another example: a developer used the exact same $8 ESP32-S3 chip and local AI setup to build a real-time object recognition camera the fact that this is running entirely offline, on an eight-dollar microcontroller, without any cloud API calls, is wild... it captures the video feed, processes it locally... through the model, and identifies objects in real-time. we are entering an era where you can just glue intelligence onto any physical object for less than $10. the hardware barrier is completely shattered.show more

I’m doing something similar but just running computer vision at the edge and then gets laid back to my agents as needed. I like what you were doing.

your implementation sounds cool!

I used one to build this.

this is really cool, have you thought about working on this as a commercial product?

Thanks, i have actually there is definitely a gap in the market for smart cat toys. The ones on the market all do the same thing just a laser or a bit that spins, cats are incredibly intelligent and soon predict the patterns and get bored. Thats what made me build it, this is just version 1 next I’m gonna add a camera so it knows when the cat is present and its location with the computer vision ai model. Then use that information to move the feather accordingly and automatically evading the cat like a real prey animal would.

that's a powerful demo of edge AI — the real test is how well it handles occlusion and lighting changes at that price po

i think at this price it doesn't matter at all

Cheap hardware plus local AI is opening up a lot of possibilities.

fact

the $8 chip doing this is still insane🔥

hell yeah

Object detection means autonomous targeting capability.

we are giving dumb objects a brain now🙃

i'm waiting for this device to run Doom using a local AI

Excellent. I have the same ESP32, and let me replicate.

you can try this

How mucho local memory?

512 KB of fast SRAM and 16 MB of flash

Woot woot. Pieces 😉

Idiots who have a child's understanding of LLMs and zero understanding of microcontrollers talking about a "hardware barrier" being shattered by this or a tiny LLM running on an ESP32, as if the former is revolutionary or later is beneficial to an average person's usecase

Yolo models are goated in local image recognitions 🔥

This chip will get you running but the camera will have its limitations. Such as resolution and sensors this will give you at best VGA quality.

Is this an open source project ?

Important step towards singularity immersion

Not sure but you said “$8 chip *and local AI setup*”. So my understanding is that the ESP32-S2 only captures, streams to video feed to a nearby, potentially beefy, laptop and *that’s* what running the AI and doing the recognition, correct? Or are you saying the S2 is autonomous?

老实说，对比一个中国量产带PTZ的 CCTV，这个价格对这程度的功能，CP值并不算高…

Bit of an overstatement

Ah the last time I tried esp32 cam it got turned to crisp 😭

Well done to the dev! Inference rate is too slow for anything safety related but slap that onto your home security and for $10 bucks you’ve got a killer setup.

Real time object recognition for under $10, that barrier is really gone now.

my 10yo son made this a year ago for birds outside with Claude Cli

this is so cute...

the hard part is not esp32-s3 inference, it is stable camera input in bad light

lol Blue Iris has been doing this for 10 or more years with yolo.

how the hell is this possible

@BrianRoemmele

fact-check this tweet by @ardchain. The $8 ESP32 isn’t running YOLO11, it’s a webcam feeding the PC that is running YOLO11. The LLM was trained only on TinyStories &its author says it “will not answer questions, nor follow instructions, nor write code, nor know facts.” The 512KB claim omits the 8MB PSRAM. No barrier was shattered.

$8 for real-time local object recognition is genuinely nuts. No cloud, no API cost, just glue it onto whatever you want.

八美元小板子跑成这样，离线这点太狠了

The S3 is a nice little package.

I’ve built that using ESP32

looks stylish

I have GOT to know more about this!!

edge ai keeps becoming more practical

Cool stuf

@BrianRoemmele