Trends in Tech and Corresponding Complexity Levels

We built a little robot called "There's Waldo" to test the capabilities of Google's new AutoML Vision service. We've found that technologies can be unapproac...

by Leo

It wasn’t too long ago that electronics were something that only large corporations did - the components and materials necessary to dabble in electronics were simply unaccessible to the average consumer, and the learning curve was steep for a large portion of the machinery.

With the advent of Arduino, however, interest in hobby electronics saw a steep rise. Coupled with the push for accessibility, efficient delivery systems, and a focus on consumer satisfaction, electronics were bought to the masses. In the same way that some amateur artists burst into the music scene from humble beginnings, we saw incredible levels of innovation coming from electronic hobbyists with no more marketing than a simple phone video. Electronics became fun to play with and easy to assemble, and as we can see with the so-called useless boxes that only function to turn themselves off, they became more amusing and design-oriented. Rather than simply viewing electronics as a solution-provider, more and more people were using electronics to create simple for the sake of creating.

Today, we’re seeing it return to its roots. Hobby electronics have turned serious and more complex - with innovation came more difficult methods and a drop in accessibility due to the rise in the level of complexity. As electronics become more impressive, the creation of such electronics begin to require bigger teams and more funding, thus returning electronics back to its corporate origins. This is a cycle that will likely repeat for some time, and at this time, I believe thar we can look for the creation of new methods that will reduce the learning slope of today’s complex methodologies.

We can see computer vision and robotics follow the same cycle; at this time, they have recently become more consumer-accessible. In 2019, and likely for the next few years, we’ll see two things: a rise in machine-vision-focused projects, and a drop in electronic ones.