 It's really great to be here. I thank you for the invitation. I was first in New Orleans in 1984, and I came to attend SoftCon, which was the first consumer software convention held in the Superdome right across the street. Of course, this was pre-web. The Mac, this was in March of 1984. The Mac had just been released a couple of months. So there was no Mac software. It was DOS, CPM. There was a jungle of other little startup OSes. And software was being packaged in little baggies with no manual, which was significant because you needed a manual to use software back then. It was actually not very good. It was very primitive. And most of it was written by just a few folks, just a few tiny developers. There was very little software being written by large companies. And they would have been astounded to see what software has become now 30 years later. They would just have been on, would not believe the scale. And that's what I want to talk about a little bit, is the scale of things. So as we look at the next 30 years, I think we're going to be entering into a scale that we are not even prepared for. And I want to give a little bit of sense of what I think that is. It's a lifting up to another level. So another example would be flocks of birds organizing as a super organism, a termite city. So a city built by termites actually has its own respiration as if it was its own organism. It has a metabolism. And again, these things cannot be found in the individual termites themselves. And of course a coral reef, which is many species together, acting as a system. And so these systems have qualities, attributes, behaviors, and essences that are not found in the individual parts. And they also exhibit other kind of behaviors like homeostasis, self-regulation. They have power law scaling in the sense that they have an exponential increase in qualities based on their size. And they also tend to exhibit persistent disequilibrium. So they're out of equilibrium from a chemical energetic status. And they have immersion behaviors. These are common to these large super organism systems. And I want to think, so what about technology? Well, here are two bits of technologies, both of them approximately the same size. The one on the left is the first tool, one of the right's a more recent tool. The one on the left, in a weekend of instruction, you could probably be taught how to make one of those. The one on the right, nobody here, even working for years, could make one by themselves. In fact, as smart as all of us are, we probably could not even together make one of these things a mouse, or anything complicated, even this clicker. Because that technology is actually a network of technologies. There are many hundreds of technologies required to make that technology. And there are hundreds of technologies necessary for each of those sub-technologies. And so it, in a sense, represents a system of technology. And we are subsidized in a certain sense by the things that we do by the large network of technology below us. And as an example of that, a great example is an art project done by a guy who decided to try to make a $20 toaster from scratch. So he spent two years full-time making the ore, mining the copper, turning it, smelting the copper, making the wires, getting crude oil to try to make the plastic, getting a species to make the insulation. And this is his toaster after two years. It worked for about 30 seconds before the element burned out. And it cost him a lot more than $20. And it shows the sense in which our technologies are really networks of technologies. And if we stand back and look at the largest network of all these technologies together, they are self-supporting in the sense that it takes a hammer to make the saw blade and it takes a saw to make the hammer handle in the sense that they're co-dependent and self-supporting. If we stand far enough to back, what we get is what I call the technium, which is this largest system of all these things together. So the software we have is dependent on the computers on mining and electrical generation and transportation, all these things feed into this. You cannot have what we have unless we have the whole thing. That whole thing is the technium. And if you go back to one part of it, like this switch that, again, not any of us by ourselves can make, that switch is in no way alive or living. But if you take five quintillion switches and you link them together, you can get an internet, solid state switches, that actually does exhibit some behaviors that are lifelike, that are not found in the parts, but are found in the system at large. And that's one of the things I want to reiterate is that the thing that we're making, this technium, is exhibiting many lifelike behaviors, even though, of course, this is made up of machine parts. And if we stand back far enough and look at the planetary system, the technium at the planetary scale, it is basically another one of these super organisms. It's exhibiting many of the same behaviors of a homeostasis and persistent disequilibrium and power scaling laws that all the other super organisms that we know about in biology exhibit. So we can begin to think about it and treat it and manage it and even program it as if it was a super organism. So this technium includes not just the communication stuff, but it includes all the roads, includes all the buildings, includes the satellites that form a halo around the globe, includes all these things. This is the whole thing, and it's all codependent upon each other. They're all self-supporting. The main component of this is actually information. If you look at the rate in which physical things are being developed and produced in the world, they're increasing at the rate of 7% a year. That's taking on a decade level. Nothing is really being produced more than that over a decade. Concrete, cars, widgets, whatever it is. It's a very in order of magnitude of a single digit. Information is actually expanding at the level of 66% a year or Moore's Law. That is an explosion from the planetary view. It is huge. We're entering into the scales of zettabytes after exabytes. It's basically an explosion. And if we take a tally of all the information storage, both analog and digital, from the past three or four decades, we can see that this is a huge thing. We're up to like 276 exabytes of storage on the planet as a whole. That's the memory of this super organism. And it's almost expanding as if it was an explosion. In fact, if we took a measurement of the total, say the total meters of fiber optic being laid per second on the globe, it turns out that at the height of the laying of the dark fiber, we was being laid at 350 meters per second, which is basically the speed of sound. So there was a shockwave. From the planetary perspective, this was a shockwave of dark fiber. And if we actually tally up the total volume of all the digital flash drives, chips, storage unit, magnetic tapes, whatever it is, if we take all that digital storage being created every second on this planet and we were to actually concentrate it into one little area, it would be equivalent to a nuclear explosion. That's how fast this is expanding. It's an explosion. But unlike a nuclear explosion, which happens in billions of a second, this is an ongoing decade after decade. So from the point of view of the planet, this is the birth of this thing is sort of like a flash. It's like a nuclear explosion that's happening as this super organism of digital information, communication technology is appearing on this planet. Again, if you take the physical world, it's very flat. But we're scheduled to enter it into 10 to the 24th level of information transistors, whatnot. We don't even have words for this right now. But we can think of this as one large machine. And that's what I'm going to suggest, is that we begin to understand that this is sort of one very large interconnected thing. And we begin to actually program it, to think of it as something that we can work with. And so if we were to make the specifications of this, we would say, well, it's got one trillion transistors right now. There's 55 trillion links, 20 petahertz cycle, refresh rates of email, instant messaging, all this kind of stuff. Actually, 276 exabytes of memory, 100 billion clicks per day. What this turns out to be, to a rough approximation, this is the same complexity as a human brain. Basically, what we've made so far is approximately as complex biologically as a human brain, which is amazing. So we have basically one brain, one synthetic brain, at the level of this superorganism. That's the technium. However, your brain is not doubling every 18 months. And this is. And if we actually look at where it's going at the rates of things improving, we can estimate that by 2040 or somewhere around there, the technium's capacity will exceed all seven billion brains on Earth. Right now, there's one brain. But by then, it'll be equivalent to all the human brains. That's a very powerful machine. So what does this organism, if super technium, look like right now? Well, actually, this is one picture of the geographical distribution of the technium. And you'll notice that it's uneven. It's not evenly applied around the globe. And that's because it's not a machine. It's not this fictional planet, of course, on from Star Wars, which is a kind of a planetary scale superorganism. But it looks like more like a machine. What we're making on this planet, in reality, is much more biological. And I want to show you that by kind of mapping the spread of the distribution of technology around the globe. We'll do that by taking kind of an arbitrary grid and applying it to the Earth. We have one already. It's called latitude and longitude, latitude and longitude. And we'll just arbitrarily take just the intersections of the rounded off latitudes, the ones that are kind of just even, so the n dot 0, 0. And we'll take a picture of what's there on the planet. And here's what's been done so far. So here's all the places where there's a degree confluence of 0, 0. And someone's taking a picture. This is an art project. And if we take China, and here's some samples from China, of the many that are done in China, the most densely populated country on Earth. And what do we see? An awful lot of green and very little urbanity, very little cities, very almost no human structures. The only kind of evidence of technology is agriculture. And if we actually take more a large average of Earth on these arbitrary random samplings, we see the same thing. There's almost no evidence of technology. That's because the technology is predominantly congregated into cities, into urban areas, into these strings of things that are connected between the cities. That's how the technology is distributed around the globe. And if we look at the future of cities in 2050, we can see it's very spiky. There's more and more people in the cities and fewer and fewer people in the countryside, which is what's happening. And so we have this very uneven, rugged landscape of technology. And if we take all the cities over a million, they look like this around the world, that's where all the technology is. And if we look at the projection of cities in 2050, those mega cities, this is the pattern of technology on this planet. Human density, mobile coverage, 3G coverage. Again, it's uneven, it's spotty, it's spiky. There's 1,000 sensors in the oceans picking up information. There's the oceanic cables. These are the maps of the technium and the 1,000 satellites around the planet forming part of this technium. And these are the old technology as well, roads. This is a map where the yellows are the roads. This is a picture of the least-roaded area on the planet, which is around Tibet. But you can see this transportation system. We see air traffic movement, flight plans. These are the connective neurons of this planet. All these pictures from the Twitter and the social media distribution in a city to flicker and Twitter around the country, the connections between relations, electronic relations between people, these look like neurons. They don't look like a machine. This is the pattern of the technology. And it's not, of course, just electronic communications. It's the electrical grid as well. It's all the sensors that we're adding to it. The billions of eyes and trillions of eyes, the microphones, the water levels, the traffic sensors, all this stuff. In fact, every object that we make will have a little chip in it that starts to communicate some little bit of information that forms this large superorganism and making it a nervous system, basically. That's what we're making. That's what we need to program. And of course, in addition to that, there's us. The internet's not just all machines. There are people. And what we have in the superorganism is another level of 7 billion people are face-to-face communication, our own travel, our own brains. This itself is another level of the superorganism, our biometrics as we begin to do self-quantified self, measuring everything we do, creating our own individual exabytes of information over our lifetime through sensors that we either wear or apply to ourselves. And this total volume forms a kind of a symbiosis of the humans and the machines. So we're together creating this level of superorganism, of a system that has its own agenda, a system that has its own workings, of a system that has attributes and qualities that are not present in the individuals. And of course, the third level is Gaia. Gaia is an hypothesis by James Lovelock. He made incredible observation that you could determine whether there was life on another planet millions and millions of miles away by looking at the geochemistry of that planet because if there was life, there was going to be a disequilibrium in the makeup of the atmosphere and the chemistry of that planet because life makes a persistent disequilibrium. In our own planet, there's oxygen levels way out of whack that cannot be sustained there unless life itself is sustaining them. And the fact that there's oxygen changes the whole chemistry of this planet. So life is a geological force. Life has changed this planet. This planet has influenced life. The two are together in one system. It self-regulates the atmosphere. That's the Gaia hypothesis. So we ourselves are making technology at the scale that is now impacting the planet. 5% of the electricity that we produce globally is used to run the internet. 75% of the energy that we manufacture on the global scale is used to service the tech team itself. When you drive your car, most of the energy in your car is being used to move the car and really not you. You're a small part of that. So we have this tech team taking over and being used more and more of the resources which affect this Gaian planet. And it's not just recent stuff. Agriculture first changed the climate. And even prehistory, the hunter-gatherers, eliminating the megafauna, killing all the big animals basically, started to change the climate of this planet. So it's been going on for a long time. What I want to say is that technology is a geological force. It's integrated into this system that we're talking about. It's actually having some influence on the planet. So what we want to think about is kind of like three levels of this. So we have this technium sphere. We have the human, seven billion people and their connections together. And we have the Gaian. And you might think of this really as three different levels of the super organism, the technium, humanity, and Gaia because they actually operate at different rates. The technium has generations we count in months. And humanity has generations that we might think about in terms of centuries. And Gaia has generations in eons. That's the level that it's working at. So these three different rates really compose a single super organism that we don't even have a name for. And I'm not even going to try and name it, but it's something, it's this large thing that basically has three components. It's a super organism on this planet that we're making right now that we're just beginning to see being born as humans and it has nature and it has technology. And these three are the three components and they work at different speeds. And that's this thing that we are learning to program right now. That's what it is. And I think because of that, what can we say? What can we say about this thing? Well, one thing we know about it is that this is our longest running machine. There's no other machine that we've had that has been running without interruption, without being turned off, then save the internet in this other thing. We have nothing comparable in terms of having something as reliable. It's the most reliable thing that we've made. The second thing we can say about it is that generally the three characteristics of this thing is that it has global span, local entry, and it runs in real time. That's one of the attributes of this thing from a technological point of view. But I think there are seven frontiers for technologists and I want to gonna briefly go through and introduce them to you. Seven frontiers that I think this presents us. The first frontier is what I would call new math. Forget about big data. We're entering into a regime of mega data, okay? Mega bandwidth, planetary quantities of sensors, infinitely in real time. We don't have even the words to use for that. We don't actually have any standard prefixes after Yoda, which is after Exit. So it's like we have only exponential mathematical nomenclature, which will be fine, but the fact that we don't have any words for it is an indication that we don't have concepts and tools for it. And the kind of playful idea people talk about, well, there's lotta and hella lotta, maybe. I've actually suggested in all seriousness that we might think about a kind of a nested nomenclature where we have a mole, which is 10 to the 23rd bytes of a Goddow's number. So we could have mega moles and giga moles. Or you could take the same idea and take the largest thing, which is the smallest legitimate measurement that we have, which is a Planck, 10 to the 34 negative, but we can say, well, those kiloplunks and megaplunks. But in fact, these are really insufficient. And again, when we start to do things like having fully realized immersive VR worlds that are shared by millions of people at once, the scale of things that we have to move and manage and manipulate just far exceeds anything that we're even remotely doing, that it really will require a new kind of mathematics to do this in real time. The mathematical challenges are formidable. And so I like to think of this as zillionics, which is like zillions of things. So we're gonna need to become really good at moving zillions of stuff, zillionics. So the second frontier is new biology. So we make these very large systems at the scales of the planet, entailing zillions of things. How do we maintain them? How do we keep them secure? How do we keep them up? I think we have to import in from biology some principles such as immunology. So there's kind of five basic components to a really robust immune system. They have to have some definition of a self. It has to know self from non-self. It has to detect and eliminate foreign invasions or infections. It has to remember those things. And it also has to be able to recognize entirely new infections. And then it also has to be able to prevent itself from attacking itself. That's the kind of thing that we're gonna need in this system. That's the kind of technology, technological immunology that we're gonna need to actually run a system as large in the zillionics that we're talking about. An example, just a concrete example of this, is that today we have security, the way security, say, or privacy works in the technological systems today is through secrecy. So you have a secret password, you have secret crypto keys. Biology doesn't have secrets. The immune system doesn't work on secret. It works on behavior. It detects and the non-self through behavior. And so that's a model that I think that we'll look at for running a system, a hygienic system of this scale, is through behavior rather than through secrets. The third frontier is new emergence. The idea that there are levels of behavior, levels of phenomena that are not present at this level of the PC and the phone level is gonna be happening at another level. A great example of that was in the last financial crisis. You had many, many different countries with their own regulations and their own markets and their own politics exhibiting almost simultaneous synchronized behaviors in their own marketplaces as if there was one financial heartbeat in this thing. Because it was a system for the first time. It was a new system. We see things like the 2010 flash crash, which was a momentary collapse that was, nobody knows why it happens. It was a phenomenon that happened at the large scale of the system. It was a system failure. Nothing individually failed, but the system at large collapsed. And that is the kind of phenomenon that we're gonna see more and more of. It's almost like slow earthquakes which take present on the earth and that we're not aware of. The frequency of these earthquakes are so low that we can't feel them. And they're very hard to detect because they happen at such a low rate. Well, the same thing is happening at this super organism scale. There will be phenomena that will be very hard for us to detect at first because we're simply not looking at it at the right scale. The fourth frontier is a new thinking. Of course, we'll make this thing smarter and smarter. And of course, we already have things like Google's Android's speech recognition and Siri. I call this utilitarian intelligence because whether it's really conscious or not, whether we want AI or not, it doesn't matter, all we wanna know is that it's useful. It'll become even more useful over time. That's one version of it, but I'm much more interested in this other version of intelligence. That happens at the largest scale. So there was a bunch of researchers who took a million different pictures from the internet and they fed it into a perception algorithm that would then try and draw or paint the dominant patterns that it saw in these millions of images. And what that AI, what that intelligence painted was the face of a cat. It said, I see cats. Now, it didn't actually say cats. It didn't know it was a cat. It just made a picture of a face of a cat. That's not that smart, but someday it will be. But that is the, that's an emergent intelligence that I think we're gonna do. We can harness, we can make use of, that we can program and do something very powerful with. In fact, David Eagleman and I and neurobiologists have proposed something model on SETI, which is a search for internet intelligence. If there was some kind of emergent intelligence on the internet, what evidence would we need to be convinced of that? How do we even know? It's actually a very difficult problem because it turns out that even SETI does not have a definition, an operational definition of intelligence. So this is a very difficult thing to figure out and anybody who has an idea about how to define something such that we can actually look for it, it'd be a very powerful thing to do because if it was to arise, how do we even know? The fifth frontier is anticipations. The purpose of a system, the reason why cells form multicellular organisms is in order to anticipate the future. It's in order to have a better view of their environment, to be able to anticipate a coming food shortage by having more reserves, to in some ways look ahead to the future. And what we're gonna do with this system is of the super organism, the technium, is to be able to use it to anticipate things. So take a very concrete small part of it like the road system. If you have all the roads in the world and they have embedded sensors everywhere and we have smart cars that are being driven and smart traffic lights, it's possible to integrate that in with the weather system. Holidays, shopping behaviors, and begin to say, well, where the weather is coming, we can, and the holidays, we can anticipate that there's gonna be traffic jams here so we route traffic over here. That is one way in which we use this system at the system level to anticipate things. It's taking that information and looking ahead and integrating it at the system level. The six frontier recognizes the fact that this is not utopia. I don't think that this technological super organism, the technium, is utopian. It's not a panacea. There will be as many new problems as solutions. There will be a lot of new problems, a lot of new ailments. There will be, of course, more of the same that we have already, viruses, malware, all that kind of stuff. More of that, but that's not what's really interesting. I think the real frontier is in the system illnesses. The equivalence of having the flu or cancer or poisoning, which affects the entire system and it's found not in the individual components, like your PC, but it's found at the system's level. In fact, if we have any kind of intelligence in the system, we'll have systems ailments that are very similar to mental diseases like phobias, compulsions, and oscillations. Phobias is where there's this attraction to something, I mean, attraction away from something, where you're moving in fear away from something. A compulsion is an attraction towards something and an oscillation is where you can't decide and you're going back and forth. Those are the three general classes of these ailments and I think we can expect to see the same thing in the system on the internet where there's a system-wide phobia or a compulsion to repeat something. And then finally, there's the frontier of a new OS, okay? This is a new platform and I'm urging people to think about it at a higher level. Right now we are programming this, but we're programming it one click at a time. Every time you click on a link, you are programming this thing. You're making an associative connection like a Synapse. You're saying this is connected to this. So you're clicking through and we're inadvertently programming this. We can do better. We could do this deliberately. Try to make an OS. And I'm not talking about an OS, it's just another bit of code. There's code involved, but it's code, it's laws, it's organizations. These are all the ingredients of an OS that runs on this new platform. It's a very big thing and I think that the quality is unnecessary for this kind of OS. It needs to be decentralized, transnational, very agile, open, because it has global span, local entry, real time. So that's the kind of qualities that's required to run a system like this. It cannot be centralized, there's no way to do that. And so I think it's beyond the, we need organizations that are not state or nations, we need organizations that look a lot like Linux. And so a lot of the qualities that people have used and developed over time, a lot of the tools and the attributes are the kinds of things that we're gonna need to run this technium at the level of the super organism. That's what I think a lot of these new OSes will look like. There'll be kind of something like Linux at the scale of the planet. And I think that's really what's needed. I want to think about, to emphasize, to actually go back to that soft con in 1984. Imagine if we're on a time machine and we could actually go back across the street until 1984 and we told them about what was going on right now. We described what we could have with these things in our pockets, that we could have maps to almost any city, street maps, walk down street view maps. We could have real time sports scores, we could have stock quotes, we could have news, we could watch movies. We could have the entire encyclopedia. We could have all these things right here in front of us and a lot of it for free. They simply would not believe us. It would be impossible. They would have arguments saying, well, how does that even work? What's the economic model for that? That's not even economically possible. In fact, it seems impossible. I think over the 30 years since that first software conference in 84, what I have learned is that we have to believe in the impossible easier because the impossible things are happening all the time. We don't realize the incredible impossibility of sort of what we have right now with the level of software and computation. It would be literally unbelievable to anybody in 1984. That's only in 30 years and my strong hunch is that the next 30 years, there'll be even more of a surprise, even more of a gulf between what we thought could happen and what actually will happen. This is just the beginning of the beginning. You're not late, nobody's late. We haven't even started what we're doing. I want to thank you for your attention and I really appreciate the invitation to talk. Thank you.