Lindy effect
en.wikipedia.org
en.wikipedia.org
At the time it surprised me, but of course it is natural to expect long games to be long.
https://www.chess.com/blog/kurtgodden/the-longest-possible-c...
Chess AIs, perhaps needless to say, are very good at computing at the depth necessary to win drawn-out endgames.
Indeed, which is why I am skeptical of purely anecdotal claims of the Lindy effect, as they may be skewed by survivorship bias. In this case, however, you have the numbers to back up the observation.
Take programming languages for example. If I asked you to bet on 30 different programming languages which would still be in use in 10 years, and all you knew about them was how long they had already been in use, you'd probably correlate your bets to some degree with their age.
Consider radioactive decay. An isotope has a half-life that remains constant over time. After one half-life, the remaining material of that isotope isn't there because it's "special" or robust or less likely to decay, it just got lucky. Its half-life from this point remains unchanged, so it does not display the Lindy effect.
Similarly, old humans give us plenty of opportunity to talk about survivorship bias, but we out lifetimes do not display the Lindy effect -- older humans are not expected to have longer remaining lives than young humans.
Gott says you can be 95% confident that you're experiencing the thing in the middle 95% of its life. Let's say x is its life so far. If x is 2.5% of its eventual life (one extreme of the middle 95%), then the thing still has 39x to go. If you're at 97.5% (the other extreme), then the thing only has x/39 left. So the 95% confidence interval is between x/39 and 39x
Of course, 5% of the time you actually are experiencing something at the very beginning or very end of its life (outside the middle 95%), which is a unique thing. But that's why it's a confidence interval < 100% :)
I prefer this form of the principle a lot more than "the expected life is equal to 2X, always."
Side note: I took J. Richard Gott's class in college called The Universe. Maybe not the best use of a credit in hindsight, but we studied some really interesting things like this.
If you only look at development since agriculture then yes, but that's less than one percentof the time since the taming of fire.
Anyone know of a term for this kind of behaviour? I've never seen it named, though I do recall an article that made the HN front page that demonstrated this effect with the New York subway.
Far more interesting is that two of the buggers will always turn up when you don't actually need one. I can prove that by assertion now and fairly confidently be able to appeal to around 60M Britons for testimony as required.
This is not related to "virality" which is my newly made up term for the Lindy Effect.
However, if the buses arrive independently and by a purely random process on average every 10 minutes (i.e. a poisson process), your wait will average 10 minutes.
I always remember this result from probability when waiting for something. It helps me feel less unlucky: of course, I tell myself, it's more likely to land in the time interval between widely spaced busses because those intervals take up more space on the timeline.
We can also see why it's really difficult to compete with early [surviving] frameworks, since they will last for a really long time.
The longer it continues increasing adoption and users (like any network effect) the more useful it will become to more people. Also, the higher the market cap, the more people will be invested in its success. The longer it continues to work as designed, the more people will trust it.
js got there by happenstance of history.
In the corporate IT world, there are IBM operating systems, such as Z/OS, that are direct descendants of 1960s operating systems.
Also, instruction sets for IBM mainframes and Intel x86 machines have been around for a very long time, and are not likely to go away any time soon.
Not to mention standards like 120v/60Hz AC and the shapes of electrical connectors, which have been around even longer and will thus probably survive for a very, very long time.
And going back to software, editors like Emacs and vi have been around so long (both come from the 1970s, and were invented for CRT terminals) that they're likely to keep on being used for a long time to come.
Say at age x my probability density of dying at that instant is f(x). Now we condition on the obvious fact that I would lived at least x before I die (counting from 0). The distribution function F(x) is the probability that I die before x. So that gives a conditional probability density of dying in this instant is
h(x) = f(x) / (1- F(x))
If h(x) is an increasing function of x then I am more human, I age. I age.
If its a decreasing function of x I am probably the Joker, "... makes me stronger". Whenever h(x) is a decreasing function of x one encounters Lindy effect.
Pareto distribution has been called out in the article but anything that has a fatter tail than the exponential distribution will suffice. The life of a database query, search engine request, etc., etc., likely all fall under this category. In such cases it is on us engineers to try to make those latencies have an increasing hazard function.
The lesson here is that things that last have developed certain adaptations to make them last. It's always worth studying why some oft-repudiated or outdated tech won't die; it is almost always because it possesses some key attribute present that is essential. If you're proposing a new framework, or promoting a new idea, it is essential you understand why these crufty old incumbents are still around, and see whether your new framework or idea embodies those old adaptations.
I've learned a lot about how flashy surface features (which compete well against new tech at the surface level) can be inferior to tech that embodies what the incumbents did well.
https://english.stackexchange.com/questions/153166/what-is-t...
It happens to me all the time. For anyone who hasn't experienced this, I offer this experiment. Pick one or more words from the list below that you don't already know. Repeat it to yourself a few times, read the definition, and invent a sentence using the word. Remember, choose a word or words you don't know.
frisson -- shudder of emotion with goose bumps when deeply affected by music
comity -- courtesy between nations for the laws of another
blithe -- happy and not worried; not realizing how bad a situation is
voxel -- 3D analogue to 2D pixel; a portmanteau of "volumetric" and "pixel"
pratfall -- comical fall landing on the buttocks
deus ex machina -- a god introduced into Greek/Roman play to resolve plot; for example, in Raiders of the Lost Ark, the hero's problem is solved for him rather than having him solve the problem himself; the film would end the same way even if Indiana Jones didn't exist: Nazis open the ark and kill themselves; pronounced day-us-eks-mah-kah-nah
marmite -- large cooking pot having legs and a cover; also a British sandwich spread made from yeast extract
Maybe you can come back to this comment 48 hours from now and tell us if you've heard your chosen word in real life soon after learning it.
Does anyone know if there a different name for those distributions?
Do you know of any literature, articles, etc., about this? I'm asking more from a consumer's view point..
If it is a brand new car (and depending on the kind of car, too) - you probably don't want to do this, at least immediately.
This is because the engine has not been run much since it left the factory. There is an engine "break in" period (you can read about it in your owner's manual) during which you need to follow the instructions properly, or you can actually cause damage to the engine and decrease its life dramatically.
Essentially, it involves not running the engine under extreme loads or speeds for so many miles (500 - 1000 I think is normal). After that, you might also do an oil change and some other early maintenance. For certain sports cars or other high-performance vehicles, it can be even more strict.
It basically has to do with the frictional components wearing into each other with lubrication carrying away (and being captured in the filter) the small bits of metal scraped away. Because even despite the fine tolerances engines and transmissions, etc are machined too, they aren't exactly matched, and the wear-in period allows for this (then you change the fluids and filters to remove the contaminants). Running the engines and such hard during this period puts higher friction and stresses on the system, which actually causes more metal than normal to be removed (essentially - wearing the engine in more than needed, if that makes sense).
This is also basically the same thing you have to do when you get an engine overhauled or otherwise modified (ie - new pistons, rings, porting, honing, etc).
Same difference, I guess.
https://en.wikipedia.org/wiki/Red_Queen_hypothesis
Basically, from Van Valen's data, species have a constant chance of going extinct, regardless of how long they've been around. His hypothesis is that even though speciation appears to be a discrete event, these species are constantly jockeying with each other for survival in a dynamic environment -- they have to run faster and faster to stay in the same place, and are always subject to falling out of the race, as it were.
The devil's in the details, of course, but it's intriguing to jam these two ideas together.
I wonder if it also holds true for profitable companies. That would mean that - all other things equal - a company 10 years old is worth as much as a company that is one year old but makes 10x the profits.
There is kind of an escape velocity then... Some teams will be able to refactor or replace their way out of this, back to a point where more developer hours equals more features.
Other companies will fail to achieve escape velocity, and the dev team will expand to use all available resources while the application becomes slowly worse relative to competitors.
That process can be stretched out, and money made while the velocity nears zero, but the company will eventually die.
Whether your codebase and development team is an asset or a liability depends on whether you have that escape velocity.
That's only if what they're building is capable of eventually turning a profit. History is full of dead startups that had ample funding and lots of customers, and went on for many years, but could never figure out how to turn a profit. For example: