A lesson from the machine learning community

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thai_tong
Posts: 20
Joined: Sun Jul 01, 2018 1:38 pm

A lesson from the machine learning community

Post by thai_tong »

There is a common joke in the machine learning community.
How long does it take to train a deep learning algorithm? 2 days
Now double your computing power. How long does it take to train a deep learning algorithm? 2 days

What often happens is the more computing power you have the more complex you make the computer model, or you want to run the training algorithm for more iterations to eek out extra performance.
In fact, 2 days is just the amount of time you are willing to commit to train the algorithm.

This has lessons for the FIRE community. I like my lifestyle and I hope to be FI in 10 years. If my salary doubled I'd start to think that I'm too austere and actually I deserve a better lifestyle, eventually my lifestyle inflates until I've still got 10 years to FI.

I'm happy with my lifestyle now so it doesn't make sense that I should increase my lifestyle and delay FI. It's better to appreciate what I have and take the opportunity to reach FI faster.

7Wannabe5
Posts: 7081
Joined: Fri Oct 18, 2013 9:03 am

Re: A lesson from the machine learning community

Post by 7Wannabe5 »

I have the opposite problem. Because my income sources have mostly been flexible or temporary and I have little difficulty with saying “Friday will be my last day.”, I tend towards very quickly ratcheting my income/hours devoted to paid work down to match lowered expenses acquired through improved frugality and/or some kooky scheme I’ve hatched.

thai_tong
Posts: 20
Joined: Sun Jul 01, 2018 1:38 pm

Re: A lesson from the machine learning community

Post by thai_tong »

I want to point out that this is different from lifestyle inflation.
Lifestyle inflation happens when there's extra income and people feel more comfortable spending extra.
In this case someone decides that they will retire in X years and continues to use that as a baseline for their expectations so they increase their spending to match their expectation.

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