Juno + Ballio

This time, I was inspired by Josef Albers’s “Interaction of Color” 

Josef Albers’s Interaction of Color

For this exercise, I was experimenting with using random()for various fills and the type. I was also trying to see how animation, timing, and frame rate works in drawbot. Lots to explore and play with.

This reminds me of one of my favorite books we read to our children, Albers’s Squares and Other Shapes, before working on this design with Juno. Highly recommended.

Here’s the code if you all want to play with it:

NFRAMES = 50

for frame in range(NFRAMES):
    newPage(1000,1000)
    frameDuration(1/7)
    
    
# set a blend mode
    blendMode("hardLight")

# draw a rectangle

    fill(random(), random(), random(), 1)

#    x    y    w    h
    rect(100, 100, 400, 400)


    fill(random(), random(), random(), 1)
    rect(500, 100, 400, 400)

    fill(random(), random(), random(), 1)
    rect(500, 500, 400, 400)

    fill(random(), random(), random(), 1)
    rect(100, 500, 400, 400)

    fill(random(), random(), random(), 1)
    rect(300, 300, 400, 400)

    # set a font and font size
    font("Futura", 200)

    # set a blend mode
    blendMode("overlay")

    # draw text
    fill(random(), random(), random(), 1)
    text("Juno", (140, 630))
    fill(random(), random(), random(), 1)
    text("Ballio", (130, 230))
    
    
saveImage(u"~/Desktop/drawBotTest.gif")

Drawing in Python

I’ve been drawing computationally with Drawbot in Python 3 out of John Maeda’s encouragement and teachings. Much gratitude to John… I’ve been posting some work-in-progress on Twitter, but thought it’d be nice to post it on my blog too as a nice collection of trials, experiments, fails, surprises, and some really cool things that came out of playing with code. 🙂 Stay tuned for more posts on this blog!

First up, this is one of my favorites so far. I love how the colors and dots spiral into this beautiful pattern. I love it so much that I made it a shirt and a sweatshirt on Amazon! Support art, buy a shirt today. 🙂 I got one to check out the quality and I can confirm that it’s very comfortable. The print quality is ace, too!

5000×5000 high res glory

Ballio wearing his computational art shirt.
It’s a real shirt! 🙂 Buy one today!

I’m looking to make more computational design shirts too! Stay tuned for more new designs.

In the subsequent posts, I’ll be sharing my fun exports mostly from Drawbot. As well as a few creative experiments I’ve been noodling with.

Check out more of my journey in computational art.

Google Doodle — Tyrus Wong

A close friend informed me today that Google doodle is honoring Tyrus Wong for his 108th birthday. This is the video that they made:

If you all didn’t know, Tyrus Wong was an

Chinese-American artist responsible for some of the best-known images in American popular culture. Drawing inspiration from Chinese artists of the Song Dynasty, Wong applied his unique vision to paintings, prints, and even the Walt Disney film Bambi.

I had the honor of meeting him and attending one of his kite flying events a few years ago at the Santa Monica beach. The craft of his kites were one-of-a-kind and amazing:

What an amazing tribute. 🙂

Computer, do my design work.

This is a piece I first wrote for Automattic’s Design Voice blog about the future of design and marketing:

Imagine you step into your car for your morning commute, then the car starts driving itself. You realize you need to make a stop at the cell phone store, so you tell your car. You walk into the store where you’re greeted by a shiny humanoid who offers you the latest model of its product. This is NOT the future, it’s the present.

We live in the age of self-driving cars, humanoid robots that replace human sales associates in Japan, websites that design themselves, and even an AI creative director that makes come up with sticky commercial ideas. This is what the “future” supposed to be like, so…what is the future of this future?

As a marketing designer at Automattic, I think about the future quite a bit. It’s part of my job to think about how we can adapt to the ever-changing needs of our customers while communicating to them the value of our brand and products. Culture and trends evolve at the speed of light and we need to keep up.

We are challenged by our Head of Computational Design and Inclusion, John Maeda, to solve this problem with computational design thinking. In order to create an expansive amount of fresh creative work in a timely manner, we need the help of computation. Automattic is a company that is known for its engineering, how can we leverage this engineering thinking and culture in our design discipline? Here are a few ways I think we can:

Think like engineers

One way we can do it is by treating design more like engineering. Prototype our work with fast rough ideas, then iterate on it with real world user testing and continual refinements of the design. We can use tools like Abstract for Sketch to allow for an agile versioning and reviewing process. Love an idea you see? Fork it and make it your own. There’s no such thing as a perfect design anymore in this time of Snapchat and new media. People want things that are personal and new. We need to learn from our engineering counterparts to combat this.

Software as tools for creation

Another way is to literally rely on our machines to create our designs. We have access to an immense amount of data internally and externally. User trends, product usage, trending hashtags, etc. Let’s use that data to create software that lets us scale our designs. With generative programming languages like Processing, OpenFrameworks, and even JavaScript, we can create numerous designs that are new and fresh based on different inputs and variables.

Software as tools for efficiency

We create software to help us be more efficient. Instead of doing the same arduous task multiple times, we can automate these tasks with our computers. We are building systems that helps us compute and automate repetitive tasks like resizing a design in multiple sizes and mediums for advertising, or localizing copywriting in various languages for our global customers. The next level is to analyze our data inputs, while making creative autonomously for our various customers with different interests, geographies, and needs. My philosophy is always to work smarter, not harder. Using computational power frees us time to focus on things that machines can’t do — like marketing and brand strategies.

I 💙 the future

I look forward to a future when we can talk to our computer and say, “Create my next comprehensive multi-channel marketing campaign for next spring.” But before that, I am enjoying this near future which we can learn from our engineering counterparts and leverage the power of computational thinking to help us create work that keeps up with the market trends.

Featured image by Automattic’s Mark Uraine, generated using Processing.