31–40 of 148 posts
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 ;)
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 ;)
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How does one get this job? This sounds ridiculously fun.
It was random, I was already working on the show as what Hollywood calls a (technical) “consultant”: advising on storylines, dialogue, background assets, etc. When this idea popped up, someone suggested we build the app for real. We took a try and ended up building the entire thing in-house with the crew, as opposed to hiring an external agency to do it for us.
Edit: I guess it's official: The time of XKCD 1425 has passed. https://xkcd.com/1425/ September 2014; Randall undershot that by a bit :)
Ha 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 :)
Earlier quoted context omitted.
It was random, I was already working on the show as what Hollywood calls a (technical) “consultant”: advising on storylines, dialogue, background assets, etc. When this idea popped up, someone suggested we build the app for real. We took a try and ended up building the entire thing in-house with the crew, as opposed to hiring an external agency to do it for us.
Sounds like you're handling yourself even better than the characters in the show. :) Edit: I guess it's official: The time of XKCD 1425 has passed. https://xkcd.com/1425/ September 2014; Randall undershot that by a bit :)
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How large is the training set / how did you get a sufficient amount of hot dog pics for a custom model, especially since you did not have a class of naive Stanford CS students at your disposal?
About 150k total images, 3k of which were hotdogs. The results are far from perfect (there's ton of subtle — or hilarious — ways to trick the app) but it was better than using a pre-trained model or doing transfer learning, accuracy-wise (honestly it was even better than using Cloud APIs). As for the difficulty in preparing the training set, I'll just say I definitely empathize with Dinesh and Jian Yang’s feelings in…
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 your model and on what hardware?
:)
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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…
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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…
Ha 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 :)
Earlier quoted context omitted.
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…
What was the hack?