May 4 2015, Flight Cafe East, Toronto 
http://snelting.domainepublic.net/files/flightcafe.MP3

FS: Maybe we can start with the different problems we have been seeing. I've been going through our notes: the voice-over for the video you made, our notes for the bugreport. I am maybe wrong but I see three areas of problems, when trying to think about humanoids in digital space. One is related to the way 3D representations of physical objects in digital space are linked to the way the mesh functions, a very particular way of dealing with inside and outside, and that creates problems I think.
PL: Absolutely. 
FS: The second is related to resolution: the disconnect between the hyper-real and the crudeness of the underlying structure.
PL: Absolutely.
FS: And the third is related to it being parametric. The fact that we are dealing with sliders and so on, and the limited 'space of possibilities' it creates. To me, each of them brings up different problems. Maybe we can go over these three areas. I don't know, maybe you see another entrance somehow?
PL: Well, I think they all intersect as well, from my point of view at least.
FS: Yes.
PL: For me, there is also something about the environment of simulation, the world in which the simulation is created in order to then simulate within, or to represent within or to modify within. And each of these problems you mention in some way speaks about that.
FS: So if you say 'simulation', what do you mean by that, or how do you use that term? 
PL: From my background [as an architect] you have the simulation of a buildings' performance, that is the way I am normally exposed to it so: how much energy would it use, would it be structurally stable, these kinds of questions. In order to simulate  that, you would have a digital model and you run a bunch of algorithms over it that would test solar gain (?), structural stability, things like this. But that digital model is very much a reduction of the most detailed model that might exist during the design process, partly due to computing power, or mostly due to it in fact, you have to simplify the geometry of that building down to boxes, effectively, and that reduces the relationship between two rooms that share a wall and the algorithm does not really care exactly how big that room is, it can't really change with a change in geometry, even in the order of a couple of meters in floor area, it will not really effect the simulation outcome. The simulation I am talking about is of a certain type (?), the constructing of a world in which you test your 'proposal', and very often that is merely talked about as the environment in which you construct, and in a structural simulation it is what kind of algorithms are you using, is it efficient, does it take this into consideration, does it take that into consideration, but very rarely do you see what you need to do to the geometry in order to expose or subject it to the algorithm.
I think there is an almost blindness in the understanding that the nature of the algorithm effects the nature of the model. So in architectural discourse on digital modeling at the moment you have a lot of hyperbole about how this stuff gets way more capable of modeling huge amounts of detail, the model is almost quasi one-to-one, it might have every nut and bolt, the window ledge will be modeled with the exact profile, and there is a fallacy held that that geometry is then translated in the environmental simulation, and will render a better result but it doesn't. The model that you see on your screen is not the model that is actually analysed.
FS: You use the word 'reduction' and I would like to think a bit about that because when we hear about models and try to critique their crudeness, the response is often: “we need more data”, “if only we had more computing power”, “it is a question of efficiency” … Is that the kind of reduction you talk about, meaning is it a problem that can be solved if you would have more data-points or rendering power, so that the reduction could be minimized?
PL: My understanding of this, is that there is a symbiotic relationship between the algorithm that runs the simulation and the structure of that algorithm. It is not that it could ever understand the profile of a window sill or an opening or an overhang. It has been designed with the computing power available in mind to deal with the fact that you just can't …  So, there is a link between the digital environment in which you are simulating, the processes you modify, you have to modify the model, the physical materiality of computing itself. You can't just swap one in and one out. They have been involved symbiotically probably.
FS: It is kind of interesting to think about what it means to design an algorithm with the computer in mind ...
PL: Yeah!
FS: … which in itself does not have to mean a reduction.
PL: No. I use the word 'reduction' and it is pejorative often and I don't necessarily mind it but what I mind is the lack of visibility in that process.
FS: Yesterday I was talking to one of the developers at https://thegrid.io/ which supposedly offers an artificial intelligent problem solving technology for web lay-out. I was trying to talk about the difference between designing with an algorithm, or outsourcing the design to the algoithm. You just used the word 'visibility' but he kept on using 'introspection'. I realised that I am no so interested in that part, of literally 'seeing what it does', but finding a way to be (to use the word of the week) ... in conversation. Which is something else than visibility, it only starts with it I think.
PL: Absolutely, yes! I guess by visibility I mean acknowledging that this is going on I suppose. It is interesting you mention AI because when I worked on neural networks in the past, and you start to understand the history of neural networks and algorithmic approaches, you start to see exactly the relationship between the algorithm and the hardware. So the initial phase, the postwar phase of AI in the US, funded by military, when everyone is getting very excited by hard AI ...
FS: Hard AI?
PL: Meaning you are basically hardcoding it's functionality, it is not really learning in the way that soft AI is seen as capable of learning.
FS: OK.