How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow, Keras & React Native
Tim Anglade on Hackernoon goes deep on how technical the silly app actually was to create:
The HBO show Silicon Valley released a real AI app that identifies hotdogs — and not hotdogs — like the one shown on season 4’s 4th episode (the app is now available on Android as well as iOS!)
To achieve this, we designed a bespoke neural architecture that runs directly on your phone, and trained it with Tensorflow, Keras & Nvidia GPUs.
While the use-case is farcical, the app is an approachable example of both deep learning, and edge computing. All AI work is powered 100% by the user’s device, and images are processed without ever leaving their phone. This provides users with a snappier experience (no round trip to the cloud), offline availability, and better privacy. This also allows us to run the app at a cost of $0, even under the load of a million users, providing significant savings compared to traditional cloud-based AI approaches.
The app was developed in-house by the show, by a single developer, running on a single laptop & attached GPU, using hand-curated data. In that respect, it may provide a sense of what can be achieved today, with a limited amount of time & resources, by non-technical companies, individual developers, and hobbyists alike. In that spirit, this article attempts to give a detailed overview of steps involved to help others build their own apps.
Adafruit publishes a wide range of writing and video content, including interviews and reporting on the maker market and the wider technology world. Our standards page is intended as a guide to best practices that Adafruit uses, as well as an outline of the ethical standards Adafruit aspires to. While Adafruit is not an independent journalistic institution, Adafruit strives to be a fair, informative, and positive voice within the community – check it out here: adafruit.com/editorialstandards
Stop breadboarding and soldering – start making immediately! Adafruit’s Circuit Playground is jam-packed with LEDs, sensors, buttons, alligator clip pads and more. Build projects with Circuit Playground in a few minutes with the drag-and-drop MakeCode programming site, learn computer science using the CS Discoveries class on code.org, jump into CircuitPython to learn Python and hardware together, TinyGO, or even use the Arduino IDE. Circuit Playground Express is the newest and best Circuit Playground board, with support for CircuitPython, MakeCode, and Arduino. It has a powerful processor, 10 NeoPixels, mini speaker, InfraRed receive and transmit, two buttons, a switch, 14 alligator clip pads, and lots of sensors: capacitive touch, IR proximity, temperature, light, motion and sound. A whole wide world of electronics and coding is waiting for you, and it fits in the palm of your hand.
Have an amazing project to share? The Electronics Show and Tell is every Wednesday at 7:30pm ET! To join, head over to YouTube and check out the show’s live chat and our Discord!
Python for Microcontrollers – Adafruit Daily — Python on Microcontrollers Newsletter: CircuitPython Comes to the ESP32-P4, Emulating Arm on RISC-V, and Much More! #CircuitPython #Python #micropython @ThePSF @Raspberry_Pi
EYE on NPI – Adafruit Daily — EYE on NPI Maxim’s Himalaya uSLIC Step-Down Power Module #EyeOnNPI @maximintegrated @digikey