[otras]

I remember learning about the complex pumping machines running some of the reservoir pumps in Boston (https://en.wikipedia.org/wiki/Metropolitan_Waterworks_Museum), where they made such distinct noises when working (and malfunctioning) that an engineer could diagnose the problem by ear.

I sometimes think about what a modern analogy would be for some of the operations work I do — translate a graph of status codes into a steady hum at 440hz for 200s, then cacophonous jolts as the 500s start to arrive? As you mentioned, no perfect analogy as you get farther and farther from moving parts.

[jychang]

You can try running LLMs on your own computer!

They have extremely distinct sounds coming from the GPUs. You can hear the difference between GPT-OSS-20b and Qwen3-30b pretty easily just based on the sounds that the gpu is making.

The sound is being produced by the VRMs and power supply to the GPU being switched on and off hundreds of times per second. Each token being produced consumes power, and each attention and MLP layer consumes a different amount of power. No other GPU stress test consumes power in the same way, so you rarely hear that sound otherwise.

[vrighter]

this. I was running a reinforcement learning training run. I could very clearly hear from the coil whine whether it was simulating or backpropagating

[SoftTalker]

Cars are a pretty common example. Any new noises or changes in noises are indicating something. Usually a developing problem. E.g. a groaning or roaring noise, especially in turns, that varies with speed, is likely a worn out wheel bearing.

[andai]

Sound is a good cue to problems. In one place I worked, we had a big board of dials showing what was happening to our web servers. The hands were moved by little servomotors that made a slight noise when they turned. I couldn't see the board from my desk, but I found that I could tell immediately, by the sound, when there was a problem with a server.

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