OKAI viewed on multiple devices

Links: website
Members: Jiaju Ma, Michael Mao, Yimei Hu
Duration: Sep 2018 - May 2019
Pageviews: 160k+
Users: 38k+

Overview

OKAI is an interactive introduction to Artificial Intelligence (AI). The project aims to demystify and introduce machine learning and deep learning concepts to a broader audience with limited or no background in computer science. It utilizes web-based interactive graphics and animations to visualize the working principles of a simple feed-forward neural net classifier on the MNIST dataset.

I was the AI specialist of OKAI, conceptualizing the materials and writing 5 out of the 6 chapters. I also worked with Jiaju Ma to come up with concepts of the more mathematically-oriented animations.

OKAI chapters

Mission and Methodology

From “The Matrix” to “The Terminator” to “2001: A Space Odyssey”, there is no lack of depictions of uncontrollable AI threatening humanity in science fiction and popular culture. We believe that with more understanding of the underlying principles of the latest AI algorithms, people will be more receptive to AI technologies. Furthermore, we hope that our project can spark curiosity for AI and computer science in a new generation of students.

Thus, we aim to explain simple deep learning concepts without complex college-level mathematics. To achieve this goal, we have chosen interactive graphics combined with short explanations and everyday analogies. This effectively cuts through the linear algebra and calculus, and exposes the core mathematical intuitions of a simple feed-forward neural network.

OKAI landing page

UI/UX Design

To read more about the UI/UX design process, please refer to the wonderful writeup on Jiaju’s website.