QuickDraw

WHO

WHO

WHO

WHAT

WHAT

Quick, Draw!

Quick, Draw!

Quick, Draw!

Quick, Draw

Quick, Draw!

Launched as an A.I. Experiment, Quick Draw! is a game where a neural network tries to guess what you're drawing. The game was built to train a neural network to understand human drawings. Over 1 billion drawings have been collected and the data was open sourced on The Quick Draw! Data Site for researchers and developers to use. The data collected helped to power the machine learning used in Auto Draw, a drawing tool completed later.

This project started as a simple one day hackathon idea combining an API (Google's Cloud Vision API) and a game mechanism. I worked to quickly prototype the gameplay, saw it was sticky, and built out the game UX, brand and narrative and eventually a multiplayer gameplay version for use at Google's I/O conference.

The game helped explain complex technology, taught developers how to use the Google Cloud vision and went viral even appearing on The Late Show due to people's inability to draw cannons. Once over a billion drawings were collected; a site was developed, a book was made showing all 1 billion drawings (1,188 pages) and one off t-shirts, wall paper and prints were made.


Laucnched as an A.I. Experiment, Quick Draw! is a game where a neural network tries to guess what you're drawing. The game was built to train a neural network to understand human drawings. Over 1 billion drawings have been collected and the data was open sourced on The Quick Draw! Data Site for researchers and developers to use. The data collected helped to power the machine learning used in Auto Draw, a drawing tool completed later.

This project started as a simple one day hackathon idea combining an API (Google's Cloud Vision API) and a game mechanism. I worked to quickly prototype the gameplay, saw it was sticky, and built out the game UX, brand and narrative and eventually a multiplayer gameplay version for use at Google's I/O conference.

The game helped explain complex technology, taught developers how to use the Google Cloud vision and went viral even appearing on The Late Show due to people's inability to draw cannons. Once over a billion drawings were collected; a site was developed, a book was made showing all 1 billion drawings (1,188 pages) and one off t-shirts, wall paper and prints were made.

Launched as an A.I. Experiment, Quick Draw! is a game where a neural network tries to guess what you're drawing. The game was built to train a neural network to understand human drawings. Over 1 billion drawings have been collected and the data was open sourced on The Quick Draw! Data Site for researchers and developers to use. The data collected helped to power the machine learning used in Auto Draw, a drawing tool completed later.

This project started as a simple one day hackathon idea combining an API (Google's Cloud Vision API) and a game mechanism. I worked to quickly prototype the gameplay, saw it was sticky, and built out the game UX, brand and narrative and eventually a multiplayer gameplay version for use at Google's I/O conference.

The game helped explain complex technology, taught developers how to use the Google Cloud vision and went viral even appearing on The Late Show due to people's inability to draw cannons. Once over a billion drawings were collected; a site was developed, a book was made showing all 1 billion drawings (1,188 pages) and one off t-shirts, wall paper and prints were made.

Launched as an A.I. Experiment, Quick Draw! is a game where a neural network tries to guess what you're drawing. The game was built to train a neural network to understand human drawings. Over 1 billion drawings have been collected and the data was open sourced on The Quick Draw! Data Site for researchers and developers to use. The data collected helped to power the machine learning used in Auto Draw, a drawing tool completed later.

This project started as a simple one day hackathon idea combining an API (Google's Cloud Vision API) and a game mechanism. I worked to quickly prototype the gameplay, saw it was sticky, and built out the game UX, brand and narrative and eventually a multiplayer gameplay version for use at Google's I/O conference.

The game helped explain complex technology, taught developers how to use the Google Cloud vision and went viral even appearing on The Late Show due to people's inability to draw cannons. Once over a billion drawings were collected; a site was developed, a book was made showing all 1 billion drawings (1,188 pages) and one off t-shirts, wall paper and prints were made.

Launched as an A.I. Experiment, Quick Draw! is a game where a neural network tries to guess what you're drawing. The game was built to train a neural network to understand human drawings. Over 1 billion drawings have been collected and the data was open sourced on The Quick Draw! Data Site for researchers and developers to use. The data collected helped to power the machine learning used in Auto Draw, a drawing tool completed later.

This project started as a simple one day hackathon idea combining an API (Google's Cloud Vision API) and a game mechanism. I worked to quickly prototype the gameplay, saw it was sticky, and built out the game UX, brand and narrative and eventually a multiplayer gameplay version for use at Google's I/O conference.

The game helped explain complex technology, taught developers how to use the Google Cloud vision and went viral even appearing on The Late Show due to people's inability to draw cannons. Once over a billion drawings were collected; a site was developed, a book was made showing all 1 billion drawings (1,188 pages) and one off t-shirts, wall paper and prints were made.

download
Quick_Draw_Data_2
download (3)
QuickDraw_Book
Quick_Draw_book_3
Quick_Draw_book_2
QuickDrawTshirt

HOW

HOW

Technology: Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, Nick Fox-Gieg
Production: Brenda Fogg

Additional Design: Alex Chen, Andrew Herzog, Eli Block, Use All Five

Technology: Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, Nick Fox-Gieg
Production: Brenda Fogg
Additional Design: Alex Chen, Andrew Herzog, Eli Block, Use All Five

Technology: Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, Nick Fox-Gieg
Production: Brenda Fogg
Additional Design: Alex Chen, Andrew Herzog, Eli Block, Use All Five
 

Technology: Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, Nick Fox-Gieg
Production: Brenda Fogg
Additional Design: Alex Chen, Andrew Herzog, Eli Block

→ © ADAM KATZ 2019 ?        → HAVE A NICE DAY ✌        → PLEASE LEAVE MY $H!T ALONE ?        → SORRY; NO SHIRT, NO SHOES, NO SERVICE 👎        → COME BACK SOON 👋

→ © ADAM KATZ 2019 ?     → HAVE A NICE DAY ✌    → PLEASE LEAVE ME $H!T ALONE ?     → SORRY; NO SHIRT, NO SHOES, NO SERVICE 👎     → COME BACK SOON 🤞

→ © ADAM KATZ 2019 ?→ HAVE A NICE DAY ✌→ PLEASE LEAVE ME $H!T ALONE ?→ SORRY; NO SHIRT, NO SHOES, NO SERVICE 👎→ COME BACK SOON 🤞

→ © ADAM KATZ 2019 ?→ HAVE A NICE DAY ✌→ PLEASE LEAVE ME $H!T ALONE ?→ SORRY; NO SHIRT, NO SHOES, NO SERVICE 👎→ COME BACK SOON 🤞

→ © ADAM KATZ 2019 ?    → HAVE A NICE DAY ✌    → PLEASE LEAVE ME $H!T ALONE ?   → SORRY; NO SHIRT, NO SHOES, NO SERVICE 👎    → COME BACK SOON 🤞