The invincible 20 year olds

It is often said that people age 20 think of themselves as if they’re invincible. It’s an attribute most commonly given to young men in general. 

The idea of immortality is one which comes up in mythology a lot and sometimes it comes up within scientific circles. Bacon spent his life in search of finding ways to become immortal until, in perhaps an ironic way, his search killed him.

When immortality is spoken about the concept of ageing is often also brought up, Tithonus comes to mind.


Solving the problem of ageing through does not lead to immortality, although it may seem to be that way. Each year you live your chance of dying that year increases. This is how the ageing process manifests itself in this side of the numbers, growing from a low of 0.01% age 5 up to almost 40% age 100.

What if instead, this didn’t rise. What if every year you had the same chance of dying as when you are 20? How long would you then live, with ageing no longer the issue?


Life expectancy is the median age at which people die. That means how many years until half a population has died. With a model of what fraction of 20-year-olds doesn’t make it to their 21st birthday we can work out at what age would half of the people die, if every year of their life they had the same chance of dying as when they are 20.


This calculation can work for any constant figure. Using a figure of 0.05% chance of dying per year (20-year-old man). It would take over 1385 years for the average person to die. Therefore assuming ageing is completely removed then the average lifespan could be 1385 years!

Comments

Post a Comment

Popular posts from this blog

THREE.js: minecraft in a weekend

Image
I have been enjoying exploring the ideas behind procedural worlds and in a previous post even showed a simple voxel renderer based in THREE.js which would load chunks when the camera got close enough to the edge. That was based on the great tutorial here which explains how to create a voxel-based mesh in THREE.js such that it doesn’t use all of the machine’s resources for the smallest of worlds. I found that to be an invaluable source of information and continually referenced back to that throughout the weekend. Looking back at my git logs for this project to be able to type this up, I have no intention of this post being a tutorial in itself, my progress was as follows: Walking around rather than observer view Sideways collision detection - not walking through the map Changing to a system where there was a sensible grass - sand - water height system Adding trees Another optimisation for terrain generation in addition to the afor...
Read more

Picking apart Perlin noise from first Principles

Image
Although there are a lot of tutorials explaining the what and even the how of Perlin noise and the general class of algorithms; gradient noise, I have found none explaining the why behind the algorithm. Why does this algorithm work? In this post I aim to build up perlin noise from first principles, explaining why we add each element to the algorithm as we do. We will start by trying to make a surface, perhaps for a computer game world map. We are aiming for something that looks like a mountainous region. We don’t want to hand craft this landscape as we want it to go on forever, how can we procedurally generate this world? Given we want the surface to be random, we could start with that. However as you can see that doesn’t lead to the most pleasing of surfaces, in fact it wouldn’t be traversable in the game. Our problem is that there is no smoothness from one place to another. The lowest of points could be adjacent to the highest of points. What we want is for it to take som...
Read more