From df674f6bd6b560948b8e056133003a20333f3e12 Mon Sep 17 00:00:00 2001 From: Justin Haaheim Date: Thu, 30 Jun 2022 13:51:29 -0700 Subject: [PATCH] Add flora landing page Summary: The purpose of this diff is to add a WIP landing page for Flora so that we can link to it from the blog posts announcing PlayTorch. As a follow up we will need to add links to PlayTorch in the iOS and Android app store, and a call-to-action at the bottom (perhaps "Join our discord"). Reviewed By: clarksandholtz Differential Revision: D37540835 fbshipit-source-id: b2899db4d3f193675282eeaf2d42e03fe3ba6791 --- website/src/pages/flora.mdx | 32 ++++++++++++++++++ .../static/img/flora/flora-opening-page.png | Bin 0 -> 755867 bytes 2 files changed, 32 insertions(+) create mode 100644 website/src/pages/flora.mdx create mode 100644 website/static/img/flora/flora-opening-page.png diff --git a/website/src/pages/flora.mdx b/website/src/pages/flora.mdx new file mode 100644 index 000000000..9cd118357 --- /dev/null +++ b/website/src/pages/flora.mdx @@ -0,0 +1,32 @@ +--- +id: flora +title: The Flora App +hide_table_of_contents: true +--- +
+ +# The Flora App + +*Flora* is an multimodal learning app built with PlayTorch. It was built through a collaboration between the PlayTorch team and PhD students in Stanford University's Human-Computer Interaction Graduate Program. + +The app presents a sample lesson about eucalyptus trees in California and makes use of "multimodal learning" -- learning that happens through a variety of different modes like visual, kinaesthetic, reading, writing and speaking. PlayTorch enabled us to quickly integrate a variety of machine learning models that make the learning experience interactive and engaging. + +The Flora App + +## Try it out + +You can try out Flora for yourself! + +To get started follow these steps: + +1. Download the PlayTorch app onto an iOS or Android device. [TODO: Add link] +2. Open the PlayTorch app and use it to scan the QR code on the right side of this Expo Snack [TODO: Add link]. +3. Start the lesson! Your first task is to find a eucalyptus tree and scan it using the custom-tuned imagenet classifier. If you don't have a eucalyptus tree nearby try using one of these [pictures](https://www.google.com/search?q=eucalyptus+tree&rlz=1C5GCEM_enUS992US992&source=lnms&tbm=isch&sa=X&ved=2ahUKEwiMje_M8NX4AhWPDkQIHYNhCGkQ_AUoAXoECAIQAw&biw=1964&bih=1117&dpr=1#imgrc=_iXbgljkmKDk4M). + +PlayTorch allowed our team to quickly integrate and use three different machine learning models, which you'll see as you engage with the app: +1. The imagenet classifier for identifying tree types +2. The wav2vec model, which enables high-quality speech-to-text. +3. The BERT QA model for answering basic questions about eucalyptus trees. + + +
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