Bret Victor: Seeing Spaces [video]

BTW, for good reading material on control rooms, look on Google Scholar for papers by Paul Heath and Christian Luff. They're very thorough in their analysis of how people in control rooms communicate and "spontaneously" synchronise their actions.

I can't tell if everyone one is like that (I assume not), but I am extremely reliant on visualization, and I suppose Bret is also. I believe profoundly on it's power partly because it's the only way I can really get things done properly, which is why those tools resonate so much to me. I have a friend however that shudders every time I mention making programming more visual.

I mean, If I'm not visualizing something, I can perhaps find some solution in a logical way following some guidelines -- much like following a recipe to solve a equation or doing trial an error to solve an algebraic problem. But critically, I can't create this way. I may stumble unto something useful, but it's an entirely different process from creativity -- it's efficiency is so much lower that it's qualitatively different.

But my difficulty at that is not fundamental, I think. I believe you can be creative purely 'algebraically', but I have no experience with it -- but I do believe that some people have the same efficiency that I have when I think visually and perhaps stumble a little more when trying to visualize things themselves.

I do think this diversity is quite good, but that's missing the point. My point is that Bret's tools shouldn't be universally essential, but are probably universally beneficial. And for some people, like me, they'd be simply enabling.

To give an exaple: when I see a system of linear equations, I don't think of a bunch of steps to solve them and the number of cases that the solutions may look like in terms of constraints of variables an so on. I think of the Image hyperplane, which can be abstracted as a plane in 3D, and the Kernel, which may be for example a line not on the Image. Then instead I wonder if the Kernel is non-null, what funny things this matrix is doing to the vectors (are they rotating, contracting, and so on), or what are the invariant subspaces. I can answer most questions one could ask about such system, but it's a distinct way, I'm not sure if more efficient or not (and that may be up to the task).

I think spaces like this would do well to incorporate projected augmented reality ala CastAR: https://www.youtube.com/watch?v=GpmKq_qg3Tk

You could collaborate, sharing the same view, or each individual could project different views, or mix and match.

I love Bret Victor's talks, blog posts, etc. They're super inspiring.

2 things came to mind though.

1. It seems, possibly, the exact wrong time to make rooms with giant displays. With things like Google Glass and Oculus Rift as first gen (2nd?) VR/AR you could project all of that info virtually and cheaply and be able to have all the visualization he describes wherever you are, not just at a makerspace that only a few people can use at a time.

2. I'm always super inspired by the Bret's visualizations but when I actually try to figure out how they'd be implemented I'm clearly not smart enough to figure out how that would happen.

In this example in particular, he shows graph toward the end where the system tries every setting and graphs the results so it's easy to pick out the best setting. How would that happen? How does the system know what "good" is? It seems to me it can't know that. You'd have to program it which in itself would be pretty hard. Worse, most system have not just one adjustment but many. Just a few and there'd be tens of thousands of variations/combinations to try to figure out "best".

I'm not saying we can't get there. Maybe the first step is building a framework that would make it easy to make systems like that with various kinds of visualizers, analysers, time-recording, searching features etc, and maybe somewhere along the way we'd figure out how to automate more of it.

I'd love to help work on such a system.

I just wanted to make a couple of comments; 1. I think that when something is new, like Google Glass or occulus rift, we (as nerds) tend to think it's the future because it hasn't been possible before before we have quite worked out when it's most applicable. Giant displays are awesome when you're brainstorming a topic with people in the room, which is what maker spaces seem to be about.

I can see glass being good for things like surgery, where you need to concentrate your attention on something, but would like some extra data to be easily available.

VR might be a substitute for live brainstorming sessions, and it might allow you to visualise in new ways. But latency is going to be killer across remote locations, and that's a big challenge in terms of infrastructure.

2. I'd imagine as these types of techniques become commonplace, we'll have to learn more stats.

You could also apply clustering and neural nets to a lot of data sets, but yeah - maybe we'll all have to become statisticians.