In the case example that you linked, I find it disappointing that you still do not read entire threads. The original article is a Wikipedia article with many authors. The original comment, which critiques either Wikipedia or Baumol & Bowen's original study, includes the summary:

> So - this is simply a bad, ignorant example. It's not just wrong, it's flagrantly, wildly, outrageously misinformed, and is based on an almost total lack of insight into an industry that is worth $146 million a year - of which around $90 million is income from streaming.

My comment concludes with the line:

> This is a bad, ignorant example. Not just wrong, but flagrantly, wildly, outrageously misinformed.

I understand that you object to when we (those who know of the Prime Directive) hold a mirror up to HN. It is embarrassing to imagine how other people must see us, knowing how we see other people. However, that does not mean that we should stop looking at ourselves in the mirror.

Oh, and finally, have a happy Halloween.

Comments URL: https://news.ycombinator.com/item?id=24826124

Points: 1

# Comments: 0

It is not a problem for a creature to live for a long time; the inevitability of cancer seems to itself be genetic and part of the human experience but not for all life. You mention whales, but lobsters are even more interesting: They do manufacture telomerase throughout their lives, and they are not killed by cancer in old age, but by being unable to molt and continue growing. Trees are interesting too; they must always grow in order to keep living, but past a certain size, the physics of water limits their ability to grow.

Indeed, if we want to understand trees and whales, my first guideline would be that, because they are so large, the rules for cellular homeostasis are different at that scale. The things which allow us or lobsters to live for long times are not the things which allow whales or trees to live for long times.

This is a bad, ignorant example. Not just wrong, but flagrantly, wildly, outrageously misinformed.

The weakest forms of Sapir-Whorf are obviously true, via Zipf's law; being able to shorten long phrases into short nonce words allows for faster communication, which allows for normalization of concepts, in a positive feedback loop. In English, for example, it's no accident that the shortest two words are "a" and "I" and that they are also the most two common ways to refer to things; "u" is on the way there, too!

Unsure how Aeon is doing this; some sort of URL trickery?

I assume that you know about the facts that some humans have fewer than two arms, and some humans have not just fewer than five, but also sometimes more than five fingers [0]. In what way, then, do you hope to show that the facile versions aren't wrong? I think that what you're saying is that it is quite common for human genetics to plan for people to have two arms and five fingers. But it's not universal. We must distinguish between the two, because every time we make a universal claim about humans, we implicitly exclude the humans who aren't covered by the claim. Indeed, intersex folk, polydactyls, amputees, and folks with Down syndrome are all marginalized in our society, and all via this same mechanism of minimization and normalization.

On personal attacks: I've only lost karma in this thread and I'm going to continue losing it; I'm not sure by what means you could imagine that I'm effectively winning.

[0] https://en.wikipedia.org/wiki/Polydactyly

* Perl 5 to Perl 6: So disastrous that they rolled back and Perl 6 is now known as Raku

* PHP5 to PHP7: Burn my eyes out, please! But of course PHP has unique user pressures, and a monoculture helps a lot

* Python 2.4 to Python 2.7: Done in several stages, including deprecation of syntax, rolling out of new keywords, introduction of backwards-compatible objects and classes, and improvements to various semantic corner cases

* Haskell 98 to Haskell 2010: GHC dominated the ecosystem and now Haskell 98 is only known for being associated with Hugs, which knows nothing newer

* C++03 and earlier to C++11: Failed to deprecate enough stuff, but did successfully establish a permanent 3yr release cadence

* C99 to C11: Aside from the whole Microsoft deal, this was perfect; unfortunately Microsoft's platforms are common in the wild

Now consider how many Python 3 features ended up backported to Python 2 [0] and how divisive the upgrade needed to be in the end.

On readability, you'll just have to trust me that when Python gets to millions of lines of code per application, the organization of modules into packages becomes obligatory; the module-to-module barrier isn't expressive enough to support all of the readable syntax that people want to use for composing objects. If you want a FORTRAN example, look at Cephes [1], a C library partially ported from FORTRAN. The readability is terrible, the factoring is terrible, and it cannot be improved because FORTRAN lacked the abstractive power necessary for higher-order factoring, and so does C. Compare and contrast with Numpy [2], a popular numeric library for Python which is implemented in (punchline!) FORTRAN and C.

[0] https://docs.python.org/2/whatsnew/2.7.html#python-3-1-featu...

[1] https://github.com/jeremybarnes/cephes

[2] https://github.com/numpy/numpy

> stating that the biological sex exists and in human case there are two sexes is sexist.

You got it! Sort of. It's not a problem to use the concept of biological sex, but it's completely wrong to say that humans have two biological sexes. The main problem is in the assignment of chromosomal configurations to sexual configurations; humans have a dozen or so intersex [0] configurations which don't fit neatly into binary gender theory.

And this has real-world consequences. There are many countries which have canonicalized various sorts of human-rights abuses based on the binary theory, mostly by establishing some sort of concentration camps for homosexuals. The author's writing forms a small but real brick in the wall of these camps.

> If that's so then the most biologists I've met are jest sexists and I should probably call the police and denounce them as petty criminals.

This is the error. It doesn't make sense to criminalize sexism, and indeed it's not criminalized in any jurisdiction that I know of. Instead, what's criminalized are specific deleterious pragmatic aspects of sexism: Sexual harassment, genital mutilation, conversion therapy, forced emancipation of trans children, human trafficking. When biologists are sexists, they are usually being reductionist as the author is doing, by minimizing and ignoring the diversity of the real world's biosphere; they are not directly advocating for the harm that is done by other, more hateful people, based on their reasoning.

Also, yes, my priors are that people are 99% racist, 80% sexist, 85% delusionally religious, and 20% fascist; this gives me a weak but steady belief that the typical person I talk to is, in some way, a sincere believer in deeply harmful and falsifiable cultural beliefs. I'm in the USA, for what it's worth; hopefully it's not like this everywhere.

[0] https://en.wikipedia.org/wiki/Intersex

First, the excellent readability leads directly into hard-to-read code structures. This might seem paradoxical but Dijkstra insisted that the same thing happened in FORTRAN, and I'm willing to defer to his instinct that there's something about the "shut up and calculate" approach that physicists have which causes a predilection for both FORTRAN and Python.

Second, Python 2 to Python 3 was horrible, and created political problems which hadn't existed before. Now, at the end of the transition, we can see how badly it was managed; Python 2 could have been retrofitted with nearly every breaking change and it would have been lower-friction. Instead, there's now millions of lines of rotting Python 2 code which will never be updated again. Curiously, this happened in the FORTRAN world too; I wasn't around for it, but FORTRAN 77 was so popular compared to future revisions and standardizations that it fractured the FORTRAN community.

> Telomeres, the caps on the ends of eukaryotic chromosomes, play critical roles in cellular aging and cancer.

On war, we lose millions of people regularly [4]. We lose about a million people to genocide every year [5]. These are people that, in Bostrom's parlance, we have put on the train to go see the dragon; we sacrificed them for nothing at all. Nothing in Bostrom's tale suggests that, having defeated the dragon, we will stop killing millions of people.

On nuclear war or other disastrous climate change, something you only allude to, the Doomsday Clock [6] is currently at less than two minutes to midnight, and has never been closer. It is widely agreed that we are on the very edge of self-annihilation and that we expend a tremendous amount of political effort simply not destroying ourselves.

I can see that you're a relatively young and inexperienced account; I hope that you do some reading and improve your understanding of biology and history, rather than continuing to lean on mystic or mythic influences for your worldview.

[0] https://en.wikipedia.org/wiki/Cancer

[1] https://en.wikipedia.org/wiki/Carcinogenesis

[2] https://en.wikipedia.org/wiki/Telomere

[3] https://en.wikipedia.org/wiki/Telomeres_in_the_cell_cycle

[4] https://en.wikipedia.org/wiki/List_of_wars_by_death_toll

[5] https://en.wikipedia.org/wiki/Genocide

[6] https://en.wikipedia.org/wiki/Doomsday_Clock

Sibling comments are completely correct. Graphics simulations often require quasirandom sequences; the particular sequence is not important, but any correlations in the sequence will be visible in the output as artifacts, so we want a decorrelated sequence.

If this is not enough of a real-world example for you, then Monte Carlo methods also show up in weather modeling, financial planning, and election forecasting. In those predictive systems, there is extreme uncertainty and dependence on initial conditions, which we model with quasirandom sequences and seed numbers respectively. By running many simulations with different random sequences and then examining all of the results statistically, we can get good estimates of future behavior.

Edit: Oh, you're not in good faith. Okay, cool story. Best of luck with whatever imaginary idea of "unpredictability" you're trying to define, but you might want to return to actual maths at some point.

In the classic video game "Link's Awakening" (chosen to fit the article's theme), there is a maze of signs. Each sign points towards another sign. Reading the signs in the order that they point to each other, following the chain of arrows, leads to a prize. The player is local and does not know where the prize is, but the signs encode global information about the maze. The player's memory is limited and can only remember one sign at a time, but that is sufficient. It seems to me that cells communicate and act using similar local/global distinctions.

> We reject a simplistic essentialism where humans have ‘real’ goals, and everything else has only metaphorical ‘as if’ goals.

This is the philosophical meat of the article, and the tough takeaway for the reader. The reader must admit that their own goals, since they are human, are not quite "real" in a way which somehow transcends the accidental success of blindly-evolving low-level components. Rather, humans do the same sort of predictive modeling, blind guessing, and lucky incidence that we see in "simpler" life forms.

That said, he did have relatively nice things to say about Haskell [2] and preferred Haskell to Java:

> Finally, in the specific comparison of Haskell versus Java, Haskell, though not perfect, is of a quality that is several orders of magnitude higher than Java, which is a mess (and needed an extensive advertizing campaign and aggressive salesmanship for its commercial acceptance).

I imagine that he would have liked something structured, equational, declarative, and modular; he would have wanted to treat programs as mathematical objects, as he says in [2]. Beyond that, though, we'll never know. He left some predictions like [3] but they are vague.

[0] https://en.wikipedia.org/wiki/ALGOL_60

[1] https://www.cs.utexas.edu/users/EWD/MCReps/MR35.PDF

[2] https://www.cs.utexas.edu/users/EWD/transcriptions/OtherDocs...

[3] https://www.cs.utexas.edu/users/EWD/transcriptions/EWD12xx/E...

Bostrom brings us "fine phrases and hollow rhetoric," mostly. Sure, we should do something about aging, but what, exactly, are we failing to do as a society here? He seems to think that the problem is that we're treating aging and death as inevitable, but science already has marched past that position; instead, we now know that aging is part of a tradeoff involving cancer and is closely tied to maintenance of DNA as cells reproduce in multicellular organisms.

Further, the notion of agency is hopelessly confused by the design of the fable. Humans are deliberately sending other humans to the dragon while the missile is ready to go, in the story, and Bostrom insists that we are supposed to regret this. However, when we move back through the analogy to the real world, then the way that humans send other humans to the dragon is via war. Will ending aging end war? How?

Anthropomorphizing psychopomps may have been a mistake, since it has led to Bostrom imagining that if we just collect all of the psychopomps into one really big mean dragon, and then kill the dragon, that we'll have defeated death. Easy peasy!