Do we need to have the same account on edge impulse as well as on chat gpt for labelling. I have been trying to label data but unable to label. Can anyone help me.

Esp 32 cam object detection 🙏

Hi, if you have a very tiny dataset, why don't you use TensorFlow? Newbie here...

Amazing Application, I would think about apply it to my screen reading for faster processing.

ok. But what will it answer when it sees toy unseen before? I think, CharGPT will say YES, but your model will say unexpected answers )

Very helpful and amazing stuff to learn 😄

I really love this concept and def gonna try it but how's the license? like if you wanna train a commercial model then will GPT4o license would allow this? cuz as far as i know its not so it only works for personal stuff, please lmk if otherwise

How can we classify images (the model is from edge impulse) from esp32 and use Arduino uno to turn servo motors based on the result of classification ? (as you mentioned that we cannot use css for images)

So you basically used the GPT-4o for labelling the training dataset (that you created manually), that you then used for training your small model. 😊

That was interesting

As a new engineering student this is definitely what I want to do for a living

they do not _understand_ anything

wow, so we can detect bad product directly on Convair belt

It would be nice if the webapp could take a live video stream from the camera for the inferencing.

Chat gpt is dead now,

this is kind of a dumb post. i'm kind of the world's old time secret leader in procedural generation, as in through the 90s, 00s and a bit more, my procedural poetry and music generators were much more encompassing than any visible work. so i'm kind of like the world's most experienced procedural media experiencer. my issue is that my work and related factors drew intense abuse from some of the less visible factors in contemporary culture over a sustained period of time, so "trust issues". i'd have to train my own AGI amusements. this is keen to see. what i'd like to say is this is keen to see, technology applied in some kind of useful way for real lives. not what i expect from society whatsoever.

So is there a way to connect the micro-LLM to sensors so that for example I could video a self balancing robot , train the microprocessor and then the microprocessor would control the motorspeed to balance the robot?

The TAO Kit from NVIDIA seems very interesting one with the aspect of technology, the MediaTek tends to be quite successful in the terms of the edge AI applications.

Unfortunately they don't understand a thing. And they are very gullible to availability bias, even if something contradicts logic.

Is it possible to have a collection of small models on device with a "director" that choose the model based on the input?

*Have tried having the model that chatgpt labeled the data for label data for another model and then have that label data for another model and so on until....?*

"cloud on the edge" is pure marketing bullshit. Cloud is another-mams computer

A real world use case i was thinking of a few weeks ago was a grocery store assistant. likely built into AR glasses, you would first build up grocery list then the model would look for those items via the camera as you're walking down the isles. probably would take a long time to train with all the different items you would need to account for but solves one of the biggest gripes i have with going to the grocery store.

Very useful!! I'm finding anymethod to collect data wiressly and the speed is fast enought, can Edge Impulse data forwarder do this?

But the data base is way too small, if you show any color object to it , like orange it will be toy ( color x pixel ) . So I would say , it's click bait ;)

Sir i am getting error during compilation of the example from library included downloaded from edge impulse.. please help....

You double introduced what you're doing and nobody can see the screen 😢

It's against openAI policy to use gpt to train other models 😅

Awesome

This is so cool, congratulations on that!

Conclusion Implementing logarithmic and optimized calculations on edge devices with limited resources can significantly improve efficiency and performance. By following these strategies, you can develop robust and efficient solutions that make the most of limited hardware capabilities.

isnt that illegal

incoming openai lawsuit

I've been looking for this for a couple months, now I see this video, my mind is blowing!

Sam Altman left the chat

small language models retire large language models

عالی بود 👌🏼👌🏼

As the poet said, this is f'n awesome :)

Bakit hanggang ngauyun e wala pa rin GOVERNMENT SANCTIONED na GUMAGAWA ng RHIBS ng bansa? Samantalang nuon kay PNoy e me plano na tayong maka GAWA ng mga BARKO!

Really interesting ; wondering if it could be used for uav navigation (vision based) on commodity hardware

Hello, you mention the Coral Micro dev board. Does Edge Impulse supoort it?

I don't think they understand anyway

Hi! I listened to you and understood what you said, but I still have no idea how to start with my Raspberry Pi and reproduce what you did there. I would like to do the same thing, but I don't know how. It would be amazing if I could follow your step-by-step instructions. Cheers!

So will it be equivalent to gpt2 ...3

Yes, it is possible to use a multimodal AI assistant that can both see your computer screen and respond to voice commands. This type of technology is often referred to as "vision-enabled voice assistants" or "visual voice assistants." Some popular examples of such assistants include Amazon Alexa with the Amazon Lookout for Gadgets service, Google Assistant with its Vision API integration, and Microsoft Cortana with the Windows Eye Control feature (which requires specialized eye-tracking hardware). These assistants can perform various tasks such as identifying objects on your screen, providing visual feedback based on voice commands, or even controlling your mouse and keyboard using only your voice. However, keep in mind that these features may require additional setup and configuration, including enabling accessibility settings, installing necessary software or services, and granting permissions to the AI assistant to access your computer's camera and microphone. Additionally, privacy concerns should be taken into consideration when using vision-enabled voice assistants, as they involve sharing more personal information than traditional text-based voice assistants.😎🤖

@edgeimpulse how feasible is it, using your tool, to create a model sophisticated enough to track facial expressions with a raspberry pi equipped with a micro camera ? Would this likely only work with a specific face it was trained with? Thanks for your thoughts

This video is an ad. Why did I get it in my feed not tagged as an advertisement?

Realy great!

Commercial use here would be a cat door for cats to get in/out of the house, and check if the cat has an object it its mouth, like a dead mouse, rabbit, bird, neighbor kid, etc, then not allow the door to open. Otherwise allow cat in.