#748: Visualizing Cyclical Time in VR With Helixaeon’s Time Helix

alex_bowlesHelixaeon’s Time Helix has a unique way of visualizing time-based data as a fractal-nested helix. Helixaeon was recently awarded US Patent #10,185,933 for their interactive, multi-dimensional data visualization that’s able to “generate a representation of the length of time as a view of a three dimensional (3D) helix wherein each revolution of the 3D helix corresponds with an iteration of the cyclic period.”

I had a chance to talk with Helix co-founder Alex Bowles at Oculus Connect 5 about how visualizing data displayed as cycles of time can help to detect underlying patterns in sets of big data, but also provide a direct embodied experience of complex systems such as the threats that we’re facing from climate change. Helix is moving beyond the linear depiction of time and their innovative Helix visualization of cyclical time has the potential to help us understand more about our past as well as understand predictions about the future so that we can make better decisions today.


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Music: Fatality

Rough Transcript

[00:00:05.452] Kent Bye: The Voices of VR Podcast. Hello, my name is Kent Bye, and welcome to The Voices of VR Podcast. So on today's episode, I'm going to be doing a deep dive into time with Alex Bowles of Helix. So Alex has created this startup in order to look at time-based data in a spatialized way in a way that's kind of like a fractal visualization. You have a spiral, but then you can have spirals within spirals. so that you're taking something that is somewhat abstract and you're giving a specialization to time-based events. And if you do that, then you just have a deeper intuition as to what the relationships and the meaning within that data set is. So time is a bit of an open philosophical question because it's kind of mysterious as to what exactly it is. I mean, you can look at space and time and how they're related, but then There's our perception of time, our phenomenology of time, and that's different than the actual physics equations. You look at the physics equations, so many of the equations don't even matter that time is a thing. You have this sense of an arrow of time. But the only thing that really points to that is entropy and heat transfer. And yeah, it's just mismatched between what the physics says it is and what our experience of it is. And for anybody who's been in virtual reality and been in the experience of super hot, you know, how compelling it is to be in an experience that actually slows down our normal experience of time or any VR experience that starts to do like these time-lapse experiences. There's been some time-lapse footage and a number of different Felix and Paul pieces, both in the white house, as well as the. Isle of Dogs experience that they did where they were really playing with this changing of the unfolding of time in these time-lapse sequences, but also in Superhot, how you move your body actually changes your experience of time. So there's something about the unique affordances of virtual reality being a spatial medium that because space and time is so intimately related, it's going to potentially change our relationship to time as well. And that's what Alex has been thinking a lot about, especially in what are the different pragmatic applications when you're able to add the magic of embodied cognition to the spatialization of time. So that's what we're covering on today's episode of the Voices of VR podcast. So this interview with Alex happened on Wednesday, September 26th, 2018 at the Oculus Connect 5 conference in San Jose, California. So with that, let's go ahead and dive right in.

[00:02:27.135] Alex Bowles: Hi, my name is Alex Bowles. I'm co-founder of a company called Helix. We are developing applications that allow people to work with time and time-based data with the same intuitive ease that they can work with space.

[00:02:38.524] Kent Bye: Great. So you're doing, in some ways, the spatialization of time, giving a geometry of time. So maybe you could tell me a bit about what inspired this and what you're able to do once you specialize time in that way.

[00:02:50.840] Alex Bowles: Well, I think calling it spatialized time is exactly right, and I would invite any of your listeners to go and take a look at our website simply because it's much easier to see it and understand it than it is to just describe it. We're at helixtime.io, but the basic form that we're using is a nested heliacal form, and we're using this to visualize time for a few reasons. One is that a helix provides both a linear and a cyclical view of time in a single object. So we're able to take the two predominant views of time and combine them into a single thing. The issue with a single helix, though, is it only shows one measure of time. You really can't show all of time or multiple units of time, which is how we typically deal with it, you know, in any sort of applied situation. So what we've done is created a nested arrangement. So if you can imagine the axis of a helix being curved to form another helix, you can start seeing how one helix nests inside the other. You can also take your original helix and use that as an axis. to wrap another smaller helix around the line that it forms to get a nesting arrangement that goes in the opposite direction. And what you end up with is this structure where the loops at one level can represent time units at one level and that the loops at a larger level can represent units at a larger level. The really nice thing is that these are independent, so there's no necessary relationship between numbers of one and numbers of the other, meaning that you can use the same form to represent any combination of intervals that a particular data set might require. So you can use this with financial data, you can use it with geological data. The same basic structure works regardless of the time frame involved.

[00:04:29.869] Kent Bye: I know that there's these different interesting things that'll say, oh, we're closer to this date in the future than we are to, like, something that feels like the 90s. And we don't have a good sense of spans of time, because, you know, we have this sense of linear time, but yet, to give lengths of time, once you get a certain age, and you're like, oh my gosh, the 90s was like 30 years ago, and that we're closer to, like, 2045 to, like, 1990 or something like that. What's the benefit of being able to actually add space to time and be able to visualize it? And what are you able to do with this then?

[00:05:06.376] Alex Bowles: So we see this as a very general purpose technology. I mean, the basic value of immersive technologies in general is that they're able to tap embodied cognition. For any of your listeners who aren't familiar with embodied cognition, it's basically the viewpoint that our cognitive processes are deeply rooted in the way that we interact with the world physically. And this includes our abstract thinking or what we think of as our abstract thinking. It turns out from a neurological perspective, it is actually very, very deeply rooted in the processes we use to make sense of and operate in the world. And to give you the textbook example of what embodied cognition is and how it works, there's something called the outfielder problem. An outfielder sees a ball being hit, needs to know exactly where and when to be to catch that ball, and does not have the ability to do what a physicist would do, which is to quantify the inputs to the system, look at the speed of the bat, the speed of the ball, and calculate where the thing's going to land. What they're doing is very, very different. They're taking an embodied approach. So when they see the ball move across their field of vision, they're watching the ball move. But as soon as they start moving, their field of vision moves with them, and they can essentially cancel out the motion of the ball with their own motion, specifically in a way that will keep the ball parked in the center of their field of vision. And if they can keep it there, they can follow it as they're running, they can keep it, they can basically lead the thing right into their glove. So this is an example of how we use embodied cognition to solve a problem. We're actually physically a part of the system in which we're trying to solve something that we're doing. And we're incredibly good at this. We've got millions of years of evolution that are helping us do this. And what's amazing about immersive technologies is that they give us a way to blend computing power with this natural ability that we have. So instead of interacting with data and information structures using keyboards and mice and so on, you're actually able to work with these things using this physical ability that we have to make sense of the world around us in this very natural intuitive way. The issue when it comes to time-based problems, however, is that we don't have an object and that embodied cognition requires some sort of object for us to work with in this fashion. I mean, we need the ball in order to like know where to run to. So what we recognized was that by taking time, which lacks both position and form, and giving it both, we could create an object that would allow people to bring this power of embodied cognition to a field, basically time-based problems, where we have not been able to apply it in the past. And this can, again, work in areas where the spans of time are very small or they're very large. But in either case, we're able to give people an ability to think about and understand stretches of time that we don't have an ability to think about intuitively otherwise.

[00:07:51.353] Kent Bye: Yeah, I've been playing around with different ways of translating all of space-time into a memory palace, and so in order to have a sense of time and history, if you add spatialization of that, and you have one approach, I have other approaches that I personally use, but You are, in some ways, creating this ability to change my concept of history in a lot of ways. And I'm just curious from your own personal experience of working with this, how has that changed your relationship to time and how you're able to remember different things that happen from a more historical perspective in terms of when things happen?

[00:08:25.906] Alex Bowles: So we're still working on the basic interaction structure to get the embodied side of this worked out nicely. So I have not been able to apply this in the way that you've described yet, which is something I deeply, deeply want to do. I mean, my background was in the history of mathematics and science. So thinking about how ideas and our understanding of the world to develop over these large stretches of time is something that has taken a long time to develop if you just read books and do it that way. If you can actually see how this stuff plays out though, you get a much more visceral sense of it. And I think the concept of the memory palace is exactly right. One of the characteristics of embodied cognition is that we look for ways to offload cognition into the world around us. Memory Palace is a classic example of that. So if you can provide people with a framework into which they can then assign specific events, durations, operations, sequences, and you can give them a sort of a spatial structure, they're able to see them and remember them in ways that they can't otherwise. So yes, the idea is that you do develop a much clearer picture of whatever data set you're looking for, and specifically whatever intervals it contains. And again, you're able to think about this and to feel this and to work with it in the way that we work with our natural surroundings, which is something that is very difficult to maintain when you're dealing with large stretches of time. I mean, you get this collapse that happens once there's too much or too little of it. Our minds simply can't process it, which is not to say that our minds can't process the relationships. I mean, for example, you could stand on the edge of the Grand Canyon looking at your watch and then also looking at this enormous vista. So there's this enormous range of scales that you can perceive. One of our problems, though, is that we don't necessarily have mechanisms to assign value to those different scales. So if you're looking at, say, a traditional calendar or a traditional timeline, you're still looking at it in a very limited frame. A classic example here is the Powers of 10 movie by Charles and Ray Zemes, which was designed to show people how exponential functions work. And it starts with an overhead view of a couple on a picnic blanket by the side of Lake Michigan. It zooms out, so you're now looking at a frame 10 times larger than the size of the picnic blanket. You can now see more of Chicago. It keeps zooming out, and pretty soon you're looking at the entire galaxy. But the problem with this is that it's still an illustration. It's not an experience. As a viewer not moving in space, the frame is not moving, you're not actually physically looking up or changing your perspective in the way that you would be if you were, say, in Yosemite looking up at El Capitan or on the rim of the Grand Canyon looking out at this enormous vista. So you're not actually engaging your body in making sense of this information and making sense of these relationships. So the result of this is still quite abstract and still quite limited. What the value of immersive technologies is, is that they give application developers the entire field of view to work with, as well as three dimensions. So you're actually able to render information with the scalar relationships that you might see in a place like Yosemite or a place like the Grand Canyon. And by using a structure like the Helix, what you're looking at is not a geological structures, it's It is itself an abstract structure, but you're able to present scalar differences in a way where you can actually understand how the different time spans are working well beyond the point where they normally collapse. So you're not struck by the idea that the Romans were as far away from the Egyptians as we are from the Romans. I mean, I think a lot of people tend to think of ancient history as one sort of block in the same way that they might think of all the stars as being roughly the same distance because that's how they look to us. But, you know, in fact, the stars that we see all forming what appears to be a single dome are, in fact, you know, an enormous range of differences. And it's the same thing with points in time historically. This, I think, gets really interesting when you start going the other way, you start looking into the future. When you start mapping events that we can be fairly sure are going to happen, or a range of events, but outside of a range we normally think about. You know, obviously with things like climate change, it becomes a huge issue. One of the groups we've been working with initially was a group from the University of Colorado doing research on El Nino. and they've had a problem in communicating with a lot of the policy makers who are impacted by El Nino when it comes to just the scale of this event and how this event plays out and the way that the impacts of the El Nino system itself can be quite far in time from the secondary impacts that come from the consequences playing out in natural and economic systems. And by being able to show a bigger picture of how all of this stuff works together, these natural systems, social economic systems, and then tie that back to the individual level and the lives that policymakers are generally having to think about and deal with, they can start to get in a visceral sense of how these systems are actually working, what their own capabilities are in relationship to them. and ideally prepare for them better. So, you know, we found that some of the people who have been most interested in using this are people who basically have communications problems. You know, you have scientists, for example, who understand this data deeply. They know what this means, but they've spent years, if not decades, building up that understanding. they don't necessarily have a way to convey what they understand to people who don't share the same background. And so what we've discovered with the Helix is that it provides a way to sort of fill in that context very, very quickly. So you're able to communicate problems that function on scales or with ranges that most people can't grasp without extensive study. Within this framework, you can convey the idea almost instantly. So we see this as not just a way to work with data and to understand data, but to reach conclusions and then to communicate those quickly and swiftly.

[00:14:25.307] Kent Bye: And so I know that you showed me a little graph that you were charting different aspects of your day-to-day life, kind of like a quantified self exercise where you're trying to categorize different dimensions of your flow of time over the course of many days. And so maybe tell me a bit about that experiment and what you were able to find when you were kind of looking at, you know, different aspects of your own time.

[00:14:47.280] Alex Bowles: I think one of the remarkable things about it is that you find you have both less and more time than you think. The way we perceive our own time is, I don't want to say inaccurate, but there are perspectives that are very, very different from the way we experience it normally. One of the refreshing things I think when you're able to look at an entire lifespan is to see how much time you have. You actually realize when you start looking at something that's got 10, 20, 30 years perhaps, that you can take on projects that are maybe more ambitious than you would think about otherwise, that you've got time that you didn't think you had. So in one sense it can actually be very liberating, you know, because you're out of this sort of immediate day-to-day rush. The flip side, though, is that once you start quantifying what you actually do with your own time, how much time you spend sleeping, eating, et cetera, et cetera, you find that the intervals you actually have to yourself are relatively small. So you see that you have less time than you imagined on a day-to-day basis, but a longer stretch of time overall. And I think this can lead people, I know it's certainly led myself, to value your time quite differently. and to approach what you're doing in those moments that you really have to yourself where you do have latitude quite differently. You think a lot more careful about wasting them and you also see that they can accumulate to something that's probably a lot bigger than you imagined. I mean, I think this is what financial planners will tell you with compounding interest. It seems like a small number to be putting aside every month, but over 10 years, it can accumulate to something pretty dramatic. And I think if you can see that in terms of your time, it changes your perspective of what you can do with your life and what you have the ability and at least the space, if you will, to do.

[00:16:34.296] Kent Bye: Yeah, another metaphor that comes to mind when I think about this spatialization of time and the way that you've done it in this helix is that in music and audio there's a fast Fourier transform where you're translating frequencies where you're able to actually visualize the different tones that are within any sound and that In some ways you're doing what is kind of like a fast Fourier transform to find those frequencies, but you're spanning it over a much larger span of time. So you're able to maybe have a visual representation of cycles of like the moon is a good example of the new moon and the full moon is just an example that happens over the course of a month. that you'd be able to maybe plot out and see the lunar cycles of when the full moon and when the new moon was. That would be something that you'd be able to transform into a 3D spatialization of that. That would be kind of like the equivalent of a fast Fourier transform, but over a much larger span of time. So you're able to, if you're a financial planner or trying to understand different dimensions of the boom and bust cycles within the economy, maybe you'd be able to plot out different dimensions and signals and then plot them in this spatialized way, and maybe you'd be able to get ahead of the market or see a trend before it actually takes place. And so I'm just curious to hear your perspective on that in terms of being able to detect these types of cycles and what you're able to do with that.

[00:17:51.039] Alex Bowles: Okay, so this is easily one of the most exciting things I see about this whole thing. And specifically its ability to look at the macro and the micro at the same time. With most of the ways we represent time, flat two-dimensional systems, calendars or clocks, Generally on printed but now on screen media, you're still bounded by scale. So with Microsoft projects, for example, you can look at an overall map of the project or you can like zoom in, but it's very difficult to actually see and account for both at once. You kind of have to be in one place or the other. When you've got the full field of view in three dimensions to work with, those problems go away. So you can start to chart data that plays out on this very, very large scale, and you can combine that with data that plays out on a very, very small or a fast scale, and you can keep both in view at the same time. And at this point, you can start to see how very long-term cyclical effects may be playing out or governing what's happening on a microscale. And it may not have predictive power necessarily, but it can give you a range and you can start to understand what is possible within a moment. Not necessarily what will happen, but what can happen. And you know, I think this obviously works for financial planning if people are trying to look at large macro trends in the market, historical data, and they're trying to nest what's happening with a particular company inside of that. It can also happen with scientific data when you're looking at large planetary systems and how these work and how they either narrow or open our options in terms of resilience planning at different points in the world. So anytime that you need to understand the interplay between the macro level and the micro level, You've really been stymied by a lot of the representational technology we have up to this point. So getting back to the idea of in-body cognition and the idea that we like to offload our cognition, we've only been able to go so far with this and the limits have largely been imposed by the media that we use. But when we actually have a media that again is working in three dimensions, it's fully immersive and it taps the power of embodied cognition, then all of a sudden we can start representing data in ways that allow us to essentially offload far more of the stuff that we want to think about and make sense of bigger problems and more complex problems that we've been able to use in the representation systems we've had to date.

[00:20:12.672] Kent Bye: Yeah, I wanted to ask you about Carlo Rovelli and his conceptualization of time, because I feel like we have this sense, like an Antonian sense, that there's a flow of time, and that in The Order of Time, which is Rovelli's book and a lecture that he gave about the philosophy of time, he says, well, actually, Aristotle had probably a little bit better conceptualization of time, which is just a measure of changes that happen. And so it's more of a process rather than an object. that when you dig deep enough into the physics of time, if you look at all the different physics equations from electromagnetism to the standard model to like general relativity to quantum mechanics, like there's no time variable in any of the major equations for physics and that Revelli was like, well, the time is actually coming from your brain, like from a neuroscience perspective, it's a bit of like your brain is a time machine where it's able to have this experience in context where it's drawing from memories to give you this experience of continuity of time, but really at the quantum level and from a physics perspective, it's kind of like energetic patterns that are in relationship to each other. So it's like a completely different conceptualization of time. I think of it as a metaphor as each city used to have like local solar time. So like Whenever the sun was due south, that would be the midday, and then that would be their noon. So that would be their noon. But then whenever they had trains, people trying to travel from place to place, then they had to have time zones to be able to coordinate the train going across large, vast distances. So now we have time zones. Not only that, we also have atomic clocks. So like globally in the internet, and from a security perspective, you actually have to have synchronized time in order to have secure internet. So we have embedded into our technology this concept that there is a time that is universal time. But Ravelli would argue that even from the point in your head, from the point of your toes, the difference gravitationally is enough to say that there's actually different time at every point in space. So time is relational in that way. So how do you account for this different concept of relational time that's dependent on the observer of where you're at in a space, or if the approach that you're taking now is kind of assuming this Newtonian universal time, or if there's some way to account from this relational aspect of time?

[00:22:30.516] Alex Bowles: Wow, so a lot to unpack in this, but I think the essential point that Raveli is making is that we as observers are essentially producing time. that time is almost the byproduct of our experience of phenomena that's happening around us. And I think this is sort of dovetails with what Immanuel Kant hit on when he was looking for what he called the a priori conditions for experience, the things that we experience before we can experience anything else. And in his assessment, they were time and space. And you can almost imagine these sort of these empty matrices that the mind uses to compose an understanding of the world and our experience within it. This was a philosophical intuition when he hit on it in, what was it, 1783 maybe? 1789? But it's subsequently been proven out by neurological study that is actually looking for the specific structures in the brain which are responsible for understanding of space and time and it turns out they are in fact very, very closely connected. The exact connections are not clear yet, but we're zeroing in on them. And it's also clear that these things really do provide this framework for understanding everything else about our experience. So, you know, I think Ravelli is exactly right in describing this as time as a product of our experience of nature, not something that's within nature itself. So, with something like the helix, you're able to take the thing, which is essentially a human experience, and you're able to essentially give it form and to put it outside of ourselves. So we can see with it, we can see it, we can work with it, we can deal with it objectively. The developments in network technology that have happened principally since 1970, the advent of Unix time, and I think that was the first time that the world had a specific, consistent, universal clock. I mean, it was mostly for machines, mostly for people, but at this point we're all pretty much using it. It provides a layer of data, if you will, about the world that does have a universal timestamp to it. So you do have this ability to take a very personal experience of time and to interpret information that we all regard as synchronous within it. So you can use this in the same way that you've typically used calendars. I mean, calendars and uniform systems of keeping time have generally been instituted for social reasons to literally keep everyone on the same page. I mean, the example of railway time was a more recent example, but establishing calendars as a foundation of civic management. I mean, this goes back to the Julian calendar and the Romans. So we at this point have incredibly precise and very, very widely shared frameworks for keeping time and for assigning data to specific points in time. What we don't have at this point is a really good way of understanding that and interpreting it on a human level. I mean, the amount of data that is getting produced is growing exponentially. I don't know what The exact numbers are more has been produced in the last two years and in the entire human history up to that point. And this deluge is largely incomprehensible to most people. So we see the helix as essentially a form of cognitive augmentation. It provides people with a way to start making sense of this information in human terms. And because you are within it, and you're using your own scale in relationship to what you're seeing to make sense of it, you're bringing this whole thing back to this personal point of origin that time has you're able to take this enormous amount of data and relate it to these linear and cyclical forms that we have sort of intuitive understanding of but instead of having it in your head you're able to like have it in the room around you and when you're dealing with this with say augmented reality for example and people are wearing glasses and they're using multiplayer so they're all looking at the same object they can treat this as a a thing, like a table or a car or any other object, and you can work with it in this sort of externalized way. So if you're able to take this data, give it this very, very human form, and then literally put it on a table around a bunch of people, we can do what we do best, which is working from multiple perspectives to understand a problem and to find solutions that we couldn't otherwise find on our own. So by creating a bridge, if you will, not even a bridge, because a bridge is two-way, a way to triangulate between our individual perspective of time, enormous amounts of data rooted in time, and groups of people trying to solve problems in time. You've got a focal point or a mechanism to, I think, start handling and addressing a lot of the issues that we're starting to face, that we haven't really dealt with as people, as companies, as organizations, as a species before.

[00:27:17.807] Kent Bye: Yeah, just your description there of Kant and the conceptualizations of our time, it reminds me of the Greeks had two words for time, the Kronos time and the Kairos time, and it feels like I've always referred to the Kronos time as like more of the linear time because it's like things that are almost coming from your mind, you're using this kind of universal flow of time to schedule things. that the Kairos time seems to be more of a quality of the moment rather than the quantity the quality and I've called that cyclical time and as I've just been thinking about it here in the moment in this conversation that There's cycles that revolve around memory So you may be in a situation that reminds you of another time and that that is kind of like a meaning structure that you're putting on top of things but it's taking you almost like your time traveling into another moment and And then it's reminding you of another time that you were in. And so there's this experiential dimension. And so like you were saying, like Ravelli was saying that the time is kind of like this experiential dimension of how humans move through space and time, but yet at the level of nature itself, that it's kind of agnostic to time and that a lot of the physics equation actually work. both forwards and backwards, it's just like the second law of thermodynamics of this increasing entropy over time is like one of the only equations that has any conceptualization or anything to say about time at all, is to say that if there's heat transferred, then that's some dimension of measuring time that we can all kind of agree upon. But just this Kronos and Kairos time, the linear time of the Kronos and this cyclical time of the Kairos, thinking about those cycles as our memory and what it reminds us of. And so I'm just curious to hear your perspective since you are creating a visualization of cyclical time, like how you conceptualize this difference between the Kronos time and the Kairos time and what cyclical time even means. Wow.

[00:29:06.859] Alex Bowles: Okay, so I think I see it a little bit differently. I mean, I've thought quite a bit about Kronos and Kairos. I tend to see Kronos in sort of the Newtonian point of view, where you have this abstract, rigid grid. I mean, it's not rigid because there's movement in it. I mean, you've got the arrow of time moving through it, but it doesn't stop, you know, for anything. And I mean, I think what the Greek conception of this was a a giant that was eating its own children. I mean, it's actually pretty grim. But essentially, this is this relentless onward march of moments. And I think you can perceive cycles in this. You know, you can see this December following last December, following the December before that. So you do have a cyclical component in it. I mean, you can choose to look at it Kronos in a cyclical way, but what you can't get away from is the relentless motion of it and the way it just moves on this incredibly steady fixed fashion. That differs quite dramatically from our perception of time throughout the day, which can drag on. It can get long. It can get slow. It can get short. It can get long. I mean, the way we see time and the way we respond to time in the moment is very different. I think this is, again, gets into what the Greeks called kairos. And we don't have a word for it. The closest one, I think, is timing. versus time. You know, you're looking for the moment that is exactly right to act. So, well, since we're talking about baseball earlier, chronos refer to the time that the game is supposed to start. And if it starts on time, then all is well within that aspect of time. And that's something you can schedule and you can plan, but you can't plan, certainly not in advance, when it's going to be the exact right moment to swing at an exact right pitch. You have to be in the moment and you have to be looking at events that are changing sometimes on, you know, second by second to decide exactly when to act. And this is, again, something that we have, as people, developed a very, very good intuition for. You know, we're very, very good at identifying the exact right moment to act, to do something, to predict what will happen if we do something now versus too soon or too late. You know, maybe not well enough to play ball in the major leagues, but it is something we do on a regular basis. The issue with Kairoso is that our ability or our capacity to work in this way falls off quite quickly. We don't necessarily have the ability to bring this sort of very fine-tuned intelligence perceptual response cycle to events that are outside of what you can almost say what we evolved to deal with just to stay alive. So, you know, if we're dealing with what are for us very, very large and slow-moving systems, we can chart these changes, we can express them in terms of chronos. We can look, for example, at the accumulation of carbon in the atmosphere over the course of decades. Chart this with extraordinary precision, but it's not going to affect us in a way where we think oh my god We have to like do not just something now, but we have to do specific act here in order to respond to this because Again, these sort of very abstract views tend not to connect with this visceral stimulus response system that seems to be the focal point of Kairos and So what we're hoping with the Helix is that you can start presenting this information in a way where we can start taking these much more abstract fields of data, things that have resided up to this point, sort of in the Kronos, and bring them into the Kairos.

[00:32:37.338] Kent Bye: Yeah, the way that I, as you were just describing that, the thought that came up was Daniel Kahneman's Thinking Fast, Thinking Slow book where if you kind of think of a metaphor of artificial intelligence, there's like traditional symbols and rational logic, the computer programmers that are actually code up an algorithm and that that'll be one way of writing a program. Another way of doing a program would be a much more machine learning approach where you create a neural network architecture and then you curate a set of data and then you give that neural network architecture an experience of that data and then you're able to make inferences based upon the experience that you have and so there seems to be even just the way that our brain is architected from the left brain right brain sort of a rational thought that you're kind of deliberating all the different mental abstractions of something and that could be perhaps a little bit more of the Kronos approach coming from the mind versus what's coming from the body in your experience of the more machine learning approach of the gut instincts that you have that you're just making as a snap judgment and that being much more in the kairos and that our relationship to time tends to be very chronos driven something that is coming from the mind but turning it into an experiential dimension of something that we have a little bit more of an intuition around so if we are able to have this embodied cognition of these different events that are happening over time, maybe it'll allow us to actually input time and reflect upon it in a more of an experiential way, and that we're able to perhaps tune into our deeper intuitions, to be able to make those snap judgments based upon having a new reflection upon events that are happening over time, but that we have these spatial experiences of it that are allowing us to have deeper insights into time-based events.

[00:34:16.603] Alex Bowles: I know a lot of these interviews end with, what is the ultimate potential of this stuff? And I think we're getting very, very close to that with this question. Because, I mean, what we've seen in terms of like the basic operations people would use with the Helix, we tried to sort of just generalize this as much as possible. It came down to three basic things. One is simply assessing information, just looking at the view. Imagine you're standing on the Grand Canyon, just looking at what's there, seeing patterns emerge. The system itself is something where we've tried to establish a very basic framework of commands that are universal so that regardless of what data set you're looking at, it could be microseconds, the way that people actually interact with this data to select a particular range of information to filter it according to some criteria versus another. That's all very, very consistent in standards. So you have a very uniform, consistent way of working with time, regardless of what the intervals are. And the idea is that once you start getting comfortable working with time on one level, and you start recognizing that that can apply to larger levels. So you start developing a sort of an almost physical fluency with time scales that are much, much bigger than anything that we can normally perceive. The other two things that you do once you've looked at something is you make a decision, and you make some choice. And maybe you're doing this in a group, you're reaching consensus, and then deciding, or maybe you're just making the choice on your own. But in either case, you're making an assumption about what you've been seeing during the assessment stage, and then you're going to test that. and you're going to see how your decision plays out and whether or not it was correct or whether or not you need to adjust it. So you can kind of look at it like jumping into a river. There's the river, there's the moment you jump, and then there's what you do once you're in the river to correct your course. And if we're able to create a framework where people can start feeling comfortable with cause and effect relationships on scales they're not normally able to work with, but are able to apply the understanding they may have developed using this on a much more local scale, then yes, we do think that people will eventually be able to work with much, much larger, deeper, more complex events in the way that they work with stuff that's small, local, sort of on the human level. And they're able to do that specifically because they can see how decisions are playing out over time and essentially correct as they go.

[00:36:37.088] Kent Bye: And so what are some of the biggest open questions around this interface with time or some of the biggest problems that you're trying to solve? I think people.

[00:36:47.030] Alex Bowles: People are the biggest problem. One of the most interesting things about dealing with user interaction for immersive systems is that you have so many more edge cases. When you're dealing with UX and UI for you know, a laptop or a phone, you're dealing with a very, very constricted range of options. And even there, you can see what a big deal accessibility is. I mean, it's a huge deal and you realize, oh my God, accessibility problems are major, even within these very, very limited channels. When you start working with a much broader range of inputs, Gesture, eye tracking, voice tracking, all of the ways that embodied systems track people in order to get information, in order to get the inputs, you find that there are so many more edge cases. And these go beyond the physical differences between people to cultural differences. Gestures mean different things in different languages. So you have to essentially localize your application potentially to respond to the way that gestures function, the way people use their hands to communicate and to work in different languages. So, I think one of our bigger problems is actually on the human side, and to create something that feels like a truly universal human interface. The data side is, in many ways, easier, and I don't want to keep that relative, it's not an easy problem, but I think getting the human interaction side worked out is the thing that needs to be right because ultimately it does need to feel intuitive. If it still feels like an abstract system and you're using abstract representations, you're not really understanding on a visceral sense, you're not building up this deeper intuitive sense of how time works, so not quite delivering. So it's very important to get the human aspect worked out in order to make this truly effective.

[00:38:33.631] Kent Bye: Great. And finally, what do you think is kind of the ultimate potential for virtual reality and what it might be able to enable?

[00:38:42.614] Alex Bowles: I think when I think about virtual reality in general, I think of it as essentially augmenting our senses. I mean, there's this conception of the Umwelt, I hope I pronounced that correctly. I think it was a German biologist, late 19th century, basically used this to describe the sum total of any biological organism's awareness of the world. It could be a cell, it could be a tree, whatever biological organism you're talking about, it has some awareness of the world around it. And if you add all of that awareness up, you get this picture of the human world. I think where people are right now is a point where we're recognizing that our perception of the world, the sum total of it, is vastly smaller than our effects in the world, especially with regard to effects that ultimately come back and affect us in some way. So in many ways, we're just going at it blind. And our sensory systems, the way we think about, the way we perceive the world, simply are not up to the task. operating in the world in the way and on the scale that we're living and functioning now. So I see immersive technologies, virtual augmented reality, as ways to essentially augment our perceptual, our cognitive abilities so that we can actually think and adapt and live with perception that matches the scale of our impact. And if these technologies can do that, fantastic. If they can't do that, then I'm very worried because we need to, and I don't know where else that's going to come from. So I sincerely hope that that's the potential that we reach.

[00:40:15.880] Kent Bye: Great. And is there anything else that's left unsaid that you'd like to say?

[00:40:19.747] Alex Bowles: I will say that we are developing this application to be a general purpose tool, that we see applications for it in fields from education, to finance, to healthcare, to the sciences. Our main hope is that we're able to take a whole range of fields that have not necessarily been places where immersive technologies were seen to have value because they weren't intrinsically spatial, and to open up the potential that people see in these technologies, immersive technologies, to a whole class of problems that perhaps they didn't even think about before because they were focused on what it can do for our sense of space and not for our sense of time. And by, I think, filling in that missing piece that allows us to work with time the same way we work with space, that we can essentially expand the potential of these technologies pretty dramatically.

[00:41:11.827] Kent Bye: Awesome. Great. Well, thank you so much for joining me today on the podcast. So thank you. Well, thank you so much. It's been a pleasure. So that was Alex Bowles. He's a co-founder of a company called Helix, and he's looking at the spatialization of time. So I have a number of different takeaways about this interview is that, first of all, Well, the first thing that's really striking is just this spatialization of time and how you're able to get a better intuitive sense of how patterns of data are related to each other when you're able to actually visualize them in spatial relationships. And the way that he's created this helix approach is allowing you to both look at a helix at small scales, but also large scales. And so you're able to actually have a kind of like this fractal nested way of looking at these time sequences. But when you do that, you're able to potentially start to see the patterns that emerge more intuitively. And so there's so much big data, so much data that's being generated. And so any way that you can get some sense of the patterns of data is going to be a huge benefit, especially if you're able to communicate about things in the future that are coming, especially if you're able to mathematically model it in some way, you're able to then show that in some sort of spatialized way, and you just get a better sense of what the meaning of that data is when you're able to really, you know, see it in that spatialized form. It's this principle of embodied cognition, which I've been talking about a lot here on the Voices of VR podcast, but it's such an important concept to understand, which is that we don't just think with our brains, we think with our entire bodies, and that we use embodied metaphors in order to really get this deeper sense of these patterns of reality. And so what that means is that until we have an embodied experience of something, then there's something about a conceptual dimension of that, that we can't necessarily fully grasp. And when you have those primary metaphors that you're able to have in these spatial mediums, then you're able to then kind of with the Lego building blocks, take simple concepts and then start to add them up together. And that's a bit of what. Alex was saying was that in the process of creating this type of specialization of time-based events, you're going to have this understanding of complex dynamic systems that you weren't able to have an understanding of before. When I talked to Sam Roberts at the Indicate, one of the things he said is that video games do a great way of taking complex dynamic systems and breaking them down into these easy to understand metaphors because you are expressing your agency and seeing the consequences of your actions. And because of that, you are cultivating this deeper sense of a complex dynamic system. And then as you add all those things together, then you can have a deeper intuitive understanding of these larger and larger complex dynamic systems. And being able to take these time-based events and actually spatialize them out into space, I think is going to have this huge impact on so many different domains of our lives that we can't even fully imagine right now. You think about the calendar that you use to be able to plan things out. There might be dimensions of your life that are more intuitive to see your natural rhythms and natural patterns, and to see when you may want to exercise every day, for example. So you have this movement of the quantified self, which is already gathering a lot of this data that is naturally being produced by yourself. And then being able to visualize in this way may allow you to both make decisions about your future, but also make decisions in the moment. And I think that was another key thing that came out of this interview, was that being able to have this experience of data may actually enable people to be able to make decisions about these complex dynamic systems in a way that they've never had access to before. And I always love talking about the Kairos time versus Kronos time, and I really love Alex's depiction of how the Kronos is this linear depiction of time, but it's also like this unrelenting march of things that are just happening. And that's sort of the flow of time that Newton really talked about. but there's also this quality of time which is much about like when is the right time to do something and that goes back to allowing people to make choices and take action when it is the right time and I think this also has the ability to potentially get into that more kairos moment of seeing these cycles and rhythms of events over time and being able to see those patterns and then be able to more naturally and intuitively make decisions in your life or relative to specific sets of data. So I think that this approach of being able to specialize time-based data in this way, I think it's going to have a huge impact on the future of so many different domains. If we look at something like topological data analysis, it's essentially doing this feature detection to see what are the things that are related, and it's able to specialize that down into like a three-dimensional shape. which has these topological clusters that are like modularity classes that are able to then cluster things that are related to each other in some ways. And when you do that, you're able to see these different causal relationships. And so being able to actually get a better sense of cause and effect by this process of topological data analysis is one approach that is taking higher dimensional data and kind of reducing it down to show these different relationships, which is an amazing way to be able to actually see through the process of machine learning, how things are connected to each other. Well, this is able to do that same process, that same concept, but doing it relative to time to allow you to find these different connections and relationships between these individual nodes of data. And Carlo Rovelli's Order of Time, if people haven't read it, I highly recommend it because he really dives into a lot of the physics behind a lot of this stuff, as well as the deeper phenomenology and philosophy around time. And the philosophy of time is something that is a bit of an open question in terms of some of these specific details as to our experience of time, our perception of time, and what time actually is. And I think that as we have a spatialization of time, it's actually going to change our relationship to both our past, our present, and our future. And the fact that Alex has a background in the history of mathematics is really interesting to me, just because math is something that once it's true is always eternally true until you find some sort of either inconsistency in your logical reasoning, or you find a flaw in one of your axiomatic assumptions. But because of that, the history of math is something that is this ever-evolving and growing body of knowledge that is always relevant to the future. And so there's this wanting to see what the evolution of those thoughts are and to be able to potentially go back in time and to be able to pick up on threads that were opened up. And sometimes something is started, but it's left off. Doing this type of approach of the spatialization of time in something like a memory palace of all space and time would allow you to potentially find these different threads as they get started for the very first time, but sometimes there may not be a deeper context for it to really take off. And so the history of mathematics is a lot about going back in time and trying to rediscover these threads of history. that could be recontextualized into the current context, almost like these ancient tools that were developed, and you're going back into the toolbox of history to be able to rediscover and reignite the development of some of these concepts and ideas, and to potentially be able to solve real-life mathematical problems by being able to do this archaeological dig into the evolution of these thoughts and these ideas. And it's possible that this type of approach will help to discover those types of patterns of history and the evolution of these different types of mathematical thinking. So, that's all that I have for today, and I just wanted to thank you for listening to the Voices of VR podcast. And if you enjoy the podcast, then please do spread the word, tell your friends, and consider becoming a member of the Patreon. This is a listener-supported podcast, and so I do rely upon your donations in order to continue to bring you this coverage. So, you can become a member and donate today at patreon.com slash voicesofvr. Thanks for listening.

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