US only, welcome to the "global system of interconnected computer networks". Hope Richard's P2P-internet will work better :)
Yup sorry about that, the app is available only in the US (& Canada) due to some legal restrictions we couldn't avoid. FWIW I also worked about on Richard's New Internet concept for this season so I definitely hear ya ;)
Not Hotdog App
61–70 of 148 posts
Re: Not Hotdog App
#62Earlier quoted context omitted.
It was written in Objective C?
It's actually written in React Native with a fair bit of C++ (TensorFlow), and some Objective-C++ to glue the two. One cool thing we added on top of React Native was a hack to let us inject new versions of our deep learning model on the fly without going through an App Store review. If you thought injecting JavaScript to change the behavior of your app was cool, you need to try injecting neural nets, it's quite a fee…
Re: Not Hotdog App
#63Re: Not Hotdog App
#64Does it detect penises? I don't want to try it myself.
Re: Not Hotdog App
#65Ha didn't expect this to end up here. If anyone is interested, I'm working on a blogpost explaining how we built the app in detail… It uses embedded TensorFlow on device (better availability, better speed, better privacy, $0 cost), with a custom neural net inspired by last month's MobileNets paper, built & trained with Keras. It was loads of fun to build :)
Re: Not Hotdog App
#66Does it detect penises? I don't want to try it myself.
Only American ones it seems
(If anything, I'd expect the classifier to more reliably call "not hot dog" on a penis that's circumcised, since hot dogs rarely are.)
Re: Not Hotdog App
#67Earlier quoted context omitted.
AWESOME! Can you please elaborate a bit more on the model architecture and what you tried with respect to transfer learning? Did you use an imagenet architecture e.g. VGG and retrain from scratch or a custom architecture? Did you try chop off the last 1/2/3 layers of a prerrained mode and fine-tune? Bonus points: 1. How much better were your results trained from scratch vs fine-tuned? 2. How long did it take to train…
Hey so I actually tried Vgg, Inception and SqueezeNet, out of the box, chopped and trained from scratch (SqueezeNet only for the latter due to resource constraints). We ended up with a custom architecture trained from scratch due to runtime constraints more so than accuracy reasons (the inference runs on phones, so we have to be efficient with CPU + memory), but that model also ended up being the most accurate model…
Thanks for sharing all the tech details too, it's been great to read. I'm even more amazed to see it as a real app, that I didn't expect!
Re: Not Hotdog App
#68Will it be released world wide
Is there any specific reason why this happens, just seems to me like you get worse reach and no benefits? Especially for a marketing stunt like this.
Re: Not Hotdog App
#69Earlier quoted context omitted.
Yup sorry about that, the app is available only in the US (& Canada) due to some legal restrictions we couldn't avoid. FWIW I also worked about on Richard's New Internet concept for this season so I definitely hear ya ;)
Don't apologize here. Apologize on the product page for this and all other similar things you do in the future to reduce amount of surprise for customers (and as a result also enmity created towards you).
The authors of this app don't owe you anything and are entitled to sell it in whatever countries they so choose. Additionally, the app doesn't even get listed in countries it's not available in. The only reason you and other non-US users (such as myself) are able to see it is because the OP posted a link to the US version of the app store on a forum where the vast majority of visitors are US-based. Get off your high horse.
Re: Not Hotdog App
#70Ha didn't expect this to end up here. If anyone is interested, I'm working on a blogpost explaining how we built the app in detail… It uses embedded TensorFlow on device (better availability, better speed, better privacy, $0 cost), with a custom neural net inspired by last month's MobileNets paper, built & trained with Keras. It was loads of fun to build :)
The effort you put into the show is much appreciated.