Mr. Beast Saying Increasingly Large Amounts of Money

Mr. Beast Saying Increasingly Large Amounts of Money

By Morry Kolman

Mr. Beast Saying Increasingly Large Amounts of Money is a compilation of over 2800 clips from 206 Mr. Beast videos. This is the abridged 12 minute version—both this and the full length hour-long cut are also available on my YouTube and my website. The work is intended to distill the content of the most popular YouTuber in the world down to one of its core motifs: the promise of the next number being even bigger.

Mr. Beast, born as Jimmy Donaldson, tries to present himself as apolitical. But when you convince 4% of the world to hit the red Subscribe button, you get the politics for free. These clips are those politics. Donaldson has often explained that the over-the-top excesses of his content—both in conspicuous consumption and even more conspicuous philanthropy—enable him to snowball money and influence that he can then leverage to make even more positive change in the world.

This framing is overwhelming. Donaldson has been in the hot seat for allegations of worker safety violations, hawking moldy knock-off Lunchables, and exploiting the poor, disabled, and destitute for views. Nothing, however, can avoid getting subsumed by the bottom line. “Is Mr. Beast good?” quickly becomes a proxy for “Should Mr. Beast's videos exist?” and if there is anything Mr. Beast does well, it is documenting the size, appreciation, and impact of his content at an incomparable rate. To argue against Donaldson is to rebuke the planting of 20 million trees, wish 100 people remained blind, and contend that those homeless people should not, actually, have been given $10,000.

Mr. Beast Saying Increasingly Large Amounts of Money is an attempt to critique him on his own terms. In their proper context, Donaldson's absurd monetary figures not only make some level of sense, but engage the viewer on an emotional and entertaining level. Boiled down to concentrate and injected intravenously, though, they are a hypnotic experience of whiplash. It’s so easy to watch the numbers go up, increasing in opulence. At the same time, what’s actually happening—the deployment of real wealth and capital in service of making the world’s already largest creator get even more views—is uncanny. In incessant and mesmerizing form, this video portrays a 2020s version of the American Dream. Whether through extreme challenges, complete luck, or simply being a good supporting character, the beneficiaries of these videos receive houses, cars, and shiny briefcases of cash. In the video, though, this “philanthropy” is contextualized by the spectacle of consumption around it. Donaldson gives $50,000 to teachers, then dishes out $70,000 on a golden pizza. He spends tens of thousands to blow up fireworks in the sky, and drops hundreds of thousands back down from planes. He shells out $1 million on groceries for the hungry—and wastes the same amount on lottery tickets, all for the love of content.

With his (often literal) piles of money, Mr. Beast wields the ability to change lives at will. Unfortunately it is a power he uses indiscriminately, self-servingly, and ostentatiously. Jimmy Donaldson does not perform acts of kindness, he purchases views, and in this video we watch that transaction happen several thousand times. Mothers cry, children scream, and a guy named Mac gets buried alive. In return, he has not dipped below 100 million views in over four years.

Methodology

First, for the main source of data, I chose all Mr. Beast videos with uploaded (ie. non-auto-generated) transcripts—a total of 229 out of 837 published videos on his flagship channel. This gave me a source of processable ground truth about where money was mentioned and also limited the videos to those published the last 6 years, which make up the majority of his meteoric rise. Then, I downloaded the videos in 360p and scraped their transcripts for every occurrence of a dollar amount, logging each mention with its sum, video, and context in a database that I would build on top of as I nailed down the exact timing. I used those contextual timestamps to make rough clips that I fed into the open source AI tool Whisper to (a) get a more precise measurement of where “X dollars” was actually said and (b) standardize and double check that my first scrape had gotten the amount correct. Finally, as many of the clips were still off by a few annoying and noticeable fractions of a second in any direction, I made a script that allowed me to go through each entry individually, trim or extend the clip on either end, and modify the amount one last time if my first 2 methods had failed. After all 2800+ were processed—a task that took weeks—I made a final set of clips out of higher quality versions of the videos and used Premiere to make the film’s final dizzying supercut you see before you.

90% of data science is data cleaning, and I have kept this overview pretty high-level in the interest of making it accessible to a wide audience. A much longer and more technical dive into the steps needed to go from a raw YouTube archive to this video—including everything from token suppression, the comparative benefits of transcription libraries, counterintuitive ways to standardize and parse numbers in natural language, and debugging audio desyncs in clip concatenations - may appear in the future on my website.

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💝 closing note

This project took literal hundreds of hours to complete, so thank you for watching! It could not have happened without Sam Lavigne’s Infinite Video class at the School for Poetic Computation, which gave me the opportunity to develop a proof of concept last year. There’s a lot of content out there, and critique-through-clip-compilation is a fun medium. I encourage you to give it a try :)

Your fellow brains in rot,

— Morry & Reboot Team