Comment by skippyfish
2 days ago
You can buy sub-$0.50 microcontrollers. But even at $5, I don't know why you'd want to run models on them, it's an environment constrained to the point of being useless for this task.
And I hope it stays that way, I don't want MCU shortages...
Many artificial environments are useless to tasks they were not designed for until somebody experiments, tests, redesigns, and iterates.
I'll give a specific example apropos of TFA. Computer vision models were never run on MCUs because they were constrained to the point of being useless for this task, but then someone tried the impractical, and now it's trivial[1]
Regarding MCU shortages, you should be worried about the supply chain, but I don't see the impact really being from running LLMs on ESP-32s, of all things.
[1]: https://github.com/espressif/esp-vision
Fun and learning is a really good reason. It also reminds me of the damascene: trying to achieve something that doesn't feel possible, and working through all the extreme resource-constrained engineering limits.
I think most of my embedded projects aren't that useful, but they've taught me a lot.
I'm not disagreeing with you, I think this goes beyond impractical, it's doomed from the get go.
In my book, impractical means "I built a cuckoo wristwatch". Beyond impractical: "I built a cuckoo wristwatch but there was no room for a working mechanism".
I don't see the relationship between "fun and learning" and "(beyond) impractical".
I enter most of my learning project from the assumption that I could just buy/install whatever I am building and save time/money.
Please consider seeing things from a different perspective than "your book".
Not saying this to antagonise you, but because a lot of time reading comments like this makes other posters less willing to share their impractical efforts, and would love to read more of those, not less.
Learning how to make a cuckoo wristwatch and everything that involves helps you acquire skills, even if what you build is fundamentally useless.
How is it useless? If it has an NPU it is literally built to run models.
You're just extremely biased in what you consider to be a useful ML model. For example, for some strange reason you think only LLMs exist. The model must be as big as possible or else it is pointless.
Training custom non-LLM models for specific tasks so they run on a resource constrained device? You must be insane.
There's a neat project out there that can read your water meter into home assistant using an ESP32+camera+computer vision. I imagine a small TPU like this could be very useful for similar projects. More compute means higher resolutions and more reliability.
Interested in this. Link please
AI on the edge https://jomjol.github.io/AI-on-the-edge-device-docs/
I want to run music models on the Milk-V and have them jam in realtime with me.
isn't floor price 0.10$ for last couple years?
Well, that's sub-$0.50. But yeah, CH32V003 is in that ballpark, and some of the cheapest Microchip and Infineon products are around $0.20.
It's almost never worth it to buy the cheapest chip unless you're making a million of something, but there are very good ones around $1-$2, and $5 is the upscale stuff.
There are 2 cent microcontrollers.
Used in the cheapest devices you wouldn't even imagine to contain any software - eg. To control a touch sensitive on-off switch.
where can I learn about those?
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