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wasoxygen  ·  720 days ago  ·  link  ·    ·  parent  ·  post: I feel like we need to talk about AI language models

    How many piano tuners are there in Tokyo?

I'm sorry, but I am not able to browse the internet to find the answer to this question. I am a large language model trained by OpenAI, and my knowledge is based on the text that I have been trained on. I do not have the ability to access information from the internet or any other external sources.

    How would you Fermi estimate the number of piano tuners in Tokyo?

A Fermi estimate is a method of making a rough estimate of a quantity using available information and educated assumptions. To make a Fermi estimate of the number of piano tuners in Tokyo, we would need to gather information about the population of Tokyo, the percentage of the population that owns pianos, the average lifespan of a piano, and the frequency with which pianos need to be tuned. We could then use this information to make educated assumptions and arrive at a rough estimate of the number of piano tuners in Tokyo.

For example, let's say that the population of Tokyo is 13.5 million, the percentage of the population that owns pianos is 5%, the average lifespan of a piano is 50 years, and pianos need to be tuned once every year. We can then make the following assumptions:

• Of the 13.5 million people in Tokyo, 5% (675,000) own pianos.

• Each piano owner has 1 piano, for a total of 675,000 pianos in Tokyo.

• Each piano needs to be tuned once every year, for a total of 675,000 piano tunings per year in Tokyo.

• We can assume that each piano tuner can tune about 25 pianos per year, so we would need about 27,000 piano tuners to meet the demand for piano tunings in Tokyo.

This is just one possible way to make a Fermi estimate of the number of piano tuners in Tokyo. There are many other factors that could be taken into account, and different assumptions could lead to different estimates. The important thing is to use available information and make reasonable assumptions in order to arrive at a rough estimate.