We return to the saga to make indescribably large numbers, larger than anyone else. Today, we look at the Veblen Functions once again and take them to their highest limit, and then we start making something called a Collapsing Function. Large Numbers is back, onward to be bigger than ever.

Continuing our new voyage into making numbers larger than ever before, I continue off of the ordinals defined before and quickly surpass every other number notation system proposed, and then continue even further. In this essay, we define a general definition to create a finite number for all possible ordinals; get to ordinals like ε(0), ζ(0), and eventually reach φ(1, 0, 0); and then use these all to define unfathomably large numbers.

Continuing our new voyage into making numbers larger than ever before, I discuss the use of diagonalization functions powered by ordinals. We start at the lowly “f(x) = x+1″, but then move on to make large numbers that eventually match everything the Extended Conway Chained-Arrow notation has.

The previous attempts at making an introduction to large numbers have all fallen apart. So I’ve decided to try again, taking an approach to re-explain how to make large numbers and how large numbers work in a very easy to follow manner. This post explains the concept of Graham’s Number and multiple extensions to Conway chained-arrow notation.

The previous attempts at making an introduction to large numbers have all fallen apart. So I’ve decided to try again, taking an approach to re-explain how to make large numbers and how large numbers work in a very easy to follow manner. This post explains the concept of magnitude, exponentiation, tetration, Knuth Up Arrows, and the Hyper Function.

About half a year ago, a reader named Louis Epstein asked me a question regarding large numbers. I answered his question, which lead to more questions. In this post, I attempt to tackle another one of his questions — Which is larger, x[x[...[x[x]]]…]]] of length x or x→x→…→x→x of length x? For those that both make large numbers as a very nerdy hobby and understand what is going on, this post is for you. For the remaining 99.9999% of the world, wait until Wednesday.

A decent amount of people play the lottery. We also know that playing the lottery makes you lose money, on average. But just how much money are people losing? What would the jackpot or ticket price have to be to make it worth playing the lottery at certain odds of winning? Today I use math to find out.

Bayes Theorem is an important mathematical formula of probability that can teach us how to properly use background information to understand the true probability of events. After we use it and understand the general philosophy, we also understand that the existence of false positives requires us to apply skepticism to claims in our lives.

About half a year ago, a reader named Louis Epstein asked me a question regarding large numbers. Which is larger, 3[3[3[3]]], a certain number defined via Moser Notation, or 3→3→3→3, a certain number defined via Conway’s chained arrow notation? For those that make large numbers as a very nerdy hobby, this post is for you.

“In a room of 23 people, the chance that there are two people who share the same birthday is 50%. In a room of 75, that chance of overlapping birthdays increases to 99.9%!” How is this possible? The birthday paradox, that’s how! Check it out!