#learningtosee

Even today after years working I'm still learning to see. The design has always been seen as something without the real value it has by the general public. There is a lot of memes on the internet laughing about it. I'm not the first one who has listened to something like that: “You did it in 5 minutes, so you can do it again (for free obviously)”. But well, our work it’s not only to do the work, but we also have to explain our project and the process to reach the solution in a way that can be understood to our audience. It not only needs to be good, but it also needs to look good.

So, coming back to the main topic of the article, I agree with the idea of designing is the first place is observing and questioning. Many times, when I see something I like, I observe it, with two questions, how it was done, and how it can be improved.

I only have to add, that sharing with other designers made me grow. I’ve learned a lot by sharing, and it’s not easy, it’s something that in this, let’s call it “competitive society”, you need to unlearn first, and start learning again with a new sharing mentality.

I have always wondered if what I consider good design would be seen the same way by somebody else. I used to think good design is something that is simply visually pleasing to the observer, so it made more sense to think that good design is completely subjective as we all see things differently. After 2 weeks of starting to get to know the UX/UI Design world, I can confidently say that good design is so much more than being pretty. 

As the “Learning to see” article very accurately says “visual and functional beauty are not completely independent”. On the contrary, they go hand in hand. Even if you had the visually most beautiful design, as long as it didn’t work, it wouldn’t be possible to consider it “good design”. The design concept involves, most importantly, functionality. Why? You just don’t design to make something pretty, you design to make something work. It is only once you make it work that you can start thinking of its aesthetic. Dieter Rams’ “Ten principles for good design” are quite accurate as well when defining what good design means. Only 1 of these 10 principles mentions the “pretty” aspect: “Good design is aesthetic”. Nevertheless, this same principle can’t help mentioning functionality as well “But only well-executed objects can be beautiful.”

The following quote is included in the previously mentioned article and it clearly defines how important was functionality considered by one of the most influential people in the tech world:   “[Design] is not just what it looks like and feels like. Design is how it works”. —Steve Jobs

Interesting right? Moreover, I think this is where empathy gets involved in the designer’s path.  The design has to primarily work for the customer you are designing for, not only for yourself. Can this design “eye” be trained? Definitely. “Learning to see” has a very interesting point:

“With practice your intuition evolves, and the better you understand what you do, the deeper your intuition.”

Realtime Neuratorial Art

Artist Memo Akten has been exploring methods to generate neural network images in realtime. It started with his #Learningtosee project, with a ‘blank’ neural network, not trained on anything, visualizing fresh visual input:

This is a deep neural network that has not been trained on anything. It starts off completely blank*. It is literally ‘opening its eyes’ for the first time and trying to ‘understand’ what it sees. In this case ‘understanding’ means trying to find patterns, trying to find regularities in what it’s seeing now, and with respect to everything that it has seen so far; so that it can efficiently compress and organise incoming information in context of its past experience. It’s trying to deconstruct the incoming signal, and reconstruct it using features that it has learnt based on what it has already seen – which at the beginning, is nothing. When the network receives new information that is unfamiliar, or perhaps just from a new angle that it has not yet encountered, it’s unable to make sense of that new information. It’s unable to find an internal representation relating it to past experience; its compressor fails to successfully deconstruct and reconstruct. But the network is training in realtime, it’s constantly learning, and updating its ‘filters’ and ‘weights’, to try and *improve its compressor*, to find more efficient internal representations, to build a more ‘universal world-view’ upon which it can hope to reconstruct future experiences. Unfortunately though, the network also ‘forgets’. When too much new information comes in, and it doesn’t re-encounter past experiences, it slowly loses those filters and representations required to reconstruct those past experiences.   

More Here

Following from this, he is using the same realtime method but with a neural net trained on art collections from 150 museums:

#DeepNeuralNet #LearningToSee (havin a hard time cos I'm playin w LR momentum gradclip etc in realtime - no post vfx, all from the DNN)

Here is a link to a video where it re-visualizes a drawing in realtime [EDIT 01/05/17 - Video now uploaded to Vimeo:]