128 Matching Annotations
  1. Feb 2026
    1. statistical knowledge is still required in order toformulate the correct prompts and to ensure that the AIdoes not leave out any step of the analysis.

      rhetoric: author presents a prescriptive claim that AI needs humans with competent knowledge (in this case, statistics) to create prompts and ensure that the AI does not leave out any steps of the analysis. He positions domain knowledge not as a tool for using AI for statistical analysis, but a prerequisite for management of the AI and auditing the output.

      inference: In addition to policing and correcting the AI outputs, the deep domain knowledge is what allows the AI to do complex data analysis without mistakes, hallucinated results, or mathematically false outcomes. This is basically the job description of a human with "Augmented Human Wisdom". The human's value is no longer in doing math, but in possessing the vertical expertise (flesh/wisdom) to know exact what math needs to be done and ultimately auditing the assistant machine's work.

    2. ChatGPT Data Analyst clearly produced a false resulthere, precisely because the application assumptions for theANOVA were not checked.

      rhetoric: Schwarz employs cause-and-effect reasoning here based on empirical testing. He links a specific technical failure (not checking assumptions) to a definitive unwanted outcome (a false result).

      inference: the "Data Analyst" function of ChatGPT hallucinated a result during the use of it's core function! This is the best evidence so far of the 'Crisis of Truth' and the dangers of the 'Headless Automatons' in my essay. If a generalist with no deep knowledge uses AI, they are at great risk of blindly accepting mathematically false conclusions. Synthetic syntax without competent human validation is a liability.

    3. The results show that generative AI canfacilitate data analysis for individuals with minimal knowledge of statistics,mainly by generating appropriate code, but only partly by following standardprocedures.

      rhetoric: author uses comparative, objective statement (logos) to establish the main boundary of the technology's capability/capacity -- it excels at technical generation (things like coding) but fails at standard procedures (methodological adherence to SOPs).

      inference: the proves the 'Raising the Floor' concept. AI completely automates the entry-level syntax (the "Word"), meaning that the Generalist coder is obsolete! However, because it fails at standard procedures, it requires a human architect to guide it to outputs that are valuable in the real world.

    1. Perseverations that are input into the system are essentially mag-nified by the system’s suggested sentences,

      rhetoric: authors explain an unintended consequence of using the AI tool: it scales the errors or the emptiness of the human prompt.

      inference: this is an excellent metaphor for the 'manager fallacy'. If the human user in incompetent (or provides empty or incomplete input), the AI does not magically create wisdom -- it just amplifies the user's incompetence in a a highly articulate synthetic thought.

    2. Participant 2 stated the age of her daughters (“Name1 is 18, Name2 is21”), Aphasia-GPT transformed it as “Name1 is 18 and 21”, which is an impossible, butrelated, hallucination

      rhetoric: researchers use a specific, clinical observation of an error to demonstrate the model's inability to comprehend logical reality despite the human relaying a perfectly structured sentence.

      inference: this shows that AI is amoral and lacks the lived experience necessary to make logical judgments that work in the real world. It can format a sentence beautifully, but it does not/will not always understand that a single human cannot be two ages at once. This is why it is very important/necessary for the "flesh" to text the output against reality

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    1. The cost of the time that it takes fix "workslop" could add up too, with a $186 monthly cost per employee on average, according to a survey of desk workers by BetterUp in partnership with the Stanford Social Media Lab. Forty percent of the workers surveyed said they received "workslop" in the last month and that it took an average of two hours to resolve each incident.

      $186/per employee/per month!

      10 employees = ($22,320) 25 employees = ($55,800) 50 employees = ($111,600) 100 employees = ($223,200) 250 employees = ($558,000) 500 employees = ($1,116,000) 1000 employees = ($2,232,000)

    2. “Younger workers aren’t necessarily more careless, but they’re often using AI more frequently and earlier in their workflows," Dennison said. "There is also a training gap. Organizations often assume younger employees intuitively understand AI, yet provide little guidance on verification, risk, or appropriate use cases. As a result, AI may be treated as an answer engine rather than a support tool."

      this is another great quote, which helps to establish how orgs treat younger generations, and how they tend to overtrust their understanding of AI.

    3. 58% said direct reports submitted work that contained factual inaccuracies generated by AI tools, while fewer reported that AI failed to account for critical contextual factors. Other issues cited include low-quality content, poor recommendations and inappropriate messaging.

      from reporting managers, 58% of them said that employees were submitting work that contained factual inaccuracies in the work that was generated by AI, and that fewer of them reported that AI failed to account for "critical contextual factors", implying that the writing was generic and not directly applicable to the context that the writing was written in. Other issues were: low quality content, poor recommendations and inappropriate messaging.

    4. 59% of managers saying that they had to invest additional time to correct or redo work created by AI. Similarly, 53% said their direct reports had to take on extra work, while 45% said they had to bring in co-workers to help fix the mistake.

      Extra time and money spent to repair errors made by AI but not caught by the human in the middle. 59% is almost 2/3 (closer to 3/5) needed to correct or redo the work created by AI without a human auditing it. 53% claim extra work is needed to repair the AI mistakes, and 45% also needed to bring in a (perhaps more senior) co-worker to help fix the mistake. I can imagine workers needing to work on a mistake the hits production code, and all of the thousands (or more) mistakes that would need to be later repaired and rolled back. very expensive and costly.

    5. While 18% of managers said they did not suffer any financial losses from the mistakes, and 20% said those losses were less than $1,000, a significant number reported bigger losses. Twelve percent said those losses were more than $25,000, while 11% said between $10,000 and $24,999. Another 27% placed the value of those losses above $1,000 but below $10,000.

      great stats for the cost of using AI without human auditing.

    6. “AI is reliable when used as an assistant, not a decision-maker," Dennison said. "Without human judgment and clear processes, speed becomes a risk, and efficiency gains can turn into costly mistakes,”

      great quote. directly mentions my concept of requiring human judgement, and how not having a human in the loop can make work move faster, but can also lead to very costly mistakes.

    7. “Employees treat AI outputs as finished work rather than as a starting point. Current AI tools are very good at generating fluent content, but they don’t understand context, business nuance, risk, or consequences. That gap shows up in factual errors, missing constraints, poor judgment calls, and tone misalignment.”

      another great quote -- ties into the abdicating human agency to a robot, and the full quote even illustrates the dangers of doing so.

  2. Dec 2025
  3. Apr 2025
  4. Feb 2025
    1. Back in the day people used custom erasers for erasing. They were much harder than the softer erasers in use now, which is why modern pencil and art erasers don't work as well. For some historical methods, see these videos or here.

      Secretaries also used small eraser shields to target individual letters, words, or lines. They also used larger curved shields for erasing within carbon copy packs.

      Eaton used to make Ko-rec-type tabs which could be inserted for short corrections and it can still be found online as old stock.

      There was also bichrome ribbon with white correction tape, but that tends to fleck off and make a mess in your machine over time. Similarly White Out is still made, but it can spill and make a mess while you wait for it to dry.

      For modern typists, hand-held correction tape is probably the quickest and easiest.


      This could be expanded for the widest range of history on erasing using typewriters with caveats, etc.

      reply to u/Fearless_Camera_1788 at https://old.reddit.com/r/typewriters/comments/1ixmz88/how_to_erase/

  5. Nov 2024
    1. we now realize the base pairs come to join each other up together as the system unravels and forms a new pair of DNA molecules well up to a point it does and that point is known to be accurate to about one in 10,000 base pairs now if you and I wrote an article and there was only one typo in a 10,000w article we'd be very pleased but this is nowhere near enough for a DNA sequence of three billion base pairs there would be half a million at least of Errors

      for - DNA replication accuracy - 1 in 10,000 - too high for successful replication - another higher level mechanism to correct for these errors - need a whole body for that - Denis Noble

  6. Sep 2024
    1. IEP Process: Common Errors

      “fixes” to ensure you don’t make these errors

      I studied a case involving Child find, Referral & Evaluation. The details of the case are: 23 IDELR 411, 23 LRP 3306, W.B., Parent of the Minor, E.J., on her own behalf and on behalf of her son, E.J., Appellants v. Joan Matula; Mary Angela Engelhardt; Judy Beach; Catherine Brennan; Patricia Cericola; Dr. Gary Danielson; Ann Pearce; Kathleen Mahony; Carol Burns; Florence Noctor; Dr. Jeffrey Osowski; New Jersey State Board of Education; Warren County Department of Education; Mary Lou Varley; Mansfield Board of Education; State of New Jersey, Department of Education Division of Special Education; Employees of the Mansfield Township Board of Education, Appellees, 67 F.3d 484, U.S. Court of Appeals, Third Circuit, 95-5033, October 17, 1995 deals with a case related to Child Find, Referral and Evaluation related to IDEA, FAPE, Section 504, and NJ State rules implementing IDEA. This is an appeal of a lower court (Administrative Law Judge) judgment for a case filed when the parent is not satisfied with school boards processes and conclusions of her son’s Child Find, Referral and Evaluation. It is a complex case.

      In my analysis of an earlier case, I expressed my fear that as a special education teacher and a member of the IEP team of our school, I could potentially be a defendant in a similar case. Strangely this is such a case. Several teachers including 1st grade teacher Mary Angela Engelhardt and 2nd grade teacher were defendants in this case. This should serve as a warning to all the teachers that they should adhere to the IDEA. The court in its scathing indictment specifically signaled teacher Mary Angela Engelhardt and wrote:

      “This decision would not be complete without a comment on Mansfield's seemingly endless attacks on the parent, W.B. Evidently, Mansfield believes not only that W.B. is overly persistent, but also that she is trying to wear down the district to obtain services to which E.J. is not entitled. In my view, however, W.B. was essentially correct about the major points in dispute in these proceedings including evaluation, classification and placement. Nonetheless, the district has consistently denied W.B.'s reasonable, appropriate, and meritorious requests related to E.J.'s education. The basic dynamic of this entire dispute is that the district has denied W.B.'s meritorious requests and W.B. has been left with no alternative to an enormously burdensome struggle in order to obtain E.J.'s rights under IDEA. In my view, the burden placed on W.B. was unnecessary, unwarranted and largely the product of the district's unwillingness to recognize and appreciate E.J.'s neurological impairments despite ample reliable evidence thereof.”

      Another point that caught my attention is the willful dragging of their feet by the school officials and lower courts routinely (2:1) siding with the school districts. The judgment states:

      “As to classification, despite the findings of the independent evaluation, in November the CST concluded that E.J. was perceptually impaired but not neurologically impaired. The distinction is important, because the former classification would result in a lower level of IDEA services for E.J. than the latter. W.B. attempted to persuade the school to reclassify her son as neurologically impaired, and in December 1992, Mansfield cross-petitioned to have E.J. classified as perceptually impaired.”

  7. Mar 2024
  8. Feb 2024
  9. Jan 2024
    1. Accuracy of the slide rule. From thediscussion of § 2 it appears that we read fourfigures of a result on one part of the scaleand three figures on the remaining part.Assuming that the error of a reading is onetenth of the smallest interval following theleft-hand index of D, we conclude that theerror is roughly 1 in 1000 or one tenth of oneper cent. The effect of the assumed errorin judging a distance is inversely propor-tional to the length of the rule. Hencewe associate with a 10-inch slide rule anerror of one tenth of one per cent, with a20-inch slide rule an error of one twentiethof one per cent or 1 part in 2000, and withthe Thacher Cylindrical slide rule an errorof a hundredth of one per cent or one part.in 10,000. The accuracy obtainable withthe 10-inch slide rule is sufficient for manypractical purposes; in any ease the sliderule result serves as a check.

      The accuracy of most 10 inch slide rules is approximately 1 in 1000 or one tenth of one percent.

      Because the error in approximating distance is inversely proportion to the length of a slide rule, longer slide rules will have proportionally smaller errors, so while a 10 inch slide rule has an error of 1 in 1000, a 20 inch will have an error of 1 in 2000 and larger rules can be accurate to within 1 in 10,000 or better.

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  10. Dec 2023
    1. There are common errors experienced by beginners when getting started with asyncio in Python.

      They are:

      1. Trying to run coroutines by calling them.
      2. Not letting coroutines run in the event loop.
      3. Using the asyncio low-level API.
      4. Exiting the main coroutine too early.
      5. Assuming race conditions and deadlocks are impossible.
    1. next stage is parsing (also known as syntactic analysis) and the parser reports the first error in the source code. Parsing the whole file happens before running the first line of code which means that Python does not even see the error on line 1 and reports the syntax error on line 2.
    2. I haven’t done a deep dive into the source code of the CPython interpreter to verify this, but I think the reason that this is the first error detected is because one of the first steps that Python 3.12 does is scanning (also known as lexical analysis). The scanner converts the ENTIRE file into a series of tokens before continuing to the next stage. A missing quotation mark at the end of a string literal is an error that is detected by the scanner—the scanner wants to turn the ENTIRE string into one big token, but it can’t do that until it finds the closing quotation mark. The scanner runs first, before anything else in Python 3.12, hence why this is the first error message.
    3. Python reports only one error message at a time—so the game is which error message will be reported first?

      Here is the buggy program:

      python 1 / 0 print() = None if False ñ = "hello

      Each line of code generates a different error message:

      • 1 / 0 will generate ZeroDivisionError: division by zero.
      • print() = None will generate SyntaxError: cannot assign to function call.
      • if False will generate SyntaxError: expected ':'.
      • ñ = "hello will generate SyntaxError: EOL while scanning string literal.

      The question is… which will be reported first?

      Spoilers: the specific version of Python matters (more than I thought it would) so keep that in mind if you see different results.

      The first error message detected is on the last line of source code. What this tells us is that Python must read the entire source code file before running the first line of code. If you have a definition in your head of an “interpreted language” that includes “interpreted languages run the code one line at a time”, then I want you to cross that out!

    4. The fact that error messages are generated by different stages of the compiler, and compilers generally issue errors from earlier stages before continuing also means that you can discover the stages of your compiler by deliberately creating errors in a program.
      • for: social tipping point, STP, social tipping point - misapplication, social tipping points - 4 application errors

      • title: Social tipping points everywhere?—Patterns and risks of overuse

      • author: Manjana Miikoreit
      • date: Nov 17, 2022

      • abstract

        • The last few years have witnessed an explosion of interest in the concept of social tipping points (STPs),
          • understood as nonlinear processes of transformative change in social systems.
        • A growing body of interdisciplinary scholarship has been focusing in particular on social tipping related to climate change.
        • In contrast with tipping point studies in the natural sciences–for example
          • climate tipping points and
          • ecological regime shifts–
        • STPs are often conceptualized as desirable, offering potential solutions to pressing problems.
        • Drawing on
          • a well-established definition for tipping points, and
          • a qualitative review of articles that explicitly treat social tipping points as potential solutions to climate change,
        • this article identifies four deleterious patterns in the application of the STP concept in this recent wave of research on nonlinear social change:
          • (i) premature labeling,
          • (ii) not defining system boundaries and scales of analysis,
          • (iii) not providing evidence for all characteristics of tipping processes, and
          • (iv) not making use of existing social theories of change.
        • Jointly, these patterns create a trend of overusing the concept.
        • Recognizing and avoiding these patterns of “seeing the world through tipping point glasses” is important for
          • the quality of scientific knowledge generated in this young field of inquiry and for
          • future science-policy interactions related to climate change.
        • Future research should seek to
          • identify empirical evidence for STPs while remaining open to the possibility that
            • many social change processes are not instances of tipping, or that
            • certain systems might not be prone to nonlinear change.
  11. Nov 2023
    1. Why do Direct Leaders decentralize when they issue a token? Decentralization imposes costs on an organization — decisions are made more slowly by lower context people who are not held accountable for bad decisions — this is why companies don’t operate this way. These costs are being felt across the industry. Kevin Owocki, who left as Direct Leader of Gitcoin to later return, described a broader trend of “founders boomeranging” back into leadership to solve the organizational dysfunction caused by decentralization. As the impetus for governance changes, Rune Christensen wrote of MakerDAO in 2022, “The governance processes and political dynamics… fundamentally aren’t compatible with the reality of effectively processing complicated real-world financial deals.”

      Just keep relearning the lessons of a 1000 years of governance experiments.

      People have been trying decentralized governance for a really long time and it's really hard. Progress does not depend on structural innovation, duh! It depends mostly on ontological/cultural innovation (e.g. "god is watching" aka the internalized morality of e.g. late christian religion) with some amount of increased monitoring and transparency ...

  12. Aug 2023
    1. CAUTION:

      The slice_plot() function is not in the stable MosaicCalc package but in a beta. Given the terribly cumbersome compilation of packages in R the best is to use an R base alternaive,

      For functions a good one is curve(),

      curve(expr = FUNCTION, from = A, to = B)

      for instance: fx <- makeFun(x^2 ~ x)

      curve(expr = fx, from = -10, to = 10)

  13. Mar 2023
    1. TheCalculagraph

      Beyond having people make direct copies of cards by hand or using carbon paper, The Calculagraph Company manufactured a copying machine for duplicating data.

      There is an accompanying picture (which I haven't copied here). Advertisement from 1906 System Magazine:

      The Calculagraph<br /> Makes individual records of actual<br /> working time on separate cards<br /> which may be used interchangeably<br /> for Cost Accounting, for Pay-rolls and<br /> for a number of other purposes with-<br /> out copying or transcribing a single<br /> figure, by simply assorting the cards<br /> and adding the records directly from<br /> their faces.<br /> A card containing all the work<br /> records of one man for a week may<br /> be useful for pay-roll purposes, but it<br /> is utterly worthless for learning the<br /> cost of products, until all the items<br /> have been copied or transcribed for<br /> classification.<br /> The Calculagraph requires a large<br /> number of cards in a factory employ-<br /> ing several hundred persons, but it<br /> Saves Clerical Labor. (In one<br /> factory it saves $150.00 per week).<br /> Cards Are Cheaper Than Labor<br /> The Calculagraph Makes No<br /> Clerical Errors.<br /> Let us send you our printed matter.<br /> CALCULAGRAPH COMPANY<br /> 1414 JEWELERS BUILDING, NEW YORK CITY

  14. Feb 2023
  15. Jan 2023
    1. Transcriptions taken from Goitein’s publications were corrected according to handwrittennotes on his private offprints. The nature of Goitein’s “typed texts” is as follows. Goitein tran-scribed Geniza documents by hand from the originals or from photostats. These handwrittentranscriptions were later typed by an assistant and usually corrected by Goitein. When Goiteindied in 1985, the transcriptions were photocopied in Princeton before the originals were sentto the National Library of Israel, where they can be consulted today. During the followingdecades, the contents of most of these photocopies were entered into a computer, and period-ically the files had to be converted to newer digital formats. The outcome of these repeatedprocesses of copying and conversion is that transcription errors and format glitches are to beexpected. As the Princeton Geniza Project website states: “Goitein considered his typed texts‘drafts’ and always restudied the manuscripts and made revisions to his transcriptions beforepublishing them.” See also Goitein, “Involvement in Geniza Research,” 143. It is important tokeep in mind that only the transcriptions that were typed were uploaded to the project website.Therefore, e.g., Goitein’s transcriptions of documents in Arabic scripts are usually not foundthere. The National Library of Israel and the Princeton Geniza Lab also hold many of Goitein’sdraft English translations of Geniza documents, many of which were intended for his plannedanthology of Geniza texts in translation, Mediterranean People.

      Much like earlier scribal errors, there are textual errors inserted into digitization projects which may have gone from documentary originals, into handwritten (translated) copies, which then were copied manually via typewriter, and then copied again into some digital form, and then changed again into other digital forms as digital formats changed.

      As a result it is often fruitful to be able to compare the various versions to see the sorts of errors which each level of copying can introduce. One might suppose that textual errors were only common when done by scribes using manual techniques, but it is just as likely for errors to be inserted between digital copies as well.

  16. Dec 2022
    1. Can't annotate on https://feedback.mailgun.com/forums/156243-feature-requests/suggestions/39905227-provide-meaningful-delivery-status-description-rat so posting here instead.

      Anonymous commented · May 26, 2021 4:36 AM

      Without your comment I'd never find the real issue, because I was only look at permanent failures. That error message is really misleading, hope they can fix this.

      Kelly commented · December 30, 2020 2:35 AM

      Yes we desperately need this too. Half of our recipients were soft bounced due to "Too old" but we could still send to them previously on other ESPs.

  17. Nov 2022
  18. Apr 2022
    1. Zeitwerk raises Zeitwerk::UnsynchronizedReloadError if any of these situations are detected. This is a fatal exception that signals a fundamental bug, you cannot rescue it and expect things to work.
    1. In her 2002 dissertation, and then in a series of articles published in medicaljournals, Pape made a case for imitating this practice. “The key to preventingmedication errors lies with adopting protocols from other safety-focusedindustries,” Pape wrote in the journal MEDSURG Nursing in 2003. “The airlineindustry, for example, has methods in place that improve pilots’ focus andprovide a milieu of safety when human life is at stake.”

      In a 2002 dissertation and subsequent articles, Tess Pape proposed imitating solutions proposed by the FAA in airline accidents as a means of limiting distractions during medicine dispensing by nurses and medical staff to limit preventable medical errors.

    2. the Institute of Medicine had released a landmark report on patientsafety, To Err Is Human. The report found that as many as 98,000 Americanswere dying each year as a result of preventable medical errors occurring inhospitals—more people than succumbed to car accidents, workplace injuries, orbreast cancer. And some significant portion of these deaths involved mistakes inthe dispensing of drugs.

      Some might see the 98,000 preventable medical error deaths reported by the Institute of Medicine in To Err is Human (1999) now and laugh at the farcical number of deaths due to coronavirus since 2020, a large proportion of which could have been prevented due to better communication and coordination?

      What if a more pragmatic anthropological viewpoint could be given to the current fractured state of American politics? If anthropologists are taught not to make value judgements on the way other cultures have come to live their lives, but simply to appreciate and report on them accurately, then perhaps we should leave those on the far right who believe in top down, patriarchal rule to their devices?

      What if we nudged (forced) them all to actually live by their own rules by enforcing them to the nth degree? Republican politicians can only get away with badmouthing abortion or homophobic viewpoints because their feet are not held to the fire when those issues impinge upon their own families or even themselves. They have the wealth and the power to flout the laws and not face the direct consequences personally. Would their tunes change if forced by their own top down patriarchal perspectives applying to them?

    1. She frequently cites authors second-hand(“as quoted by”, “see,” etc.) rather than primary texts, and in some instancesthis practice results in the kinds of errors for which earlier compilations werecriticized. The most egregious of these occurs when Blair cites Ann Moss on

      Guarino da Verona when making the unlikely claim that note taking begin in earnest with Francesco Sacchini in the seventeenth century rather than a hundred years earlier with Erasmus and Vives.

      I almost feel like I've arrived as I noticed this error in the text myself.

      Interesting that he calls her out for making a compilation error, something which is very meta with respect to this particular text.

  19. Mar 2022
  20. Feb 2022
  21. Jan 2022
    1. But Google also uses optical character recognition to produce a second version, for its search engine to use, and this double process has some quirks. In a scriptorium lit by the sun, a scribe could mistakenly transcribe a “u” as an “n,” or vice versa. Curiously, the computer makes the same mistake. If you enter qualitas—an important term in medieval philosophy—into Google Book Search, you’ll find almost two thousand appearances. But if you enter “qnalitas” you’ll be rewarded with more than five hundred references that you wouldn’t necessarily have found.

      I wonder how much Captcha technology may have helped to remedy this in the intervening years?

  22. Dec 2021
    1. digital methodo collect

      I am unsure what this is and assume it is an error? If this is an error that seems odd that no-one was checking this as it is important information about how our data is used and gathered. If there are errors here, how can we be assured that our data is safe?

  23. Oct 2021
  24. Aug 2021
  25. developer.mozilla.org developer.mozilla.org
  26. Jun 2021
    1. In general, top-level errors should only be used for exceptional circumstances when a developer should be made aware that the system had some kind of problem. For example, the GraphQL specification says that when a non-null field returns nil, an error should be added to the "errors" key. This kind of error is not recoverable by the client. Instead, something on the server should be fixed to handle this case. When you want to notify a client some kind of recoverable issue, consider making error messages part of the schema, for example, as in mutation errors.
  27. May 2021
    1. If you are working on a codebase within which you lint non-TypeScript code (i.e. .js/.jsx), you should ensure that you should use ESLint overrides to only enable the rule on .ts/.tsx files. If you don't, then you will get unfixable lint errors reported within .js/.jsx files.
  28. Apr 2021
    1. Already Signed InThis session has ended because the account has been signed into from another browser window on 04/11/2021 04:30:09 PM. This happens when you sign in to your account on more than one browser screen. You can't be signed into your account on two or more browser windows at the same time. Just close your browser and sign back into your account.
  29. Mar 2021
  30. Feb 2021
  31. Jan 2021
  32. Dec 2020
  33. Nov 2020
  34. Oct 2020
  35. Sep 2020
    1. using modulesOnly behaves exactly as expected when it warns you that the listed npm libraries do not use the ES6 format and are in fact ignored. This option is meant as a way to determine if you still have commonjs libraries in your dependencies that require special treatment via rollup-plugin-commonjs. Your code will probably not work since the listed dependencies will be missing. You should remove modulesOnly and instead add rollup-plugin-commonjs.
  36. Aug 2020
    1. A category mistake, or category error, or categorical mistake, or mistake of category, is a semantic or ontological error in which things belonging to a particular category are presented as if they belong to a different category,[1] or, alternatively, a property is ascribed to a thing that could not possibly have that property.
    1. In discussing the appeal of the News Feed in that same interview with Kirkpatrick, Zuckerberg observed, “A squirrel dying in front of your house may be more relevant to your interests right now than people dying in Africa.” The statement is grotesque not because it’s false — it’s completely true — but because it’s a category error. It yokes together in an obscene comparison two events of radically different scale and import. And yet, in his tone-deaf way, Zuckerberg managed to express the reality of content collapse. When it comes to information, social media renders category errors obsolete.

      How can we minimize this sort of bias? How can we help to increase the importance of truly important things?

  37. Jul 2020
  38. May 2020
  39. Jan 2020
  40. Oct 2019
  41. Aug 2019
  42. Apr 2019
    1. Our culture is defined by the music we listen to, and the way it is portrayed in the media. Every culture around the world has a different style of song or dance that represents their traditions. Culture can not only be changed through popular songs, but is best represented through music. One of the best ways to understand a foreign culture is by listening to the music that is favorable among the people whose culture you are trying to understand. Music is one of the most powerful forms of art between cultures.

      Music has the power to redefine cultures. We can see this through generational differences between song preferences. For example, American country music back in the late 1900s has a much different feel and style compared to country music now in 2019. While keeping within the same genre, this style of music touches upon different subjects, and uses different instruments, sounds and lyrics. Even early hip-hop has evolved from its beginnings. Hip-hop music is considered the most popular music as of right now, but it has not always been that way. Each generation favors different types of genres of music, and it is clear which backgrounds over the years have favored certain genres of music. As much as music can differentiate cultures, and generations, music can bring people of completely different background together by its artistic flavor and general popularity throughout the mainstream media.

  43. May 2017
  44. Apr 2017
  45. Mar 2017
  46. Jan 2017
  47. Sep 2016
  48. Aug 2016