Live data from Hacker News

Teachable Machine: Teach a machine using your camera, live in the browser

blog.google

61–70 of 95 posts

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#61
post #55

Earlier quoted context omitted.

Yes please! :) And some quick questions: What network topology do you use, and on what model is it based (e.g. "inception")? What kind of data have you used to pretrain the model?

We're using SqueezeNet ( https://github.com/DeepScale/SqueezeNet ), which is similar to Inception (trained on the same ImageNet dataset) but is much smaller - 5MB instead of inception's 100MB - and inference is much much quicker. The application takes webcam frames and infers through SqueezeNet, producing a 1000D logits vector for each frame. These can be thought of as unnormalized probabilities for each of ImageNet'…

Interesting!

I'm curious why you've used a different classification algorithm on top of a neural network. I would expect that a neural network on top of a pretrained network could give similar results, with the benefit of simpler code. Is performance the reason?

Anyway, I'm looking forward to your blog post.

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#62

deeplearn.js author here... We do not send any webcam / audio data back to a server, all of the computation is totally client side. The storage API requests are just downloading weights of a pretrained model. We're thinking about releasing a blog post explaining the technical details of this project, would people be interested?

There's something fantastically entertaining about this. It's stupidly simple (from the outside) but interacting with the computer in such a different way is weirdly fun.

It's like when you turn on a camera and people can see themselves on a TV. A lot of people can't help but make faces at it.

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#63
post #55

Earlier quoted context omitted.

Yes please! :) And some quick questions: What network topology do you use, and on what model is it based (e.g. "inception")? What kind of data have you used to pretrain the model?

We're using SqueezeNet ( https://github.com/DeepScale/SqueezeNet ), which is similar to Inception (trained on the same ImageNet dataset) but is much smaller - 5MB instead of inception's 100MB - and inference is much much quicker. The application takes webcam frames and infers through SqueezeNet, producing a 1000D logits vector for each frame. These can be thought of as unnormalized probabilities for each of ImageNet'…

[deleted]

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#64
post #61

Earlier quoted context omitted.

We're using SqueezeNet ( https://github.com/DeepScale/SqueezeNet ), which is similar to Inception (trained on the same ImageNet dataset) but is much smaller - 5MB instead of inception's 100MB - and inference is much much quicker. The application takes webcam frames and infers through SqueezeNet, producing a 1000D logits vector for each frame. These can be thought of as unnormalized probabilities for each of ImageNet'…

Interesting! I'm curious why you've used a different classification algorithm on top of a neural network. I would expect that a neural network on top of a pretrained network could give similar results, with the benefit of simpler code. Is performance the reason? Anyway, I'm looking forward to your blog post.

Training a neural network on top would require a "proper" training phase, and finding the right hyperparameters that work everywhere turned out to be tricky. Actually, this is what we did originally, in the blog post we'll try to show demos of each of the approaches and explain why they don't work.

KNN also makes training "instant", and the code much much simpler.

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#65
post #53

Earlier quoted context omitted.

People need to ask the question before making assumptions. In the case of Apple, they said it directly in the presentation of FaceID as well as TouchID IIRC. Yet people made these claims anyway. For this project, they also state it clearly on the page: > Are my images being stored on Google servers? > No. All the training is happening locally on your device.

Where is it clearly stating that? I couldn't find anything in the linked article + the github repo + teachablemachine.withgoogle.com But I do agree people need to ask the question before making assumptions. Sadly, the two popular mindsets is either to not think about privacy at all, or believe that everything is infringing on your privacy.

1. Go to the site: https://teachablemachine.withgoogle.com

2. Press "Start" or "Skip tutorial" (You don't have to give access to anything)

3. Scroll down to read the FAQ

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#66
post #5

I don't have a camera here. Did anyone try it? How does it work?

It's working great because they're using a state of the art model (SqueezeNet https://github.com/DeepScale/SqueezeNet) and also the samples / experiments you do are often only on yourself, in the same lighting, same clothes, etc. So it gives a nice idealized playground environment that mostly eliminates annoying details like this.

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#67
post #61

Earlier quoted context omitted.

Interesting! I'm curious why you've used a different classification algorithm on top of a neural network. I would expect that a neural network on top of a pretrained network could give similar results, with the benefit of simpler code. Is performance the reason? Anyway, I'm looking forward to your blog post.

Training a neural network on top would require a "proper" training phase, and finding the right hyperparameters that work everywhere turned out to be tricky. Actually, this is what we did originally, in the blog post we'll try to show demos of each of the approaches and explain why they don't work. KNN also makes training "instant", and the code much much simpler.

That makes sense.

By the way, I think your software could become very popular on the Raspberry Pi, because it would be very cheap and fun to use it for all sorts of applications (e.g. home automation).

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#68
post #46
post #43

Earlier quoted context omitted.

Yeah it's a little hilarious how people just keep giving Facebook more and more data to experiment with.

HN discussions tend to devolve into rants about privacy. There are a lot of repeated discussions that occur here. They overwhelm the discussion about the actual technology https://h4labs.wordpress.com/2017/09/27/groundhog-day-amazon...

That's because the privacy implication of the technology should be part of the discussions on the technology... technology is not neutral, the way its used and the privacy implications are significant.

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#69
post #65

Earlier quoted context omitted.

Where is it clearly stating that? I couldn't find anything in the linked article + the github repo + teachablemachine.withgoogle.com But I do agree people need to ask the question before making assumptions. Sadly, the two popular mindsets is either to not think about privacy at all, or believe that everything is infringing on your privacy.

1. Go to the site: https://teachablemachine.withgoogle.com 2. Press "Start" or "Skip tutorial" (You don't have to give access to anything) 3. Scroll down to read the FAQ

Ah, I didn't get that far due to it requesting the webcam. I'd prefer that they state it before the request, but an FAQ at the start of the project is good enough.

Re: Teachable Machine: Teach a machine using your camera, live in the browser

#70

Am I the only paranoid one who thinks this is just Google's way of capturing millions of faces in their database? Or did Apple beat them to it?

Don't worry some comment on a forum said they'd never do this, so I think we're all good!
Post reply on HN