Some students are not disturbed at all when they find 16,130 ft. for the length of the boat and 8 years, 2 months for the age of the captain who is, by the way, known to be a grandfather. Such neglect of the obvious does not show necessarily stupidity but rather indifference toward artificial problems. […] [A] teacher of mathematics has a great opportunity. If he fills his allotted time with drilling his students in routine operations he kills their interest, hampers their intellectual development, and misuses his opportunity. But if he challenges the curiosity of his students by setting them problems proportionate to their knowledge, and helps them to solve their problems with stimulating questions, he may give them a taste for, and some means of, independent thinking.” (George Pólya, How to Solve It. Princeton University Press)
  • “If you can’t solve a problem, then there is an easier problem you can’t solve. Find it.” (-ll-)
  • “No idea is really bad, unless we are uncritical. What is really bad is to have no idea at all. […] in theoretical matters, the best of ideas is hurt by uncritical acceptance and thrives on critical examination.” (-ll-)
  • “Let us sum up. Recollecting formerly solved problems with the same or a similar unknown (formerly proved theorems with the same or a similar conclusion) we have a good chance to start in the right direction and we may conceive a plan of the solution. In simple cases, which are the most frequent in less advanced classes, the most elementary problems with the same unknown (theorems with the same conclusion) are usually sufficient. Trying to recollect problems with the same unknown is an obvious and common-sense device […]. It is rather surprising that such a simple and useful device is not more widely known […] neither students nor teachers of mathematics can afford to ignore the proper use of the suggestion: Look at the unknown! And try to think of a familiar problem having the same or a similar unknown.” (-ll-)
  • “Speaking and thinking are closely connected, the use of words assists the mind. […] choosing a suitable notation may contribute essentially to understanding the problem. […] A good notation should be unambiguous, pregnant, easy to remember; it should avoid harmful second meanings, and take advantage of useful second meanings; the order and connection of signs should suggest the order and connection of things. […] we should choose our notation carefully, and have some good reason for our choice. […] Not only the most hopeless boys in the class but also quite intelligent students may have an aversion for algebra. There is always something arbitrary and artificial about notation; to learn a new notation is a burden for the memory. The intelligent student refuses to assume the burden if he does not see any compensation for it. The intelligent student is justified in his aversion for algebra if he is not given ample opportunity to convince himself by his own experience that the language of mathematical symbols assists the mind. To help him to such experience is an important task of the teacher, one of his most important tasks.” (-ll-)
  • Pedantry and mastery are opposite attitudes toward rules. […] To apply a rule to the letter, rigidly, unquestioningly, in cases where it fits and in cases where it does not fit, is pedantry. Some pedants are poor fools; they never did understand the rule which they apply so conscientiously and so indiscriminately. Some pedants are quite successful; they understood their rule, at least in the beginning (before they became pedants), and chose a good one that fits in many cases and fails only occasionally. To apply a rule with natural ease, with judgment, noticing the cases where it fits, and without ever letting the words of the rule obscure the purpose of the action or the opportunities of the situation, is mastery.” (-ll-)
  • “L’amour est un tyran qui n’épargne personne.” (/Love is a tyrant, sparing none.) (Pierre Corneille)
  • “To conquer without risk is to triumph without glory.” (-ll-)
  • “Il faut bonne mémoire après qu’on a menti.” (/It takes a good memory to keep up a lie.) (-ll-)
  • “The immune system functions so well that most of the time we do not notice it is actually working at all. However, it is continuously active, preventing severe infection from the micro-organisms which colonize our skin and our gut, and suppressing the chronic virus infections most of us picked up as infants. […] There are [even] data to suggest that mate choice (including in humans) can be driven by olfactory signals derived from […] MHC molecules — such that those with divergent MHC types are chosen, hence maximizing the number of different MHC molecules available to the offspring.” (Paul Klenerman – The Immune System: A Very Short Introduction, Oxford University Press)
  • “Music expresses that which cannot be said and on which it is impossible to be silent.” (Victor Hugo)
  • “Being a husband is a whole-time job. That is why so many husbands fail. They can’t give their entire attention to it.” (Arnold Bennett)
  • “Journalists say a thing that they know isn’t true, in the hope that if they keep on saying it long enough it will be true.” (-ll-) (They are wrong, and people should really stop taking those people seriouslysee part ii. here)
  • “Dying is a very dull, dreary affair. And my advice to you is to have nothing whatever to do with it.” (W. Somerset Maugham)
  • “People ask you for criticism, but they only want praise.” (-ll-)
  • “Unfortunately, theories that explain everything often explain very little.” (William Bynum. The History of Medicine: A Very Short Introduction (p. 76). Oxford University Press)
  • “Whatever the system of medical care, in Western societies, third-party arrangements are the norm in hospital payments, so large are the bills. The costs of building, heating, lighting, maintaining, equipping, and staffing these complex institutions have been an increasing concern for the past century. The guaranteeing body has been variously the state, the municipality, a religious organization, an insurance company, a charitable group, individual governors, a rich benefactor, or a combination of these. […] the drive for efficiency, and the adoption of business models, characterizes almost all modern hospitals. […] While developed nations can take the surveillance and regulations of public health for granted, or be incensed when they fail, […] the problems encountered in poorer parts of the world would not have surprised Edwin Chadwick or other advocates in 19th-century Europe. Issues of child and maternal mortality, epidemic diseases, poverty, and poor sanitation are still with us.” (Ibid., pp. 127-128, 136)
  • “I used to watch a lot of news and commentary until one day I tried to tally up what I had learned during a month of it and found the quantity of facts could fit on a postage stamp.” (Zach Weiner)
  • Eppur si muove…” (Galileo Galilei)
  • “Birds born in a cage think flying is an illness.” (Alejandro Jodorowsky)

October 16, 2020 Posted by | Books, History, Immunology, Mathematics, Quotes/aphorisms | Leave a comment

Promoting the unknown…

i.

ii.

iii.

iv.

v.

vi.

March 27, 2020 Posted by | Music | Leave a comment

Periodic Videos

I watched quite a few of their videos a very long time ago, but since then I haven’t really been following along. I happened to stumble across the channel on Friday evening, and this meant there was a lot of catching up to do.

I’ve added some of the videos I really enjoyed, but I couldn’t include all of them – there is a lot of good chemistry-related stuff in that channel, and a lot of interesting details about ‘how stuff works’ and/or ‘how we know something’. Even videos about obscure elements you didn’t even know existed may contain fascinating details that turn out to be really quite relevant to your every-day life; did you for example know that due to the material properties of niobium, by adding perhaps 200 grams of this material to a car, a car manufacturer might save in the order of 100 kilograms of steel? Well, I didn’t.

Oak Ridge National Laboratory
Neutron radiation
Involute
Triuranium octoxide
Californium
(See also this one for more footage from ORNL)

John Newlands (chemist)
William Odling
History of the periodic table
Alexandre-Émile Béguyer de Chancourtois.

Does Mendeleev get too much credit? An interesting ‘walk through the archives’. I agree with the overall assessment; other people came close/had similar ideas, but it’s quite natural for Mendeleev to be associated strongly with the Table; he pushed the idea very hard, and he was not afraid to make detailed predictions which might turn out to be wrong. As noted in (one of) Scerri’s book(/s) on the topic, “it has been estimated that within one hundred years of the introduction of Mendeleev’s famous table of 1869, approximately 700 different versions of the periodic table had been published” – so although the video seems to cover a lot of different versions, it’s really only scratching the surface.

1858 Bradford sweets poisoning.
Death of Napoleon Bonaparte.
Realgar.
Scheele’s Green.

January 26, 2020 Posted by | Chemistry, Engineering, History, Physics | Leave a comment

Books 2019

Here’s a goodreads link.

I won’t spend a lot of effort on this list – the main point of these lists in earlier years was to keep track of blogposts I wrote about books I’d read because I tended to blog quite a bit, and I realized that it was useful to have lists like these to refer to when looking for stuff I knew I’d read about in the past (I mainly use goodreads, not this blog, to keep track of the books themselves); but these days I blog very little and so there’s not actually a lot to keep track of.

I read 106 books and 34,925 pages in 2019, according to the list goodreads auto-generates each year.

This is not really ‘correct’, but it’s close. One of the books included in goodreads’ list I did not finish, and such books I don’t like to include in this kind of count (…there were actually two other books I also did not finish and decided to shelve this year, but neither of these books were added to the auto-generated list on goodreads; I’m still unclear as to how these algorithms work..). On the other hand the page count provided by goodreads is almost certainly too low, rather than too high, for two reasons: The first is that the longest book I read, The Complete Saki, did not have a page count on either goodreads or Kindle, meaning that no pages were logged for that book; however a paperback version of the book also added to goodreads actually has 960 pages. Two full novels are included in that book and they take up less than a third of the space – this also means, of course, that the supposedly longest book I read on the goodreads list is not actually the longest book I read. A second reason is that I did read a few hundred pages of two of the books I did not finish (…and ‘too many‘ of the third one which was included on the list, even if the pages were not counted), and the page count of partially read books are not logged on goodreads, so these were not included in the count. In August or September I figured I might try for 100 pages per day on average for the year, and given these considerations I think I got quite close, if perhaps not quite there. The other (soft) goal I had was 100 books, which I certainly managed – the final count was very close to two books per week, which is apparently the level I’m at currently, given the sort of books I read. Although blogging is very low on my list of priorities these days this did not mean I stopped reading as well; work takes a lot of time – more time than it did in 2018 – and the cognitive demands of my job have been increasing steadily during the last year, and so the time and resources I have left when I have time off I’d rather spend on reading than on blogging, certainly in part because reading material X is much less demanding than is blogging material X. It should also be quite obvious from the list that I in some periods of the year really did not have the mental surplus to engage in cognitively demanding activities outside of work. I feel proud of the work I did during some of those weeks, but I certainly can’t feel proud about my leisure reading habits during those weeks.

I read 16 non-fiction books, 5 ‘miscellaneous’ books and 84 fiction books to completion last year. I don’t read as much non-fiction as I’d like (…almost nothing compared to what I was reading five years ago), and I think I’ll probably create targeted personal goals for myself in this area this year to improve on that one, at least a little. However most of the non-fiction books I read this year were actually books with a significant amount of content, and I don’t mind trading off books for pages if the books I actually do read are well worth reading. I also need to be realistic, I’m not going to read a technical book from cover to cover during a week where my brain keeps jumping back to e.g. a current database configuration issue – less will have to do. And reading more is not necessarily a desirable outcome, a factor I’m trying to take into account when deciding how to spend my time; I’ve made an effort this year – successfully I believe, at least to some degree – to deliberately prioritize non-book activities like social events where possible, and I had more opportunities for doing so this year than I did last year.

The book count for this year dropped a lot compared to previous years, but if you look at the page count instead the drop is nowhere near as significant – the books I read this year were significantly longer, on average, than those I’ve read in previous years; last year I read 150 books and ~115 pages per day.

I only irregularly added books to goodreads during the year, which means that the books on the list will often not have been added in exactly the right order. This might mean for example that book 3 in a series comes before book 1 on the list, even if I read book 1 first. Frankly I don’t care about this, certainly not enough to try to recreate the list as it would have looked like if books had been added in a more timely manner.

Quite a few of the books on the list are books which I’ve read before; I decided not to add any links to old goodreads reviews in such cases, even if in one or two cases I did update a review after having reread the book this year. I also only added the current ratings of the books, not the ratings I’d given the books in the past.

As usual ‘f’ = fiction, ‘m’ = miscellaneous, ‘nf’ = non-fiction; the numbers in parentheses indicate my goodreads ratings of the books (from 1-5).

1. Medicine in the English Middle Ages (3, nf. Princeton University Press).

2. Olympiad (3, f). Tom Holt. Very short goodreads review here.

3. The Walled Orchard (4, f). Tom Holt. Goodreads review here.

4. A song for Nero (4, f). Tom Holt.

5. Unkempt Thoughts (3, m). Stanisław Jerzy Lec.

6. Alexander at the World’s End (5, f). Tom Holt. Short goodreads review here.

7. Meadowland (3, f). Tom Holt.

8. Brief Cases (4, f). Jim Butcher. Goodreads review here.

9. The Princess Bride (4, f). William Goldman.

10. Practical Demonkeeping (2, f). Christopher Moore.

11. The Tartar Steppe (f). Dino Buzatti.

12. Cognitive Neuroscience: A Very Short Introduction (3, nf. Oxford University Press).

13. The Stupidest Angel (3, f). Christopher Moore.

14. The Complete Saki: 144 Collected Novels and Short Stories (4, f). Short goodreads review here.

15. The Lust Lizard of Melancholy Cove (2, f). Christopher Moore.

16. Wilt (5, f). Tom Sharpe.

17. Angels in the Moonlight (2, f). Caimh McDonnell.

18. Last Orders (2, f). Caimh McDonnell.

19. You suck (2, f). Christopher Moore.

20. The Wilt Alternative (4, f). Tom Sharpe.

21. Wilt On High (4, f). Tom Sharpe.

22. A Man With One of Those Faces (3, f). Caimh McDonnell.

23. Bite Me (1, f). Christopher Moore.

24. Coyote Blue (2, f). Christopher Moore.

25. The Day That Never Comes (2, f). Caimh McDonnell.

26. Bloodsucking Fiends (2, f). Christopher Moore.

27. How to Attract the Wombat (4, m). Will Cuppy.

28. Wilt in Nowhere (f). Tom Sharpe.

29. My Ten Years in a Quandary and How They Grew (2, f). Robert Benchley. Goodreads review here.

30. Genomics: A Very Short Introduction (3, nf. Oxford University Press).

31. How to Tell Your Friends from the Apes (4, m). Will Cuppy.

32. Jill the Reckless (2, f). P. G. Wodehouse.

33. The Complete McAuslan (4, f). George MacDonald Fraser.

34. The Hot Rock (4, f). Donald E. Westlake.

35. Bank Shot (4, f). Donald E. Westlake.

36. Nobody’s Perfect (3, f). Donald E. Westlake.

37. Jimmy The Kid (3, f). Donald E. Westlake.

38. Good Behavior (3, f). Donald E. Westlake.

39. Why Me? (4, f). Donald E. Westlake.

40. Drowned Hopes (3, f). Donald E. Westlake.

41. Don’t Ask (3, f). Donald E. Westlake.

42. What’s The Worst That Could Happen? (4, f). Donald E. Westlake.

43. The Road To Ruin (3, f). Donald E. Westlake.

44. The Fugitive Pigeon (4, f). Donald E. Westlake.

45. Bad News (3, f). Donald E. Westlake.

46. Viruses: A Very Short Introduction (3, nf. Oxford University Press). Blog coverage here.

47. Watch Your Back! (4, f). Donald E. Westlake.

48. What’s So Funny? (3, f). Donald E. Westlake.

49. Get Real (3, f). Donald E. Westlake.

50. The Pleasure of Finding Things Out: The Best Short Works of Richard P. Feynman (5, nf.). Goodreads review here. Blog coverage here and here.

51. Cops and Robbers (2, f). Donald E. Westlake.

52. God Save the Mark (4, f). Donald E. Westlake.

53. The Spy in the Ointment (3, f). Donald E. Westlake.

54. High Adventure (3, f). Donald E. Westlake.

55. And Then There Were None (4, f). Agatha Christie.

56. The Eyre Affair (5, f). Jasper Fforde.

57. Galahad at Blandings (5, f). P.G. Wodehouse.

58. The Fourth Bear (5, f). Jasper Fforde.

59. Lost in a Good Book (5, f). Jasper Fforde.

60. In Gods We Trust: The Evolutionary Landscape of Religion (Evolution and Cognition) (4, nf. Oxford University Press). I really should have given this one 5 stars simply in order to motivate other people to read it, but I didn’t quite feel like it really deserved it; even so, this is the best book on the topic of religion I’ve read. If people in general understood religion and human belief systems as well as Scott Atran does, then the world would be a very different place indeed.

61. The Big Over Easy (5, f). Jasper Fforde.

62. The Well of Lost Plots (4, f). Jasper Fforde.

63. Intelligence: All That Matters (3, nf. Hodder & Stoughton).

64. First Among Sequels (3, f). Jasper Fforde.

65. Something Rotten (4, f). Jasper Fforde.

66. One of Our Thursdays Is Missing (4, f). Jasper Fforde.

67. The Woman Who Died a lot (4, f). Jasper Fforde.

68. The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter (5, nf. Princeton University Press). Goodreads review here (…a quote: “This is without a doubt the best book I’ve read this year. Highly recommended.”). I added this book to my list of favourite books on goodreads.

69. Bowling Alone (3, nf. Simon & Schuster). Goodreads review here.

70. Dyslexia: A Very Short Introduction (2, nf. Oxford University Press). Blog coverage here.

71. Thief of Time (f). Terry Pratchett.

72. Dead Cert (4, f). Dick Francis.

73. Rat Race (4, f). Dick Francis.

74. Smokescreen (3, f). Dick Francis.

75. Nerve (3, f). Dick Francis.

76. Odds Against (4, f). Dick Francis.

77. For Kicks (3, f). Dick Francis.

78. High Stakes (4, f). Dick Francis.

79. Forfeit (2, f). Dick Francis.

80. Whip Hand (2, f). Dick Francis.

81. Data Science for Business (2, nf. O’Reilly Media). Blog coverage here.

82. Break In (3, f). Dick Francis.

83. Bolt (4, f). Dick Francis.

84. The Edge (5, f). Dick Francis.

85. Straight (3, f). Dick Francis.

86. Driving Force (3, f). Dick Francis.

87. The Cloven Viscount (2, f). Italo Calvino.

88. Zuleika Dobson (2, f). Max Beerbohm. Short goodreads review here.

89. Dangling Man (2, f). Saul Bellow.

90. The Small Bachelor (4, f). P. G. Wodehouse.

91. The Nonexistent Knight (2, f). Italo Calvino.

92. A Pale View of Hills (5, f). Kazuo Ishiguro. Very short goodreads review here. This book was really powerful, I was very tempted to add it to my list of favourite books on goodreads.

93. An Artist of the Floating World (2, f). Kazuo Ishiguro. Goodreads review here.

94. Fire & Blood (5, f). George R. R. Martin.

95. I, Robot (3, f). Isaac Asimov.

96. Matter, A Very Short Introduction (3, nf. Oxford University Press).

97. Alteryx Inspire: Tips and Tricks 2019, London (nf. Publisher unclear, pdf-book written by Alteryx developers).

98. Lords and Ladies (4, f). Terry Pratchett.

99. A Lot Like Christmas (2, f). Connie Willis.

100. The Human Swarm: How Our Societies Arise, Thrive, and Fall (2, nf. Basic Books)

101. Mythos: The Greek Myths Retold (4, m). Stephen Fry.

102. Human Errors: A Panorama of Our Glitches, from Pointless Bones to Broken Genes (2, nf. Houghton Mifflin Harcourt). Goodreads review here.

103. A Guide to the Good Life: The Ancient Art of Stoic Joy (2, nf. Oxford University Press).

104. Heroes: Mortals and Monsters, Quests and Adventures (5, m). Stephen Fry. Very short goodreads review here.

105. Nation (4, f). Terry Pratchett.

Books I did not finish and which I don’t think I’ll finish next year:

The Anatomy of Melancholy (1, m). Robert Burton. Goodreads review here.

The Major Works of Samuel Johnson (3, f). “A mixed bag, not really worth reading from cover to cover in my opinion.” (from my goodreads review)

The Life of Samuel Johnson (m). James Boswell.

 

 

January 4, 2020 Posted by | Books, Personal | Leave a comment

Quotes

In recent months I have been reading both The Major Works of Samuel Johnson and The Life of Samuel Johnson, but to some extent I have neglected to keep track of my quotes; the Samuel Johnson quotes below are almost certainly all of them from one of those books, but which one of them? I don’t know, and I frankly don’t see any plausible scenario in which I would be justified spending the time and effort figuring it out (…I do however feel confident stating that most of the quotes below are from The Major Works…).

i. “Many complain of neglect who never tried to attract regard.” (Samuel Johnson)

ii. “It ought to be the first endeavour of a writer to distinguish nature from custom, or that which is established because it is right from that which is right only because it is established” (-ll-)

iii. “To fix the thoughts by writing, and subject them to frequent examinations and reviews, is the best method of enabling the mind to detect its own sophisms, and keep it on guard against the fallacies which it practises on others: in conversation we naturally diffuse our thoughts, and in writing we contract them; method is the excellence of writing, and unconstraint the grace of conversation. To read, write, and converse in due proportions is, therefore, the business of a man of letters.” (-ll-)

iv. “It were to be wished that they who devote their lives to study would at once believe nothing too great for their attainment, and consider nothing as too little for their regard” (-ll-)

v. “Nothing has so much exposed men of learning to contempt and ridicule as their ignorance of things which are known to all but themselves.” (-ll-)

vi. “He that can only converse upon questions about which only a small part of mankind has knowledge sufficient to make them curious must lose his days in unsocial silence, and live in the crowd of life without a companion.” (-ll-)

vii.“No degree of knowledge attainable by man is able to set him above the want of hourly assistance, or to extinguish the desire of fond endearments, and tender officiousness; and therefore no one should think it unnecessary to learn those arts by which friendship may be gained. Kindness is preserved by a constant reciprocation of benefits or interchange of pleasures; but such benefits can only be bestowed as others are capable to receive, and such pleasures only imparted as others are qualified to enjoy.

By this descent from the pinnacles of art no honour will be lost; for the condescensions of learning are always overpaid by gratitude.” (-ll-)

viii. “…the world cannot reward those qualities which are concealed from it” (-ll-)

ix. “…if we make the praise or blame of others the rule of our conduct, we shall be distracted by a boundless variety of irreconcilable judgments, be held in perpetual suspense between contrary impulses, and consult forever without determination.” (-ll-)

x. “… marriage is the strictest tie of perpetual friendship” (-ll-)

xi. “There is no doubt that being human is incredibly difficult and cannot be mastered in one lifetime.” (Terry Pratchett)

xii. “It’s difficult to say just where a marriage goes wrong, because the accepted reason often isn’t the real one.” (Dick Francis, Odds Against)

xiii. “Success depends on three things: who says it, what he says, how he says it; and of these three things, what he says is the least important.” (John Morley)

xiv. “Windbags can be right. Aphorists can be wrong. It is a tough world.” (James Fenton)

xv. “Here we must begin with the most fundamental fact about the impact of television on Americans: Nothing else in the twentieth century so rapidly and profoundly affected our leisure. In 1950 barely 10 percent of American homes had television sets, but by 1959, 90 percent did, probably the fastest diffusion of a technological innovation ever recorded. […] Time diaries show that husbands and wives spend three or four times as much time watching television together as they spend talking to each other, and six to seven times as much as they spend in community activities outside the home.” (Robert Putnam, Bowling Alone)

xvi. “We have changed the environment more quickly than we know how to change ourselves.” (Walter Lippmann, ibid.)

xvii. “If a lover is wretched who invokes kisses of which he knows not the flavor, a thousand times more wretched is he who has had a taste of the flavor and then had it denied him.” (Italo Calvino, The Nonexistent Knight)

xviii. “Where there is no bread, there is no philosophy.” (Avram Davidson, The Phoenix and the Mirror)

xi. “No one ever lacks a good reason for suicide.” (Cesare Pavese)

xx. “For the two or three years before she finally left us, Keiko had retreated into that bedroom, shutting us out of her life. She rarely came out, although I would sometimes hear her moving around the house after we had all gone to bed. I surmised that she spent her time reading magazines and listening to her radio. She had no friends, and the rest of us were forbidden entry into her room. At mealtimes I would leave her plate in the kitchen and she would come down to get it, then shut herself in again. […] I had to coax her to put out her laundry, and in this at least we reached an understanding: every few weeks I would find a bag of washing outside her door, which I would wash and return. In the end, the rest of us grew used to her ways, and when by some impulse Keiko ventured down into our living room, we would all feel a great tension. Invariably, these excursions would end with her fighting, with Niki or with my husband, and then she would be back in her room. I never saw Keiko’s room in Manchester, the room in which she died. It may seem morbid of a mother to have such thoughts, but on hearing of her suicide, the first thought that ran through my mind — before I registered even the shock — was to wonder how long she had been there like that before they had found her. She had lived amidst her own family without being seen for days on end; little hope she would be discovered quickly in a strange city where no one knew her. Later, the coroner said she had been there “for several days”. It was the landlady who had opened the door, thinking Keiko had left without paying the rent. I have found myself continually bringing to mind that picture — of my daughter hanging in her room for days on end. The horror of that image has never diminished, but it has long ceased to be a morbid matter; as with a wound on one’s own body, it is possible to develop an intimacy with the most disturbing of things.” (Kazuo Ishiguro, A Pale View of Hills)

November 23, 2019 Posted by | Books, Quotes/aphorisms | Leave a comment

Promoting the unknown…

i.

(I am grateful for you sharing this wonderful piece, SpewReeky!)

ii.

iii.

 

iv.

v.

November 1, 2019 Posted by | Music | Leave a comment

Quotes

i. “Experience is a dim lamp, which only lights the one who bears it.” (Louis-Ferdinand Céline)

ii. “The house of delusions is cheap to build, but draughty to live in, and ready at any instant to fall.” (A. E. Housman)

iii. “Three minutes’ thought would suffice to find this out; but thought is irksome and three minutes is a long time.” (-ll-)

iv. “Do not do an immoral thing for moral reasons!” (Thomas Hardy)

v. “The value of old age depends upon the person who reaches it. To some men of early performance it is useless. To others, who are late to develop, it just enables them to finish the job.” (-ll-)

vi. “Dying young is rarely worth it.” (James Thompson)

vii. “I have never thought there was much to be said in favor of dragging on long after all one’s friends were dead.” (Murasaki Shikibu)

viii. “A typical part of culture/social norms is the idea that it is very bad if people (have to) lie about X, should tell the truth about Y, should lie about Z and should not even believe A.

If you have internalized the surrounding (sub)culture and/or fit the (sub)culture so these restrictions don’t feel stifling, then you aren’t so much free, but rather: compatible. I think that most people have a hard time noticing restrictions that they are very comfortable with.

If you travel to a different (sub)culture that you are not compatible with and that feels oppressive to you, you will typically find people who don’t consider those restrictions to be stifling, but consider yours to be.” (Aapje, here)

ix. “I had a deprived childhood, you see. I had lots of other kids to play with and my parents bought me outdoor toys and refused to ill-treat me, so it never occurred to me to seek solitary consolation with a good book.” (Terry Pratchett)

x. “The destruction of the natural world is not the result of global capitalism, industrialisation, ‘Western civilisation’ or any flaw in human institutions. It is a consequence of the evolutionary success of an exceptionally rapacious primate. Throughout all of history and prehistory, human advance has coincided with ecological devastation.” (John Gray)

xi. “A lover who promises eternal fidelity is more likely to be believed if he believes his promise himself; he is no more likely to keep the promise.” (-ll-)

xii. “As commonly practised, philosophy is the attempt to find good reasons for conventional beliefs. In Kant’s time the creed of conventional people was Christian, now it is humanist. Nor are these two faiths so different from one another. Over the past 200 years, philosophy has shaken off Christian faith. It has not given up Christianity’s cardinal error — the belief that humans are radically different from all other animals.” (-ll-)

xiii. “There is no more consensus on what justice means than there is on the character of the good. If anything, there is less. Among the virtues, justice is one of the most shaped by convention. For that reason it is among the most changeable.” (-ll-)

xiv. “My friends are much more dangerous than my enemies. These latter – with infinite subtlety – spin webs to keep me out of places where I hate to go, – and tell stories of me to people whom it would be vanity and vexation to meet; – and they help me so much by their unconscious aid that I almost love them.” (Yakumo Koizumi)

xv. “He was too much concerned with his own perfection ever to think of admiring any one else.” (Max Beerbohm)

xvi. “The Socratic manner is not a game at which two can play.” (-ll-)

xvii. “Death cancels all engagements.” (-ll-)

xviii. “A crowd, proportionately to its size, magnifies all that in its units pertains to the emotions, and diminishes all that in them pertains to thought.” (-ll-)

xix. “Keeping up with the Joneses was a full-time job with my mother and father. It was not until many years later when I lived alone that I realized how much cheaper it was to drag the Joneses down to my level.” (Quentin Crisp)

xx. “Health consists of having the same diseases as one’s neighbours.” (-ll-)

October 24, 2019 Posted by | Quotes/aphorisms | Leave a comment

Designing Fast and Robust Learning Algorithms – Yu Cheng

Some links related to the lecture’s coverage:

Recommender system.
Collaborative filtering.
Matrix completion.
Non-Convex Matrix Completion Against a Semi-Random Adversary (Cheng & Ge, 2018).
Singular value decomposition.
Spectral graph theory.
Spectral Sparsification of Graphs (Spielman & Teng).
Cut (graph theory).
Split (graph theory).
Robust statistics.
Being Robust (in High Dimensions) Can Be Practical (Diakonikolas et al).
High-Dimensional Robust Mean Estimation in Nearly-Linear Time (Cheng, Diakonikolas and Ge).

October 13, 2019 Posted by | Computer science, Lectures, Mathematics, Statistics | Leave a comment

Data science (I?)

I’m not sure if I’ll actually blog this book in detail – I might, later on, but for now I’ll just cover it extremely lazily, by adding links to topics covered which I figured I wanted to include in this post.

The book is ‘okay’ – it’ll both allow (relatively) non-technical (management) people to at least begin to understand what sort of tasks the more technical guys are spending time on (and how to prioritize regarding critical resources, and engage with the nerds!), and it might also give the data guys a few more tools that they’ll be able to use when confronted with a specific issue. I really liked the book’s emphasis on conceptualizing data as a strategic asset. On the other hand I imagine some parts of the book will often be close to painful to read for people who have spent at least a few semesters dealing with stats-related topics in the past: This is the sort of book which is also at least in part written for people who might not be completely clear on what a statistical hypothesis test is, which discusses text mining without at any point in the coverage even mentioning the existence of regular expressions, and which discusses causal evaluation without mentioning topics like IV estimation.

Although there are some major gaps in the coverage the level of coverage is however not really all that bad; I hope to refer to at least some of the more technical material included in the book in my work in the future, but it’s not clear at this point how relevant this stuff’ll actually end up being long-term.

Links (…in random order, I did not have the book in front of me as I was writing this post so this is just a collection of links/topics I could recall being potentially worth including here):

Training, validation, and test sets
Cross-validation (statistics)
Statistical classification
Tree model
Decision tree pruning
Random forest
Naive Bayes classifier
Bigram
n-gram
Data mining
Zipf’s law (not covered, but relevant to some parts of the coverage)
Nearest neighbor search
K-nearest_neighbors_algorithm
Cluster analysis
Jaccard index
Bias–variance tradeoff
Hierarchical clustering
Dendrogram
Boosting (machine learning)
Ensemble learning
Feature (machine learning)
Feature selection
Curse of dimensionality
Regularization (mathematics)
Overfitting
Association rule learning
Labeled data
Dimensionality reduction
Supervised_learning/Unsupervised learning
Model selection
Rubin causal model (not covered, but relevant to some parts of the coverage)
Regression discontinuity design (-ll-)
Lift (data mining)
Receiver operating characteristic
Stepwise regression
Grid search (hyperparameter optimization).

October 4, 2019 Posted by | Books, Mathematics, Statistics | Leave a comment