How to save the planet from global warming | Tom Chi, LIVE at Mindvalley HQ

We're good bringing it up. Oh, check this out. Okay, do we have all the people? All the people. Good, good, good, good. I'm not sure who I'm asking. There's plenty of people. So we're just going to start. Cool, cool. Thank you, everybody, for coming. So we did a slightly different talk earlier for the mindvalley crew, but I wanted to open things up and go much, much broader. And it actually covers work that I'm doing a lot more of right now. So I made up a fake job for myself called Lab Director of the Planet. And, like, when you see this thing, you'll totally get what I'm talking about. But for a moment, we're just going to jump into this talk. You will get what I'm talking about through that, too. For anybody that doesn't know, I'm Tom Chi. I mostly am teaching folks how to innovate and prototype. There's lots that you can see about that. There's like 10 hours worth of videos on YouTube, so you can watch that, too. But I'm going to talk about some of my new work, which is actually not recorded and online anywhere. So you guys are actually getting a very early sneak peek of the stuff that I'm currently working on. Okay, so check this out. Starting at the very largest framing of things, at least in terms of. As human history goes, not that long ago, we invented this thing called agriculture. And since the time that we invented agriculture, the human population has increased by 1000 fold. So we had about 7 million people before agriculture. And after the development of agriculture, we're about 7.4 billion today. And this is usually the sentence that people hear right before they start talking about major environmental collapse and really how things are basically hopeless and how we use 1.6 earths of this and 3 earths worth of that, and so on and so forth. But I'm actually here today to tell you about a different narrative to the same idea. So it turns out that if you take that 7.4 billion people and you were to go add that all up and say, how many people is 7.4 billion people? Well, it turns out to be about 350 million tons of people. So you think you're overweight? Well, There you go. 350 million tons. And that means all of humanity together weighs about 350 million tons. Well, you know what else weighs about 350 million tons? The weight of all ants on Earth is also about 350 million tons. Now, why is this an interesting thing? Well, human beings eat about 2.8% of their body weight per day, and ants eat 30% of their body weight per day. So it actually means that on any given day, that same biomass of ants as there are of humans is literally eats 10 times more of the Earth than we do every single day. And yet we don't run around talking about how ants are the scourge of the Earth and how they're destroying everything and they're consuming so much more than humanity, even though, in fact, they literally are. They are literally eating 10 times more of the Earth. There's lots of running happening. Okay. Year down, year down, we're all down. Cool. Even though they're literally eating 10 times more than humanity. Well, it's not so much actually how much you consume. And this is maybe one of the major insights between a kind of an old way of thinking about the future of economy and the environment and humanity, and a possible new way of thinking about it. It's not so much whether you eat as much as humanity does or you eat 10 times of that, it's actually the way that you do it. Because the reason that we're not afraid of ants eating 10 times more than us is every time that ants go out and eat their 10 times more, then they actually make their ecosystems healthier. And ants are a great example, because ants are omnivores. They eat some animals, they eat some plants. They're basically just like us. But in eating 10 times more plants and animals than us, they also aerate the soil, distribute nutrients. They effectively make every ecosystem that they are naturally a part of a healthier ecosystem than it historically was. So actually, if we were to triple the number of ants on the planet and they were eating 30 times more than us, the planet would actually get healthier. So in a way, this is a new idea for humanity, but it is actually an incredibly old idea. Are we good with all the walking? Okay, I'm sorry. Yes. Okay. We're sitting or we're walking? Good. Cool. It's an incredibly old idea. And it's an incredibly old idea because this is new for humanity. But this is basically how all of life works. Every single organism on the planet works off of a basic algorithm of making life better for the other organisms. So this is a picture from Patagonia. And I had the pleasure of having breakfast with this woman who is an ecologist in charge of the. This restoration project that was started by the founders of Patagonia, the outdoor sporting company, and she was in charge of taking care of this enormous ecosystem and kind of being the ecologist that was overseeing it, and she was telling me at breakfast about, you know, one of our main things is to reintroduce this top predator, the jaguar. So we reintroduced the jaguar. And actually, when you reintroduce the jaguar, it actually makes the ecosystem amenable for four other species of smaller cat and five different rodents. And she listed out 15 different mammals that come back to the environment because the jaguar is reintroduced. So even though we think of the jaguar, it's a predator and it's taking things out of the environment. No, even the top predators in nature make the ecosystem healthier. They allow for more diversity, they allow for many more species to come back. And she had this amazing sense about things where she could say, oh, when I walk next to a lake and I see this grass has been nibbled, I know that these rodents have come back. I know that this has come back. And just like this beautiful sense of how all of ecology is intertwined, well, this is an example of all of life basically running this simple algorithm, which is the services that are generated, the ecosystem services that are generated by the species being in that environment actually outweigh what they consume from the environment. So that's true of the predators, it's true of the ants, it's true of the herbivores, it's true of the plants. Every single thing in life basically follows this rule. The one exception is basically us. So this is not a problem necessarily about how many people are on the planet. It's actually not even a problem about the volume of what we consume. It's just the way that we do it. Actually, all of nature consumes vastly more than humanity does, but it just does it in a way that makes all of life healthier. And it points to where we need to be pointing to, which is, as a goal for our civilization, we need to effectively follow this rule that all of life has been following, that the presence of humanity on earth needs to generate more ecosystem services than ecosystem consumption. And another way to go phrase this is humanity needs to become a net positive to nature. If you think about this, really, any other scenario than that will eventually lead to the death of the human race. So if we are majorly negative to nature, you can see how that would very quickly lead to our demise. But even if we were a little bit negative to nature, let's say we were 1 1/2% negative to nature each year, you add it up for enough years, and you basically live on a dead planet, really, any other condition than being net positive to the planet leads to our Demise. And I know a lot of you guys are probably passionate and you're interested in sustainability. And I'm here to actually say that sustainability is too low a goal. Because here's the thing about sustainability. Sustainability says, let me take exactly as much as what I give. I'll take as exactly it's sustainable. Nothing's hurt, nothing's helped by it. But if you actually track the way that we're getting sustainability done, sustainability tends to be like this unique alignment between technology, market and environmental interchange. And it's like, oh, because we talked about, oh, this company has a totally sustainable way of doing this. And they take exactly and they give back. And they use post consumer insights. Yes, there's this nice, balanced interplay between technology, market and ecosystem. But the problem with that is that technology and market are always changing. So even your sustainable thing, a thing that was running really well for you for five years, gets shaken up because technology and market change. And then you need to revise it, and then it gets shaken up. And every time it gets shaken up, you're basically unsustainable for those years when you've been shaken up. So even when we hit sustainability, we actually fail at sustainability. We need to aim at a target that is much more intense, which is we need to actively create ecosystem services that outstrip what we're pulling from the ecosystem. All right, so how are we going to do this? Oh, what? Before we get that, let me tell you how bad it is. Okay, this is a lot of charts, and all these charts together say that things are really, really bad. And I won't go into a bunch of the charts very specifically, but I will drop a couple simple ways to understand what we're doing right now. So you guys have definitely, you've heard about how we put all this carbon in the atmosphere and it's destabilizing the environment. Let me give you a little bit of context for the degree to which we're doing this. It's all good. So we are putting. So since the year 1990, we have put as much carbon in the atmosphere between 1990 and today as we did over the entire course of human civilization up until the year 1990. So think about all of human civilization before 1990. We doubled the amount of carbon output of all of humanity over all of time and in 27 years. And what we're about to do is do that same amount not in 27 years. We're about to do that same act again in 18 more years. Right now, think about how much things got messed up Just from doing that once, we're gonna do that again in 18 years, and then the next time through we're gonna do that even shorter in 15 years. And the next time through we're gonna do that even shorter. This is what we're up to right now. The level of, can I curse? I'm going to. Anyway, the level of fuck up that we're up to right now is so much more than anything that you've ever heard. And I'm trying to make it very concrete to you guys now. How much are we effing it up right now? Well, we are basically putting 10 gigatons of carbon in the atmosphere every single year. And that sounds like some abstract figure. 10 gigatons, that's just as big, whatever that is. Well, here's a way to go conceptualize 10 gigatons. You guys know how much you weigh and you know how much a car weighs, right? So you've ever tried to push a car? You know, it's a pretty massive thing compared to you. Now imagine every single year, I gave a car to every single man, woman and child. 7.4 billion people, I gave them a car every single year. And then you took the entire mass of that car and made it into carbon. That's how much we put up in the atmosphere every year. That's how much mass. So if you think about how heavy a car is, that's what every single individual on this planet is putting up. Now, you guys living in a relatively developed country, you know, city right here, actually, you put up more than a car, you're probably putting up three or four. Some of the folks that are living in villages, they're putting up a quarter of a car, a half of a car, depending on how they cook and depending on a couple other factors, because there's some dirty cook stoves and all that sort of thing, but doesn't matter, right? Like this is a visual for you to understand how much you are directly contributing. It's that much weight, that much mass for every single one of us. And this put us in a position of being a carbon generating civilization, basically polluting the atmosphere with carbon to the tune of 10 gigatons per year every single year. Now, I worked for a long time and I still do. I mean, I'm an investor and an advisor to a number of renewable energy generation storage finance companies. And I love the idea of let's continue pushing so, so that the way that we generate and store energy, it gets us closer to carbon neutral. But the danger is the following. It Turns out that we don't have enough time for all of that because even if we were completely carbon neutral tomorrow, which is not going to happen of course, but let's say we were like, I could magically wave a wand and tomorrow everything was solar and wind and we were completely carbon neutral. Tomorrow we have over 100 years of, of warming that's already built into the atmosphere. Between 100 and 150 years of warming that are built in, depending on whose model you're after. Now what does that mean if you have 100 years of warming built in? Well, a thing you may not have known much about is it turns out, I think that we even have a slide about this. Oh, this is horrible too. Okay, actually, let me just show you this really quickly. That. So this is the year 1750. We're at a concentration of 280 parts per million via coal, oil, gas, cement production, changes to land use. We added this much to it, but luckily the land absorbed a bunch of it, the ocean absorbed a bunch of it, and the rest of it went into the atmosphere. And a thing that you guys may not know about this is that the ocean has already been saving our ass in a bunch of ways. That if the heat that was absorbed by the ocean was not absorbed by the ocean and it went just into the atmosphere, it would already be 50 Fahrenheit hotter in the atmosphere. We already would be dead. Luckily, a bunch of that heat went into the ocean. But the thing that's unfortunate about that heat going into the ocean is we are on a rapid trajectory for every single coral reef on Earth to die within 30 to 35 years. You guys may not have heard of this, but basically since 1980 we've lost 40% of coral reefs on Earth. And in the next 30 years we're going to lose the rest. Now what happens if you lose all coral reefs on Earth? Well, turns out about 25% of all species in the ocean live in the coral reefs. So you're going to lose them for sure. But it turns out that 50% over 50%, slightly over 50% of all ocean species have either their food chain or reproduction chain pass through the coral reefs. So you are going to seriously disrupt more than half of all of life in the ocean and you're going to have a quarter of it just completely wiped out for all time. When you do that, we're talking about something that is basically tantamount to the entire collapse of the ocean as an ecosystem. 70% of what covers the Earth is going to collapse as an ecosystem that's 30 to 35 years from now. This is a great example why carbon neutral is not enough. Carbon neutral says we're going to keep on warming for 100 years and in that time period we're going to experience this and a lot more. I don't know about you, but I don't want to allow us to have the world where we've wiped the ecosystem of the ocean clean. And in the hundred more years of warming, we're going to lose 25 to 50% of terrestrial species as well. Right. Like that is, we're verging on a dead Earth at that point. If you lost more than half of terrestrial and the ocean ecosystems collapse, you're basically living on a dead planet. And that is the optimistic scenario where we are carbon neutral tomorrow. In fact, we're not going to be carbon neutral tomorrow. Even with the Paris Accord. We're not turning back the hangover of 100 years. We're just growing it slightly less aggressively right now. We're adding to that hangover multiple years per year. And if the Paris Accord goes through, it says let's go add just a year and a half every year. This is not good news all around the board, but it actually points to what is the real task that we're up to. The real task that we need to be up to as a civilization is to, to be sucking down carbon, to be carbon negative civilization in the order of 5, 10, 15 gigatons per year for almost half a century. That's the range that is going to have us return to a healthy Earth within this lifetime or within our children's lifetime. Oh, I actually even had a slide for this. It's a disaster. That's what the slide says. It also notes that there's a billion people that have their main protein source from the oceans. And in the back it shows the damage to the Great Barrier Reef that happened in 2016. But actually that damage is continuing to happen. So this graph is even redder now than it used to be. But we lost a huge percentage of the northern 40% of the great Barrier Reef. You know, there's still some stuff down here, but that is the largest reef system in the world and that's what we lost in one year. So yeah, this is all like super, super real. Let's get to how we're going to go change. Some of this damage is large. The time is search the short. How could we possibly become a net positive civilization? Okay, it's possible to play a video. Okay, this is going to be great. Okay, I'm going to play the video right after I explain this. So there's this idea which I call the invention Catalyst theory of change and it goes like this. So some of you know, maybe you don't know. Like I was on the founding team of Google X, so I got to work on self driving car, Google Glass, project, Loon, bunch of these projects. And a thing that I witnessed about the self driving car was the following. If you were to scoot backwards in time six years to the point that we were beginning to develop the self driving car, it actually turns out that the global spend on inventing self driving cars was very, very little. It's like a million dollars per year. I know because it was mostly our team, right? And that was basically five or six engineers and some cars cost us about a million dollars per year to go run the project. And that was like the whole global budget for self driving cars. If you fast forward six, seven years to today, well, there's actually over $10 billion and 10 companies that are actively working on self driving technology. So it's multiplied from 1 million to 10 billion in just the course of a couple years. Right. And if you were to talk to any major automaking CEO, and I've talked to a number of them, Ford, Toyota, whatever, these are some pretty big companies. If you Talk with the CEOs and the executive teams of these big automakers and you ask them about self driving technology in their future, every single one of them to a T expects that that self driving technology is going to be a significant part of their fleet in 10 more years. So given that you fast forward to 10 more years, we're talking about a trillion dollars worth of capital going into the development of and the production of self driving vehicles. This is starting from 17 years prior where only a million dollars per year unleashed that. Well, why is that type of change possible? That's like a factor of a million, right? Like why is that possible? It's an idea that I call the invention Catalyst. There's a way that you were able to think about transportation before cars could drive themselves. And then there's a way you could think about transportation after cars could drive themselves. And it's not the same thing. There's a way that you would think about city design before cars could drive themselves. And there's a different way that you're going to think about city design after cars can drive themselves. And I'll run you through this calculation really quickly because it's one of the ones that we did when we were working on the self driving car in the early days. So it turns out that most of the time that you own a car, you're not driving it, right? It's mostly in your garage or it's parked at work or whatever. You're not driving it. So the utilization of a car most of the time is less than 5%. Are you spending more than 5% of your life driving your car? No, it's less than 5%. So it means 95% of the time cars are idle. Now, in a world that cars drive themselves, you could actually have way fewer cars, but you could have the cars show up when you need to go somewhere. So the utilization of each one of those cars doesn't need to be 5%, it could be 50%, it could be 70%. Completely possible. Now if it was 50%, then actually you would need 110 the cars that you have today to get the same amount of transportation utility. Imagine this city with one tenth the cars, right? Makes a huge difference. And actually when you think about how the roads are designed, how much space is designed for parking and all that sort of thing, we made this joke back in the early days of working on the self driving car. It's like we're going to go to all the parking lots and we're going to erase the letters at the end. So it just says park. And we're going to fill those with trees and we're going to fill those with grasses. Because there's so much of a city which is absorbed in parking lots and those are not places that people enjoy. When's the last time you went to a parking lot? And I said, yeah, no, it's like if you go to a park though, you're like, yeah, let's get a picnic going. We'll get the friends out, make some food, food together. Parks are this beautiful feature of things and we have way more parking lots than parks. And we don't need to in the world before self driving cars, you just need to have that because cars are not in use 95% of the time in the world. After self driving cars, you can completely redesign the proportion of a city. So this is the idea of the invention catalyst. Before a thing is possible, you can only think about the problem. You can only think about the solutions in a specific way. Once a thing is possible, then the entire thing changes. How you own it. Like how your cities are designed, how you move around. I used to also play out this use case. It's like, what if you didn't own a car? What if on your smartphone, while you're walking down to your front door, you just ordered up exactly the sort of car that you wanted to be in that day? If you need to just pick up some groceries, maybe it's a one seater. Maybe if you're commuting with a friend, it's a two seater. Maybe if you have a hot date, it's a sports car, right? Maybe if you want to go do some home improvement, a pickup truck comes up. Because you can load a lot of stuff in pickup truck. The right car comes up for you when you dial it up right when you're walking down to the door. That is actually better than what car ownership is today. And like, if the majority of the fleet in the future was self driving, very easy to write that code. It's like Uber Plus 150 lines of code. So you know they'll take a long time to do it. It's fine. But with that in mind, now you know what an invention catalyst is. And we talked a lot about how dire things are. But what if we were to take the idea of an invention catalyst and apply it to some of these extremely dire issues? And with that. Oh, you see there's a link over there. Can you escape the presentation and click that link? We're going to have you watch a video real quick and I want to talk about this one. Mindvalley. Any quick questions? No? Good. That's easy. Oh, scroll back to the beginning and support. Did you already watch this? That's amazing. I think I was halfway through the video already. Okay.

Every year, 15 million trees are destroyed. And despite heroic international planting efforts, a Net loss of 6 billion trees remains for the 1 billion people that live in these forest communities around the world. This is not just a loss of trees. This is a loss of biodiversity, resources, carbon storage, and jobs. There has to be a better way. My name is Lauren Fletcher, and we at Biocarbon Engineering are going to plant a billion trees a year using drones.

So the system works in three phases, really. The first phase is the initial mapping to decide where to plant. We use Satell imagery to direct our mapping drone, which flies over the land, taking detailed images with centimeter resolution that tell us about nutrients, biodiversity and terrain. We use this data to automatically generate a precision planting pattern. Secondly, we upload the map into our quadcopter planting drone, which flies at 2 to 3 meters above the ground and fires a biodegradable seed pod at 45 meters per second. At each predetermined position, the seed pod penetrates the soil Is activated by moisture and contains all the nutrients for healthy tree growth. As the trees mature, we can monitor growth and support decision making around caring for the trees. This data is then stored and used to improve the algorithms to increase germination success in future planting missions. For the past two years, our team has been working hard to make this vision a reality. Using off the shelf technologies, we have developed an entirely new way of thinking about aerial robotics. We have been flying our fixed wing drone across multiple countries. We have mapped everything from deforested areas ready for planting to dense forest of multiple species. Analyzing this geotagged terrain data, We've been able to decide exactly where to plant. And we can adapt this map to each species. The design of our planting system has been optimized for its precision planting ability. Our unfair advantage comes from the way we deliver the seeds in our proprietary biodegradable seed pods. This is how we can achieve scale and move from a manual process to an automated solution. We've been developing this technology in greenhouse trials, Optimizing the pod components for each species to match environmental conditions. Our pods have been designed to improve germination rates Compared to direct seeding, Allowing us to plant in more environments. This technology allows us to plant at 10 times the rate and 15% of the cost of traditional methods. We've been out in the field validating this technology, and now it's time to have real impact.

Healthy forests aid in fighting climate change. They improve water and soil and increase agricultural productivity. More importantly, they provide massive social uplifts through local job creation. So we expect to double the daily income of millions of families in the lowest economic brackets around the world. For two decades, I have been a NASA engineer studying technologies to terraform Mars. But our own forests are in a desperate state. So if we're going to terraform, we need to start right here on earth.

All right, back into the presentation. So what you saw right there is the, is one possible invention catalyst around the future of carbon on this earth using the technology. So I'm an advisor to this team. I've been working with them on a bunch of different things around the technology and, and helping them raise capital sort of thing, but working off of where they already are, which is not the final spot. Basically, this technology could put 10,000 trees into the ground every single year using just 9,000 drones. And it will cost about $70 million to do so right in the zone that you're able to plant like 500 billion trees, you can actually completely turn back all of climate change and get us to Almost pre industrial levels. So I'm not talking like 1990 levels. I'm talking about the way the atmosphere was in 1750. Right. And 10 billion trees per year. Yeah. For 50 years, you'll get to 500 billion. Or you can go faster than that. Right. You want to do 20 billion, you want to do 30 billion a year, it'll just cost you 150 million. It'll cost you 200 million. Now sounds expensive, but you have to understand that we are in a world that after. When New York City flooded from Hurricane Sandy, New York City started getting really worried. They're like, the seas weren't supposed to rise to the level that we would flood the subways. This was not supposed to be possible. So they started talking about, what if we built a seawall? You know, the Dutch know how to make seawalls. What if we built a sea wall? And their estimate for the cost to build a seawall around New York City, 80 to $100 billion. To protect one city for $70 million a year, you could not have climate change. That is an invention, catalyst. That is a completely different category of possibility that you could not imagine before. A way of planting 50 times faster and cheaper than before it was invented. And this is not optimized yet. I'm pretty sure that just the physics of where we are, we can get to 200 times, make that even cheaper, make it even faster to be able to restore the environment at this level. Now, I'm not saying this because this is the only thing that we can go after, right? But this is actually to go demonstrate. This is the level of thinking that we need to be at in order to tackle this level of issue. It's not just throwing some scrubbers or injecting some of the carbon, sequestering it into the earth. It's not about passing some accords in order to limit by 20 more percent the growth. Because remember, these accords do not pull it back. They just slow down the growth. Now, I'm not saying that we should not do that stuff, especially if it's easy to do. Let's get some of that underway. Because it's better to have a bit less carbon to deal with. But the category of solution that we're talking about right now, two orders of magnitude off of what is actually needed. Right? So do it if it's cheap, but don't do it if you're going to expend everybody's energy and willpower into a thing that will move the thing by 2%. Because those same human beings Might be able to go invent something that could solve the entire problem. This is not a large team, this is a 13 person team. 13 human beings invented a way to potentially turn back all of climate change within 50 years. Let's let that sink in for a second because there's more than 13 of you in here. And I would actually say these are smart people, but their skills are not especially crazily different than your own. They bought industrial drones off the shelf. They didn't build all their drones themselves. They learned things from published stuff in terms of ballistics that had been published from the military and other things. And I love the fact that they're using military research in order to restore the Earth. It's kind of beautiful actually. But they did things that, like, if you trace how they did it, it's actually not impossible for the majority of the people in this room to do it. And we're using that same energy, that same willpower, that same angst into just feeling horrible or to signing a petition. And when was the last petition that you signed that turned back climate change? Right. It just hasn't worked yet. So if political solutions worked, I would just tell all you guys, go out and do the political solutions because they were working, they're kicking ass. But I haven't seen them work yet. The thing I love about trees is once you plant them, they don't change their mind in four years when somebody else gets elected. They don't change their position on a treaty in 20 years when it's economically not favorable for them. A tree will be like, I'm in this for 200 years and I'm going to plant 10 more trees because I'm a tree, right? Like we got to go for the stuff that is going to have the effect size that we actually need to go turn back what's happening to this planet. And you can see this stuff is real. You could see that it was planting. These are different prototypes of the seed pods. Here's trees that were planted that are growing the UAV mechanism. Parrot drones is one of their big investors. So we basically get drones for free. And yeah, their mapping technology on their fixed wing drones is also phenomenal. And I can talk about this technology for a gajillion years. But maybe one of the things that's most interesting is they can fire the seed pods into the ground at up to 45 meters per second. But what they actually do is they have local scanning on the drone that understands the soil type, knows where the rocks are, knows where the soil is. Knows how dry it is, and so on and so forth. And then they will adjust how hard they fire it to exactly how deep this seed needs to go. And given the type of soil is underneath it, that's fucking brilliant. So that's just one of the things. And it's 13 people, right? 13 people in two years. So I mentioned this. I upped the ante a little bit more because I added a couple of millions around what it takes to go to a remote part of Canada, remote part of Brazil, because I hadn't factored in transport costs. So add a couple tens of millions to it, but it's in that range, 40, 50, 70 million to go do 10 billion trees per year. And ultimately, whether it was 40 million, 70 million or 100 million, this is still 100 times cheaper than anything else that we're talking about. If I'm off by a factor of three, it won't matter. It'll still be 100 times cheaper. Oh, this is how you actually go for things that have really important impact. Because when I was giving this talk, it was to a bunch of folks that were trying to work on sustainability initiatives all throughout Asia. And my concern for a lot of their projects was you're kind of having impact, but the scale of the impact is, like, actually quite limited. And I didn't mean that as a, you know, to discourage them, but it's almost like it would literally take you the same amount of work to have a much larger impact. So take a couple steps back and challenge yourself and say, what is the full scale of the problem? Right. I could. The same inventors could have spent a bunch of time putting, you know, a better scrubber on top of a smokestack so that we capture a bit more carbon before it goes in the air. But that would only affect global carbon by a percent or 2. So the same amount of effort and invention and creativity and hard work or whatever could affect 1% of the problem, or it could affect 200% of the problem. Right. Because to draw down 10 gigatons and draw down 10 gigatons more is a 200% solution, not a 100% solution. Right. So challenge yourself, like, what am I doing? And actually, could these same skills actually hit the problem in a much more substantial way? Now, when you do do that, doesn't mean that you're pie in the sky. And, like, just dreaming all day, start crazily small, make your first seed pod, buy your first drone and see if you can drop some stuff out of it. Like, go talk to some ecologist and talk about what you would even need to be planting, right? But start small. But start to focus on inventing things that change the nature of the game. If you can change the nature of cars so that they are 50, 70% utilized, then it changes the nature of the game of transportation. If you can change the nature of planting trees so it's 50, 100 times cheaper and faster, you change the nature of reforestation. So start small. They didn't need to plant that many trees in order to figure out that the rate at which they were planting is much faster. If you plant 1,000 trees, you can calculate that your rates are much better than a human being planting a thousand trees or shaking it out of a helicopter. So you can actually put a lot more seeds in the ground by shaking it out of a helicopter or plane. But most of them don't germinate. And most of them germinate in the wrong place because the rain comes and washes them into the wrong place for these trees to grow. So even though you can get more seeds out there for cheaper just by shaking out of a plant doesn't work for restoring the environment. So anyway, long story short, even within that first year, they were hitting enough of a proof of concept that they could tell that they had fundamentally changed the game on one aspect of the rate that things could be done. So focus on a game changing element even though you're starting small. And then once you've done that, stick with that game changing element long enough to catalyze that change. And that's what we're doing right now. We are closing a round of funding. Almost done. We have our first contractor reforest with a mining company. It was signed a week and a half ago. Like this stuff is now becoming a thing that now exists in the world. And then the last thing, keep pushing, keep learning. So with that, yes, there's another project which is about awakening global consciousness. I talked with it to a group called Nexus about it. I also talked with mindvalley about it right now, like a couple hours ago. And this is one of the other major change accelerators out there, like beyond inventions that can change the nature of what can physically be done consciousness, the way that we approach each other and the world needs to shift. Remember that very first slide in terms of human beings actually consuming one tenth of what ants do. It's really the consciousness that we're bringing to that consumption. It's not the absolute magnitude of the consumption. We could eat 10 times as much. We could consume 10 times as much of the world. If we did it in a way that was conscious, if we did it in a way that added to the forest, that added to the fields, that added to the topsoil. I have this entire other project. I could talk about sustainable switchgrass biofuels, but I won't get into it. Just recognize that that could be amazing and relative to consciousness. I'm going to talk about one other project which is kind of in this zone, but this is more of like a consciousness accelerator versus a invention accelerator, though there's a little bit of both in there. So in a different world. And some of you guys attract this work that I do. But I spent a bunch of time in the developing world working with communities, living on less than a dollar or two a day. And this particular work was up in the cloud forest of Guatemala. Kind of looks like this when it's not cloudy, but a lot of times it's cloudy and foggy, so you can't see any of these things. It just looks like big ball of mistakes. And I was in this pickup truck with my friend Juan, who's the CEO of a company that's working on getting this distributed solar power to all these people in the cloud forest Guatemala, that had never had access to power in their entire lives. Just nobody before them and up to now have ever had access to electricity. And we're in the pickup truck and we're bouncing along, and you basically have to drive through the jungle for five hours in order to get to some of these villages. So we have a lot of time to talk. And at some point, like Juan, you know, it gets kind of pensive. And he's looking out while he's driving and he says, you know, Tom, maybe there's just too many people. You know, maybe if we had half as many people, we would have a chance. We'd have a chance of creating a sustainable world. And like, I hadn't thought about this before. I didn't pre can this response, but it just like came out of me like a bolt. As soon as he said that, I was like, juan, we had half as many people 40 years ago. And if we continue to think the way that we did then and we do now, even if we had half as many people today, we'd have all the same problems in 40 more years. This is not a problem that's out there. It's a problem that's in here. The way that we're conceiving of our civilization is messed up. It's not that there's too many people. If you could obliterate half the population in a merciful way today. I don't even know how that makes sense, but if you could, we'd have all the same problems in 40 years. You have to understand that this is what's broken. So what does it look like to begin shifting consciousness about this? What does it look like? Well, this example over here. So this is the specific thing I worked on with him. So I'm an investor and advisor in this company, and they had originally created this solar electric box, bringing electricity, all these people for the first time. And these people mostly live on less than a dollar a day, sometimes $2 a day. And that said, they really, really wanted this thing. So the people that could afford it, they bought it. But there were so many other people that wanted it that couldn't. Because if you live on a dollar a day and this product costs $120, you actually never in your life have enough in your hand to pay for this product. You're living on a dollar a day. It comes and goes. It comes and goes. You Never actually have $120 in your hand to go buy this product. So we took a bunch of steps back and we changed the model. We changed the model. So instead of selling it to them for 120 bucks, we actually, for a small amount of money, like five bucks, we would give you the unit. And then when we gave you the unit, we priced it so that you bought electricity as you went. But we priced it in a very special way. We priced it so one week of electricity cost less than one week of candles, which is the way they currently light their houses. So literally, if you can pay five bucks, you're instantly saving money every single week on something that you had been doing forever. And using this mechanism, we got so many people were able to have electricity for the first time. Like, this was a long push. But in November, December 2016, we hit our hockey stick, and it's growing like crazy. And there's going to be over a million people this year that get access to electricity for the very first time because of this shift in consciousness. Now, here's another thing that you don't think about, but you guys are in Asia, close to ground zero for this, which is. My background is in hardware engineering. I've made a bunch of hardware in my life. And there's this whole discussion that comes in every real hardware setting where you need to ship. When you're talking about the bom, do you guys know what a BOM is? It's short for Build of Materials, B O M and what the build of materials is, it's the full list of stuff that goes into a cell phone or a computer or a laptop or whatever. And it's like how much all those things part cost. And you often add the labor cost in there as well. And altogether, the BOM is basically what it costs you to make the thing. Now, in the electronics retail world, you're constantly trying to reduce your BOM. Reduce your BOM. Why? Because if you can sell a laptop for 500 bucks, but you can make the BOM 80 bucks instead of 100 bucks, you make 20 more bucks. It's relatively straightforward. So actually, every hardware manufacturer in the world, whether you guys know it or not, is highly incentivized to make everything in your thing just a little bit cheaper. Just a little bit cheaper. Because if they can make it a little bit cheaper right up to the point that it becomes unreliable, then they will make more money. This is why if you have a cell phone that's more than two years old, it's a piece of junk, right? Like it doesn't need to be a piece of junk. Actually, the first cell phones from Motorola still work exactly the same. But in the process of optimizing the bom, every single company has basically said, well, you know, if you took this part and you replaced it with injection molded plastic, that'd be a little bit cheaper. And you know, if you took that injection molded plastic and you made the wall thickness a little bit thinner, you would save 5% on material cost in your injection molds and that would be a little bit cheaper. And you know, if you were to replace this transistor with this other transistor where the mean time to failure is five years instead of, you know, 11 years, that would be a little bit cheaper. A little. A little. A little. A little. And this is why there's nothing that you can buy today that you have any faith that will work in 10 years. Nothing. Now, when we started to do this model, when we gave the people the stuff and they paid as they went, it basically flipped everything on its head. Because what it said was, I did the calculation for the team. Hey, actually, if there's anything that we can do to this device that would make it last two months longer in terms of its average life than it's worth $5 for us to go add that. And we actually went back in and we took a thing that was $120 and we added $15 to it. And by the end of adding that $15, we'd made a thing that's going to last at least 20 years, probably 30 years. There's nobody in the hardware world that's incentivized to make a thing that'll last 30 years. We were. And that's actually because of a shift in consciousness. There was no difference in the true electrical engineering skill that was required. It was all about evaluating components and, like, looking at the time to failures and putting it together. Literally the same skill set. Just this tiny tweak in consciousness about where you make your money. If you make all your money up front at the point of retail sale, then you are encouraged every single waking breath to make it cheaper, a little bit less reliable, a little bit more margin, squeezed out, whatever, you'll throw it away in two years. If you are incentivized, instead of making all your money at point of sale, to make money by people having this as a part of their life for a long period of time, actually you're incentivized to make this basically indestructible. You will do much better if it lasts for 50 years than if it lasts for five, than if it lasts for 10. And this is the tiniest shift in consciousness, but the tiniest shift in consciousness completely change the economics of major businesses that we have in this world. So when you guys talk about, like, oh, everything's so broken and it's so hard, and like, why is everything throwaway? And like, why is everything so difficult? Recognize that sometimes it's things as small as this that can change the entire nature of how a person approaches an industry. And that is true about things in your industry as well. There's some things that you hate about your industry that the smallest change to how you're getting incentivized, how you're being paid, the way that you look at quality, the smallest change might change everything about what you do. And then this one is not applicable to the talk. So this is the end of this first talk. We're going to go do a quick Q and A, and then we're going to do a part two. Any Q's and as about this, creating a net positive civilization. That's all. You can clap if you want. There you go. I totally coerced you to clap. Go ahead. Who's going to invest in the tree technology? I can tell you, because a bunch of people invested in the tree technology. So Parrot, which is one of the largest drone producers in the world, has invested. We're in talks to go close about three quarters of a million with a forestry company because if they can reforest their areas faster, then they basically have a better asset on the land that they own. So there's actually a number of folks that people talk about what's the economic incentive for protecting the environment. But here's a thing that you may never thought of but like every single thing that you see in the world was either grown or mined. So it basically all came from the environment. So grown, mined, mind, you know, whatever. Everything around you that you see, the fabric in there, grown, like everything, every direction that you look, all the wealth in all of human history came directly from nature. Grown or mined. This is a way of growing basically. So there is no situation where this does not create a huge amount of economic wealth for us. We've just been doing it on borrowed time. Question right in front of you. That's easy.

Hi. So basically what I do is basically what you do as well. I'm involved in reforestation stations, I'm involved in green building.

Yes.

We reduce order energy by 70% and everything I do is actually to connect people back to nature. And I see that as a catalyst. And I saw another catalyst, it's how do I make forestry as an asset rather than a mere resource? Because we'd be identifying a few catalysts in the forest that you can actually protect a whole region of forests, let's say forest science chem and stuff like that.

Yeah.

So for my point of view, when I see this I see a lot of tools.

Yes.

But I think what's interesting is also the higher level than that whereby if you like, let's say if you let all these trees become machines to fix the world so it becomes a profit added to what are your trees for? So let's say in now we have tsunami etc, countries actually building coastlines.

Could you get to the question please?

Yes, it is a very long question so far. Yes.

Countries are building coastlines like coastal trees, like erosion protection.

Yes.

Yeah, yeah, yeah. So are you involved in things like that now? Like, are you looking at that now?

So this technology can plant any seed that is smaller than the seed pod. So if it's smaller than this, if the seed that you plant is smaller than this, it can plant it. So that includes like anti erosion shrubs and other types of things can be planted with this approach.

But is it something that you're actually.

Thank you. One question only. Thanks.

Yes, we're not doing that yet, but thank you for working on forestry. And the same sort of thing is true around incentives for forestry is what I was saying about hardware. Because if A company just leases land to go to go log. They don't take very good care of it. If they're going to own the land for more than 10 years, they often will begin reforesting. So really like a tweak in ownership structure and allowable ownership structures for that industry completely changes the incentives around how you treat the land. Yes. Back there, going back to the point your friend Juan had, do you think the way the population is scaling with this project, the reforestation project, would it be able to scale just as much? Because let's say in 100 years when there is no place for reforestation and people cover the whole planet, do you think we'll be able to scale the reforestation just as much? I know it doesn't feel like this in Asia, but like most of North America is unpopulated. Like, go into Google Maps and like scroll around North America, it's basically empty. You know, I don't know, South Asia and parts of Southeast Asia are not unpopulated for sure. But actually human beings do not cover that much of the surface of the earth. In terms of where we live, we farm 11% of the Earth's surface, of the Earth's land surface, we graze a bunch of percent. But actually the land that we live on is less than 5%. It's not. We're going to run out of land because we, we're living in too many places. And most of the world is still unpopulated. Most of the Amazon rainforest is unpopulated. We cut down like half of it, but people don't live there.

Tom, shall we go on to the next.

There's one more question next to you. That guy. Oh, there's two more questions and then we're good. You mentioned a little bit about growing grass and grass. Switchgrass. Yeah, switchgrass, right. Carbon negative switchgrass. A few sentences about that project. This is amazing. Okay, that was already one sentence, so we're almost out of sentences. So basically it's an engineered and selectively bred switchgrass that is designed to maximize the amount of carbon that is bound out of the air and into the soil. So soil is rich when it's rich with carbon. So if you've ever seen rich soil, it looks dark. That darkness is carbon. If you've ever seen degraded soil, it looks chalky or it looks reddish, it doesn't look black because it doesn't have carbon in it. So what rich soil is, is carbon rich soil. Now, it turns out that what plants like to do generally is take stuff out of the air. And make the soil richer. If you grow plants in a place long enough, the topsoil actually grows. But the way that we do agriculture does the opposite, because we've basically genetically modified and designed plants that deplete topsoil every single single year. So we dump fertilizers and so on and so forth. Well, this team in Berkeley basically has gone into the basic genomic mechanisms by which plants are able to go bind carbon out of the air into the soil, and they've amplified those mechanisms. And what this then allows you to do. One example of what this would allow you to do is create a breed of switchgrass, of which I've already seen, because they have a hundred of these plants I was visiting the lab a couple months ago, that binds a lot more carbon out of the air into the soil, makes the soil richer every year that it grows. And here's where it gets interesting. When you cut the switchgrass off and then you make it into biofuels, that's a carbon negative biofuel. You can put it in your engine and you'll still be carbon negative. Why? Because all the stuff that you cut off burns back in the air, but a bunch of it's still left in the soil. So every single year that you use that fuel, the topsoil is improving. So imagine driving cars around, and as you drive cars around, you know that actually you're improving the topsoil and fixing more carbon into the planet than you're using. That is a possible future as well. And overall, like, this is not out of the realm of economic possibility. If you look at the way that we grow crops, about only one third of the crops that we grow actually go to feed us. Right? And a bunch of that goes to food waste. So not even the full 1/3 of it, half of it goes to feed livestock, and then one sixth of it goes to biofuels right now. And if you were to shift that mix, which is like, and it's got perverse subsidies for corn ethanol and other things that are not actually productive. But if you could switch out corn ethanol subsidies with like modified switchgrass, that is like building soil, you can plant switchgrass on all these degraded lands, build up your soil, create a carbon negative biofuel, and then change the mix of, of oil consumption to oil that actually makes it so that our planet is getting healthier when we drive with gasoline. So, yes, invention catalyst. This is my job. Yes. Last question. Okay. No, just use it. It's good. We have the technology. Sorry, just a quick thing about your king Energy thing. I was wondering if you had any ideas about how to encourage say big appliance manufacturers to move to like a subscription based model the same way that you guys did. Because then we'd have indestructible washing machines and stove tops. You know, we're actually almost not that far because cell phone carriers are playing around with what if you just paid a certain amount per month for the device and actually you automatically upgrade when it gets to two years so they reclaim the device and then they give you the updated one or you can keep it and just keep paying that amount. So we're not crazily far from it, but we're still using, we're still doing that in a way where it's like based on the old cell phone designs. It hasn't closed the loop tightly enough where it goes back to the fundamentals and say, how can we design for disassembly so that when we reclaim the thing we can reclaim all the materials in it. How do we design for robustness? So people don't like trade it in because it breaks too early, right? Because like actually it's a chain. It's a pain to go change in your cell phone because you have your contacts and all your text message history or whatever. Actually probably people would want to hold it longer if it didn't break in two years. So I think people are beginning through the carriers to experiment a little bit with the model, but because it's more diffuse ecosystem, they're not closing it tightly like the way a startup can. So it's totally possible. These things are really like one or two sentences of difference in thought and we're not, in a way, we're not aware enough or we're not brave enough to hold that thought long enough to change something with it.

Okay, thank you, Tom.

Okay, that's that talk. So.

I know. So please, round of applause for Tom.

Prompted applause so how are you doing? I'm totally fine. Like Vishen said, hungry, you need water?

Because Tom basically slept for four hours on the flight to kl.

No, I came directly here from San Francisco. It was like 19 hours of travel. This is four hours. Crap. What?

How many hours of sleep have you had?

Oh, I had four hours of sleep. That's right, four hours of sleep.

So anyway, kudos to you. So I know a lot of you also came here for the rapid prototyping talk. We're going to go into that next.

And change that talk to the other talk.

Yeah, so so basically you're getting two talks for the Price of one. But it was really important that.

Tom, what did they pay? No, I'm just kidding.

20 ringgit just to cover costs.

But. Oh, they actually paid something. That's nice.

Yeah, because otherwise, otherwise we have like 300 people over here. I mean you're the co founder of Google X. This would sell out really quickly. So to avoid like health hazards and stuff, that's why we asked for 20 ringgit. But basically it just covers cost. So Tom's main thing right now is doing good. His Twitter handle is the Good Tom Chi. It's about helping people awaken to the fact that global warming is one of the craziest threats facing humanity right now. And we can do something about it. As you saw from the drone project. Right. That can be achieved for 0.01% of the US military budget. It's mind blowing what we can do when we apply our brains. Now the question is, how do you apply your brains to take that step forward? And this talk is mind blowing. So Tom, whenever you're ready.

Okay. Sheesh. He talked it up way too much. Everybody lower your expectations. Lower your expectations. Okay, cool. Yes. Talk number two. It's all good. Yes, thank you. Everything is happening. And he was like, oh, your Twitter handle is the goodtomchi. Because I'm doing all this good. No, actually I got that the Goodtom Chi nickname from my hip hop group 20 years ago. So that's whatever. Okay, check it out. So this talk is called rapid prototyping X. This is. You saw a bunch of these invention catalysts like the self driving car and like these drones and switchgrass we talked about. But I didn't make the slides for though it's amazing. This is really like how does one. What are the practices that one uses in order to go invent in that way? And it's called rapid prototyping X because it was the foundational practice of how we did our work inside of a group called Google X. And Google X invented the self driving car and project loon and the contact lenses that do continuous glucose monitoring and Google Glass and the new approach to artificial intelligence called semi supervised learning that used 64,000 simultaneous cores in order to automatically recognize cats from YouTube. There's lots of cats in YouTube. That's what we found out. And a bunch of other stuff. So how do we do that? Oh, and actually here's kind of the secret secret which is that like the assumption is when people hear all these things that Google did on that front, it's like, well, it's because Google's got like a million great engineers and they've got so much money and they threw all these resources. That's all things that did it. But if you guys have heard of Project Loon, it was five people in four months built 100 hardware prototypes for $70,000. And by the end of that hundred hardware prototypes, we had multiple balloons up at 25km doing laser line of sight network communications with each other. That is not a lot of money. That is not a lot of time. That is not a lot of people. That was true of the tree planting drones too, right? 13 people over two years and very little funding, about a million dollars of funding, basically created something that could turn back all of climate change. Now it's really not so much about whether you're throwing millions of dollars of resources or tons of people at it and all that sort of thing. It's really about the way that you're doing that work. And this talk is really about how you do that work. So on my first day of the job at Google, I got in there and there was no Google Glass. There was no cars, there were no balloons, there was no contact lens. It was just eight people in a room talking about, like, what's the group that we're about to go make? And we also had a piece of paper that said something like, what if Google was in your brain? Which sounds kind of terrifying. And then the couple sentences after that said, well, what we mean is, right now Google is a webpage that you get to on a browser, and that browser is accessed through a device, and you get on that device by logging in, or if it's a mobile, you unlock it and you gotta open the browser app and whatever. And it's like, given that the distance between you wanting to know something and actually knowing it is all these steps, these four or five steps. So they imagined a world like, what if in the future, as soon as you want to know something, boom, you would instantly know it. And wrote about a paragraph on it. It covered about a third of the page. And the very last sentence of that, not even full paragraph, basically said, realize this in less than five years, done. So we basically set out to go, realize that in less than five years. And don't worry for us, because we were done in nine months and we had made this whole thing. But I'm scooting to the end a little bit. Like on that first day when we got that prompt, nobody knew how to do it. So we all just kind of jumped in and we began working on this together. And we had these amazing people in the room. We had Sergey Brin, one of the co founders of Google. We had Sebastian Thrun, the best probabilistic roboticist in the world. Astro Teller, the guy who does the moonshot talks, and just a great entrepreneur. Babak Parviz, amazing bioengineering and electrical engineering genius that now is the head of innovation for Jeff Bezos at Amazon. And for whatever reason I was in the room and we're all talking and we start like working on this thing and things are going really amazingly for the first half of the meeting. And we're getting lots and lots of progress on how could you make it so that as soon as you wanted to know something, you would instantly know it. And during that time period we kind of posited, well, you know, we could build a heads up display that's completely achievable in less than five years. And that's one thing that's on a stepping stone toward instantly knowing things as soon as you wanted to know them. Now that was the first half of this 90 minute meeting. And then the second half of the 90 minute meeting, everything went south. And it went from one of the best meetings I had had to one of the worst meetings I had ever had. Because what happened in the next 45 minutes of that meeting is we spent the full 45 minutes with these eight brilliant people arguing about what color the heads up display was going to be. And the thing that happened at the end of that argument, which is the thing that happens in most arguments like this, is they tend to be settled either by the person that argues the most effectively or loudest, or the person that has the highest title in the room. And that particular day, those two attributes belong to the same human being, Sergey Brin. And he basically told us unequivocally that the color of the heads of display was going to have to be red. And it had to be red for two really important reasons. Number one, red photons are less energetic, so when they hit your eye, it's going to be less energy on your retina. And less energy on your retina means less eye strain. So if you're going to wear it all day, it's best to have less eye strain. Reason number one. Reason number two, it's always red in science fiction. So remember though, that everybody in this room, Sergey, is our boss. So I think the majority of the room is kind of like nodding like, okay, well that's what the boss is saying then I guess that's our marching orders for the next couple months. We can make a device that does red. We'll get red display drivers. We'll go do our optics chain so that the index of refraction is appropriate for red, whatever wheel spinning for most of them. For me, I had an immediate visceral reaction to that moment where I was like, no, this is not how we're going to do this because we are a totally new group and we don't need to act like a bunch of idiots. And that was an idiotic way to decide this question, right? This is the first day of a new group. We do not need to be dumb like this. And I know a number of you guys already look surprised. I already told the mindvalley crew this, but I'm maybe unusual because I have like, I have no special respect for authority, which means that it doesn't mean that I actively disregard authority. It's fine. But it's like just because you're three levels higher in the organization or because you're a billionaire, it doesn't automatically give me instant respect for everything you say. Like, I listen to as deeply and respect just as much stuff that comes from people that are at a lower station in society. As long as it makes sense, I just listen for whether your thing made sense or not. And that particular moment, Sergey said a thing that made honestly no sense. Everybody nodded because he's our boss, right? But like, but I left that morning and said, no, we're not going to do it like this. And I vowed like, okay, what's a better way to decide this? Well, we can't just like guess at each other. We gotta go do this in a more principled way. Why don't we just build a heads up display and try out all the colors we were arguing about and find out how it is. So for folks that don't know the answer to the question, how long do you think it took to go build that first heads up display where we could try out all the colors and answer the question that was raised that first day? Anybody? Two days. Two days, Cool. Anybody else? One day. You guys are all fast. I'm looking forward to the future of kl. So you're all actually very close, but still long. It was working by early afternoon. And this is the second one that was built. So I guess I built like slightly more than one per hour. Now the first one, this is the second one. The first one you wore on your head and the display was here. And I learned from the first one that you can't focus on a display that's this close to Your eye, not without a bunch of optics in the way. And I wasn't going to cut a lens that morning, so. Cool. So the second one I built, I moved the display a little bit further away. So here's just some dude. And the display is this far away, so it's easy to focus on even when you're looking at distant objects. And that's mounted on a piece of plexiglass that has a coat hanger at the base. One end of the coat hanger hangs behind the neck, the other one rests on the chest. And what this leads to is a screen that's floating right in front of you like this, no matter where you turn, no matter where you walk. And basically anything that you can put onto the little laptop that's running the projector, you can see floating in front of you. So given the debate that morning, the very first thing was let's make a paragraph of text and let's put it in every single color of the rainbow. Then somebody can try to read the paragraph of text in this color, flip to another color, try to read it. You know, a different paragraph or the same paragraph doesn't matter, really. Flip to the next color, flip to the next color, try to read all the colors. So I put this simple prototype together and I grabbed all these people that were in the meeting room that morning. Remember, these are the same human beings that spent 45 minutes arguing about this. In less than 90 seconds of actually living the experience, every single one of us agreed that red was the absolute worst color for a heads up display. In that same 90 seconds, we actually got to try every single color. And we agreed red was the worst, purple was the second worst, and the best colors were yellow, white, and light blue. There's almost no variation across the eight people in terms of ranking once we actually had the direct experience. Now think about this. We debated it for 45 minutes versus 45 minutes of guessing. Compared to 90 seconds of direct experience. That's a major, major speed up. And what's really ironic about red being the worst color is it actually turns out that red is the worst color for a heads up display for exactly the reason that Sergey said it would be the best color for a heads up display. It is true that red photons are the least energetic. It is true that they impart the least energy to your retina. And what that means is when you're looking at a red display display, every other photon in the environment out competes the red. It literally means the display is the hardest thing to see. Now, red Works fine for night vision because there's nothing else to look at, right? But like in a lit environment, red is the worst color for a heads up display by far. Now what's curious about that is I bet when I shared that first reason a couple minutes ago, it actually sounded kind of smart. Because who can use the word photon and retina in a way that is correct with physics in a sentence and not be smart? But here's a really important thing to take back to your work. Smart people will always give you smart reasons for their guesses, but it doesn't make it so they're not guesses. The most important distinction is not whether a guess sounds smart or anything that you say sounds smart or sounds dumb or sounds in between. The most important distinction is is it a guess or is it a direct experience? A direct experience cuts through all the crap, right? It doesn't matter if your guest sounds smart, doesn't matter if your guest sounds dumb, it's a guess. Your direct experience will still always trump that will still always be a clear indicator of what works and what doesn't work, because you're living what you're talking about instead of conceptualizing about it. And the entire point of prototyping is to bridge that gap because I find that most businesses live their entire lives on the guessing side of the gap. Let's guess and debate and argue and make decks and present to each other and vote on and have somebody decide that has the authority. Da da da. These are not direct experiences. What prototyping says, well, that 90% of your life that you spend at business doing that, that's actually worth almost nothing. So like, let's save 90% of your life. Let's go take some of that energy and move your guesses into direct experience. And rapid prototyping is the process of teaching people to get to direct experiences as quickly as possible. Like, it sounds fun to go build this in an hour and build the next one in an hour. But what's more important is in two hours we're living the direct experience of made it so that we didn't need to keep guessing for weeks. It made it so that we didn't need to argue about this even one more time. That is the main thing that gets saved. A debate like this in most companies would last for weeks, sometimes months. It was settled that day and we settled new things the next day and new things the day after that. So let's go to another example. So a bunch of weeks into the project, we had tons of heads up displays no big deal. But we discovered in having lots of heads up displays, one eyed heads up display, two eyes heads up display display, full color, black and white. Every kind of heads up display is that regardless if you're wearing something on your head, then you don't have a keyboard and you don't have a mouse and you don't have a touch screen unless you're going to poke at your eye. So you don't have any of the ways that you normally would interact with software. Though I did build a keyboard that works like this. But you make a lot of mistakes. So we had all seen this movie though, and we kind of thought to ourselves, well, hey, if you're wearing something and it had a forward facing camera, then you could see your hands. If you could see your hands and you knew where the display was and you knew where your eye is, you have all the geometry that's required to make it feel like you're just directly touching, directly pressing that button, directly grabbing that window and pulling it to the side, minimizing this pulling up the keyboard directly by just touching the thing that's floating in front of you. So same question as before. How long do you think it took to build the first version where folks could move their hands in space and feel as if they're manipulating the software that's floating in front of their eyes? Anybody? It's so quiet. 30 minutes. 30 minutes. Damn. Anybody else? A week? Are you guys thinking about how fast you would do it or you're thinking how fast I would do it? Because I'm either super impressed or not impressed. So it's good. So you're very close. It's 45 minutes. And the way that it got done is we had advanced technology. We had a rolling whiteboard, and on the top of that rolling whiteboard, I taped a coat hanger shaped like a W. And in each one of the grooves of the W, we put a little strand of fishing line. At the end of each fishing line, we tied a hair band. And like, you're actually very close to the right amount of time. Because in that 45 minutes, 20 of that minutes was spent finding two hair bands in a department, mostly of men. So the actual assembly was 25 minutes. So 30 minutes was very close actually once the materials were together. Now what the heck is that for? Well, what you do is you put a hand in each hair band and when you move your arm, it basically creates tension on the line. As tension goes on the line, it pulls up the other end of the line and that other End of the line is tied to a chopstick, pivots over a binder clip, has a pen as the fulcrum, and the other end clicks a presentation clicker. So it means when I do this, then the screen will change. And using something like this, I can have an image gallery where I say, next image, next image, previous image. I can have an email program where I say, open that email, press reply, begin typing. Right, I can have. And we built five different pieces of mock software in about 30 more minutes after the the hardware was built. A media player, an email program, a social media feed, dah, dah, dah. Like all these different classic interactions that you might want to go do with software. And as soon as that was done, a good rule of prototyping is you should never be the evaluator of the thing that you built. And knowing this, I was like, I should not evaluate this, even though it's pretty badass. So I went and grabbed like five people from the office one by one, and I brought them over. And the second person that used it, we started discovering things very quickly. The second person that were not expected, the second person that used it, Ricardo, he straps into the thing and he starts moving around like this and clicking all the things just as I demoed for five seconds. And little by little, he starts making smaller motions. And literally in about 30 seconds, he's doing more like this. And I was like, ricardo, what the hell are you doing? And like, I think I said, you're using it wrong. But that's never what you're supposed to say. It's fine. We're all user experience professionals. So he knows that I was just messing around. But he was like, look, Tom, I could do this. But it turns out that you only need to apply about this much force and it'll change. So why would I do this if I could just do that? I was like, oh, that's actually pretty smart. That's probably a thing that people would figure out over time. And when we chatted about it a little bit more, we dubbed this the Wii Tennis effect. Have any of you guys played Wii Tennis? So the first week that you get Wii Tennis, you're running around the living room like, yes, yes. And by the third or fourth week of playing Wii Tennis, you're on the couch like this because you find out eventually that you just need to do this. That basically does it. You don't need to do all the running. You don't need to knock over the lamp. You can just sit on the couch like this. People eventually Figure out the minimum amount of effort. Now, the fourth person that used this, he didn't discover the Wii Tennis effect because I was bringing the folks over one by one. He didn't get to see what Ricardo did. And actually exactly the opposite. He used all five software prototypes. And he was so enthusiastic. He's like, I'm like living in the future. This is blowing my mind. Like, wait, he got to the end. He's like, that's the last one. Wait, do it again. And of course it's slidewear. So I just like blurp, press a button and went back to the beginning. And like he was doing it again. And because of it, he ended up using the prototypes longer than really anybody had so far. And a couple minutes in because you're not supposed to like, you know, interrupt them doing the stuff. So I was just observing and as I was observing, it's like he started to exhibit these unusual behaviors. Like he stopped between, you know, one of the prototype changeups and he's like grabbing his, his shoulder and like shaking on his wrist a little bit or touching his elbow. And I was like. And after I observed this, you know, two, three times, I was like, hey, stop for a second. What are you doing? What's going on with your shoulder? He's like, well, I don't know, it just feels a little funny. Like hurts a little bit. And my first thought was, well, this is a person that just has some weak ass arms because, you know, engineers are not selected for upper body strength. So I was like, cool, let's try this again with some people that really work out. So I went and grabbed some people that like, and I had them use it a little bit longer because I only seen this from the one person that used it longer. And actually it turned out a couple minutes in, same sort of thing started happening. And I asked them about it and they were like, it doesn't hurt yet, but definitely feels a little weird. And we learned from trying about four or five more people that if you have your hands above your heart for more than two minutes, your joints will hurt, period. Doesn't matter if you move them, doesn't matter if you hold them still. You can try this at home. This is a very easy experiment. Like in 2 minutes your joints will hurt. Now the one thing that we were not going to change, no matter what we prototyped, is we were not going to change it so that your eyes were not above your heart. So given that this is software that you're supposed to control at eye level, you just can't get away from your hands being up here and when they're up here, which gives you the illusion of really touching these things, then it's above your heart, your arms will begin to fatigue. So it was actually for that reason we built a 45 minute prototype and we discovered something that was really fundamental about human physiology. And it was for that reason that we decided not to go down this direction for Glass. This is a funny story, but a couple months after doing this experiment and deciding not to go down this direction, I ended up finding an article where Tom Cruise, this dude, was being interviewed about filming the Minority Report movie and he revealed in the article, because people were asking from a techie angle, hey, what did you think about that new interface? It was so inspiring. He basically revealed in the interview that when he was filming these scenes, he had to take breaks every 10 minutes because it was exhausting for him. And as far as I can tell, this guy's only job is to stay fit and to act a little bit. So like, if that sort of person is exhausted by this in 10 minutes, this is not our future. If you ever see this in science fiction, that's the fiction part of science fiction. Like we cannot have our hands up here for more than a couple minutes without being exhausted. Cool. So we're going to go faster because this is like a pretty corporate y example. It takes a long time to say. So we're going to go do, we're going to jump into the theory because I also want to give you some time to ask questions. But that's some two quick examples of prototyping and that's the practice. Now we're going to get to the theory. The theory is actually relatively simple. So let's say any new idea that you try has got maybe a 5% chance of success and it's not a perfectly accurate number, but it is pretty close to the percentage of startups that end up having some type of successful outcome and is also pretty close to the percentage of corporate innovation ideas and that are still around two years after they get kicked off within the corporation. So this number is actually pretty close to the success and longevity ratio of new ideas that come out. Now. This is not because the people in the other startups weren't working hard or they didn't feel that their idea was interesting or the people in the big corporations didn't want something innovative to happen. I think this boils down to the simple fact that not every idea works. Now, if not every idea works, then maybe 5% of ideas do. That means that by the time you try 20 such ideas, your overall chance of success jumps up to 64%. And by the time you try 50 of them, it jumps up to 92%. And if you guys have ever read Lean Startup, this is basically the same insight as Lean Startup, but basically taken to the extreme, because what Lean Startup basically request of you is don't just pick your startup idea and burn all your money to the ground over two years. If things aren't working, you might want to pivot, and if that's not working, you might want to pivot again. So they Recommend Go for 6 months. Pivot or persist. Go for 6 months. Pivot Or Persist. So with your 18 months of funding, you might pivot or persist once or twice. So the same math that makes this really good also makes three tries better than one. It's just that when you try three times, it doesn't get you up to 92% chance of success. It gets you up to like 11 and a half or 12% chance of, of success, which is still way better than five. Which is why Lean Startup actually is a revolution. It, like, improves your chances a lot. But if you wanted to improve your chances a lot, a lot, a lot, a lot, then 50 is way better than three. Now, anybody that's good at math in here, they actually recognize that these numbers that I'm using, I'm super low balling these numbers, because one thing that I'm putting in this calculation is I'm assuming that you don't learn anything between trials. This is as if it was pure chance every single time. In truth, as you do these trials, you learn more and more and more. So the worst you could do after 20 trials is 64%. You tend to do much better. The worst you can do after 50 trials is 92% chance of success. You tend to do much, much better than that. But the way that you actually achieve this is just this single sentence. Instead of trying to get the right answer on any given rev, what you're actually trying to do in this process is you're looking to maximize the rate of learning by dramatically minimizing the time to try things. So it might be fun to go build the Minority report interface in 45 minutes. But what's more important than building in 45 minutes is the time to try got really, really small. So we learned everything that we needed to know about that interface literally within one afternoon. It was built, you know, mid morning, and by two in the afternoon, we learned everything that we needed to learn about that that same Learning could have taken us two months. You know, my formal training is in electrical engineering, signal processing, control systems, robotics. I know how to go build the same minority report interface with an IR time of flight sensor that basically creates like a point cloud that can be resolved into a skeletal model which can be mapped into a gesture mapping library and so on and so forth. But that would take like five days to do, right? So it's like instead of learning that same lesson in five days plus testing time, we learned it by like two hours after lunch. And when you do this consistently inside of your organization, you can learn into impossible things like making a self driving car or putting balloons to go provide Internet to the air. Because you are doing 100 hardware prototypes in four months instead of doing two hardware prototypes in four months. Just the reduction of the time to try cannot help but increase your rate of learning. So the thing that's under your control is not whether your next trial is going to be successful or not. Let's just say all trials have got a 5% chance of success. You never totally know that the next one is going to be the one. But what you absolutely can control, even though you cannot control whether the next one is going to be the one or not, you can control how much time it takes you to do a trial. So every single one of you in your businesses, there's a way, there's a way that you're making things and there's a certain amount of time it takes to go try a thing in the way that you're making things. And whatever that time is, quantify it. Maybe it's two months for you, maybe it's five weeks. Maybe for some companies that I've worked with is two years, right? And whatever that time to try is challenge yourself. How could you make that five times faster? How could you make that 10 times faster? How could we get the majority of the learning from a lighter prototype? That might happen in 1/5, 1/10 of the time. And when you begin to act on that, then that is the process that makes it so that your rate of learning goes through the roof. This is a really important. I'm going to talk a lot for a slide that has almost nothing on it, right? And actually it gets worse after this because there's some slides that have even less and I'm going to talk more about them. But existential question, why are big companies afraid of startups? Because you know, all these big companies are at that. It's like we gotta be more like startups, we gotta be competitive and innovative. Like startups, like these startups are gonna eat our lunch. Now. You hear this all the time. You read Harvard Business Review, you read Fortune, you read whatever. This is what it sounds like from big companies. But why are they afraid of startups? Well, here's the thing, it actually turns out that startups have almost no advantage over big companies because big companies have tremendously more financial resources, right? They have way, way more money to go apply to any kind of thing that they could to go innovate. So it's not the money, it's also not the people. A lot of times people like mythologize. The founders were so amazing and they could never be replicated. Trust me, if your big company has more than 500 people in it, you have more smart people than basically any startup, any like 10 person startup, right? So all these 10 person startups that people are intimidated by, if your company has more than 500, 1,000 people, you definitely have more smart people than them. So it's not having more money, it's not having more smart people. The only advantage that a startup has is its rate of learning is higher. And what it looks like is this. If you're the big company and you're plugging along and you're improving your product little by little, and you're learning about it little by little, quarter over quarter, year over year, and then here's this startup down here with no market share, but they're learning like this, it means that because of their higher rate of learning, at some point these lines will cross. And just the fear of those lines crossing, that is the biggest, most essential, scary thing about a startup. Like the only advantage that a startup has is managing its rate of learning. So if you are focused on anything else in your startup, you're giving away the one advantage that you have. And I'll make this point even harder because as an investor, here's a thing that I actually do. So I invest in a bunch of companies and I have this really unique way of evaluating companies. I don't give them just one meeting, I give them two meetings, but they're shorter meetings, right? So I don't give them an hour. I might give them two 30 minute slots, but those two 30 minute slots are spaced six weeks apart because they're going to come in and they're going to tell me the thing in 30 minutes, give me the whole pitch, da da, da da. If I then see them in four weeks, six weeks, and they're telling me the same stuff, that basically means their rate of learning in the last six weeks was zero. That means the one thing that they could possibly have as a startup to their advantage, they don't have. And it doesn't matter how good you gave the pitch, how charismatic you are, all the numbers that you put in your model, that seems so convincing. If nothing changed in six weeks, you have forfeited the only thing that a startup has as its advantage. And I instantly don't invest. Right. So think about how many times you use the same pitch four weeks later, six weeks later. No. Like, if you're in a thing that is meant to be your bread and butter in terms of how you're changing the world, that better be changing every four weeks. Every six weeks. I challenge companies that I work with. It's like you should be getting three to five key learnings every single week that materially change your business. I want to see them. If I come in two weeks later and you don't have another eight for me, I question this. What are you doing then? Where did these last 10 days go? You had an ideal around how to pitch this to your customer. Where's the results from that? How did you change the pitch? How did you improve it? You had 10 days. That's a long time for a startup. That's forever. So I'm dwelling on this because this is the heart and soul of why startups are innovative, but it's also the heart and soul of how big companies can become innovative. It's just simply this principle. Now, there's two corollaries to this principle. One of them is you don't need to guess. You can just learn. So there's an implicit calculation that everybody is doing when they spend all their time guessing and debating about what they're going to do. And that implicit assumption is that guessing is cheaper than building. Because most of us are told, hey, well, you have an idea in a meeting, well, just put your best educated guess out there, because it's really cheap to guess. It'll take you 30 seconds to think of your guess, and it's really expensive to build. It'll take us four months to build it. But actually, both of those statements are wrong because guessing is not that cheap. What happens is when you start guessing is everybody's guessing at each other, and you get all the way to the end of the meeting and you haven't decided on it yet, and you're like, we didn't come to resolution yet, so let's reconvene next week to go talk about this more. Okay, fine. So you're guessing Some more next week, and it goes another week. And by the end of that's like, well, we really need to decide by now. And so. And so made a deck about this, and that looks pretty good. So why don't we. And by the end of it, you spent three and a half, four weeks to get your guests done. Now, if you can actually prototype, if you can convert something from a guess into a direct experience in an hour, in a day, in two days, then actually solving the problem with direct experience becomes cheaper than three and a half weeks of guessing. Just think about the last important decision that your business made. Did they make them in a day? Did they make them in two weeks? Did they make them in five weeks? If you're up in the weeks range, trust me, you could have built it in less time, had the confidence of, this is how it works. I've experienced how it works. We made the decision because the direct experience was amazing. So when you begin to prototype fast, then you can give up on guessing, period. You can take this 90% of the time that you spend at work debating each other's guesses and just get all that time back and use a fraction of that time to just build direct experiences and another fraction of that time to go test those direct experiences customers, and it will get you to the same places 10, 100 times faster with more confidence. Second corollary, do not fail, learn. So in the Valley, we popularized this phrase called fail fast. Fail fast. And it's not actually completely accurate because you can learn without failing and you can fail without learning. And luckily, there's this in between where you can both learn and fail at the same time, which is why it's not a completely untrue statement. But the real statement is to learn fast, not to fail fast. But there's another important distinction around the word failure itself, because there's something very powerful that happens to the mind when you believe that something has failed. When you believe that something has failed, then it darkens a little spot in your mind where you don't want to go visit that idea anymore because that's a failed idea. And not only does it darken that spot in your mind, it darkens anything that kind of sounds like that idea so that you won't go anywhere near it again. And like, you guys have witnessed this, you definitely have witnessed this in your meetings. If you've ever met some, you know, if you've ever been in a meeting where somebody's new to the company, like, let's say they joined the company two months ago. And they're so enthusiastic and like, oh, guys, over the weekend I was thinking about this and you know how we want to go into this market. I've got this idea and this idea and it's like, it's great. There's all this energy coming for it. And then somebody who's been at the company like three or four years, they're kind of leaning back. It's like, I'm just going to stop you right there because two years ago we tried something just like that. I don't want to be a jerk, but like, I just don't want you to waste your time, right? Like the old timer right now, what's happened to this person is not that they actually totally know what's going to happen here. What's happened is in their brain. They've given themselves a special type of brain damage where they've darkened the spot around the failure. And anything that sounds like that, they'll also shoot it down. And the reason that that is dangerous is many, many things. And probably close to most of the things that end up being successful in the long run are only a little bit different than things that failed in the past. So when you darken the spot around that failure and you darken the things that sound like it, you're probably also flushing the solution down the toilet. So every time you darken that spot, you're giving yourself a type of brain damage that might make it impossible for, for you to solve the problem in the future. Now, this is a choice, though, and people don't recognize it as a choice because they say, this didn't work, it's a failure. But actually, failure is not an event. Failure is an attitude that you have toward an event. The actual event was, it didn't work. And I'm not telling you, like, go pretend that things that didn't work worked. That's just delusional. So don't do that. But if a thing didn't work, you can have an attitude toward it like it failed, let's never go there again. And anything that sounds like it, I'm shooting it down. And like, I feel bad and like, we wasted all our time. That's an attitude that you can have toward the event that it didn't work. Another attitude, and very unproductive. It is a type of brain damage that we give each other and we give to ourselves. So I would not recommend that attitude. Another attitude toward the same event that it didn't work is, oh, what might I learn from this? That's a very interesting Attitude, a better attitude. To both of those attitudes, the best attitude is it didn't work. Okay, what's 5% of it? What's 10% of it that did work? Because what you're challenging yourself is to go look in there at this thing, that maybe the totality of it didn't end up the way that you wanted, but probably in there, there's something that's valuable. And I'll give you a specific example from my time at X. At the. At the end of the first week, everybody on my team had made roughly 3, 4, 5 prototypes in the week. And we were supposed to do our share on Friday. And our interaction designer, Bob, he basically came to me before the meeting. He's like, hey, I made kind of four and a half things, but really only one of them worked. So maybe I can save time in my presentation today by just talking about the one that worked. I was like, bob, tell me about some of these other ones. And he's like, well, there's this one, but it totally failed. And this one totally failed. Hold on a second. This one that you said that failed? Is there 10% of it that did work? He's like, what do you mean? I mean, we ran the prototype. It didn't work. What do you mean 10% of it that would work? It was like, well, I remember seeing you put that prototype together, and as part of that prototype, didn't you need to write some websocket code? He's like, sure, absolutely. And that allowed us to move data into the prototype in a really useful way, right? He was like, yeah, yeah. He's like, did the WebSocket code work? He's like, yeah, sure, it sure did. Is that code that we could use on another prototype? He's like, absolutely. So I said, well, great. That's 10% of the prototype that worked. Even though the data that we put through and the experience that we created through that websocket was not something that people liked or enjoyed or worked for us, that's fine. There was 10% of it that did work, that websocket code. And what happens in your brain there is. Instead of darkening the spot around that experience, it lights up a little spot around, hey, we have this little websocket code we can use on a different prototype. Lit up a spot. I went to the next one. I was like, okay, how about this prototype? He's like, oh, no, that one was a total failure. Not a single person liked that. I was like, there's not 10% of it that Worked. He's like, well, no, definitely not. I was like, look for that one. I remember that you had to create a new research protocol because this is the first time we've ever worn software on our head. Everything else was screens and maybe a mobile screen before. Like, we didn't have any research protocols for things that were worn on the head. So I remember you made a new research protocol for this. How did that research protocol work for this type of experience? He's like, oh, that worked fine. I mean, people didn't like what we created, but it's like the research protocol was good. We got good data from it. So I was like, well, great. Well, that's 10% of that prototype that worked. So that lights up another spot. And all that creativity and problem solving is it's completely driven by how many light spots you have in your brain and how well connected those light spots are. The more light spots, the better connected those light spots. The faster you solve any problem, the more creative you are, period. And it's true on the individual level, and it's true on the team level. So when these moments happen where things don't work, you can choose to give yourself a type of brain damage, or you can choose to actually accelerate the speed at which you learn and solve any problem. It's just the question of whether you install a dark spot or a light spot at that moment. And if you guys have ever seen somebody. You guys have witnessed this phenomenon before. If you've ever met somebody who studied two different fields of study in school. So maybe a person studied both architecture and dance, and if you hang around a person like that, they'll see a dance. And in the process of seeing the dance, they'll see how the relationship between the dancers creates architectural space that people are then playing. And they're seeing so much more to it. And when they see a building, they can see how the shape of the building is evocative of a type of motion. Or the structure of the building allows people to flow with each other in a particular way. They see more. And the reason that that happens is they have some light spots that lit up from architecture. They have some light spots that are lit up from dance. And those light spots are really well interconnected because they're in the same brain. And these people almost cannot help but be more creative than regular people. They are the living, breathing example of just having more light spots. Now, you can sabotage that if you become like a super critic and you put in a bunch of pothole dark spots, too. So occasionally you'll have a person that studied a bunch of disciplines, and they're such a downer on everything, they ruin it. But for the folks that don't do that, you've seen many a time, like what it looks like for people to work with a lot of light spots in their brain. And the same thing that happens for these individuals you can make happen for your whole organization. Because every moment that a thing doesn't work, you can ask your team to take that attitude of lighting up the spot. As you light up a bunch of these spots, you can start interchanging them. Trade the light spots with each other in the meetings, even if the overall prototype did not work. Trade the light spots. Trade the light spots. Trade the light spots. This is how you get better interconnection between the light spots. Even if different people did the prototypes, even if they weren't in the room at the same time. It's like this is how you light up the collective brain of your organization and make it more creative and faster at problem solving. All right, so very close to the end, this is the entire presentation again in one slide, which makes you think, why did I spend all this time? But along the bottom is the time axis. And on anything innovative, we always start in the unknown. We don't really know how we're going to solve the thing. And after a specific amount of time, we're going to arrive at one of a range of possible outcomes. And really, all I'm talking about in this talk is that this process of going from having no idea how to solve something or be innovative on a thing to landing on a great outcome is actually something that happens in just two phases. And the two phases are called research and development. Now, development I'm not going to talk about, because this is actually what they teach you in school. Business school, engineering school, design school, they teach you development. And what the nature of development is, is once you know what you're trying to go make, how do you use your people and resources efficiently to go make that thing with quality? Right? This is what they teach you in school. And I'll just presume that you guys do enough of it because you all work in companies where you get to do some type of development work. But not only is development not research development, research and development are actually opposite disciplines of each other. And what I mean by that is the following. When you're in the development mode, your overall focus is, let's get more and more narrow, and let's go really, really deep. I want to narrow in on exactly what we're building, build it with efficiency. And I want to go really deep. I want to take it all the way over the finish line. The nature of development is a narrow and deep discipline. The nature of research is the opposite. Research is not narrow and deep. It is broad and shallow. It basically says in the shortest, the shallowest amount of time, I want to hit the broadest range of possible outcomes. Because in the very short amount of time, I want to explore a very large percentage of the possibility space. And it means that by the time I've explored a lot of that possibility space, when we decide to go put something into development, it's the sort of thing that is worth taking over the finish line. And what innovation actually is, is the research process, the development process. I don't know, you can go, you hire a CM in China and they'll do the development process for you for a fee. You actually don't even need to be good at development anymore. Like, we have entire countries that are good at it. It's great, right? But it's like people are not good at the research process still. That's the rare thing. And what the research process is is this broad and shallow. Let's go reduce the time to try. So we hit a huge range of outcomes, get a very high rate of learning so that we burn through this very quickly, and then go find things that really stick, that really work. Now this actually, this is a slightly philosophical point, but this is the way that humanity has built through most of civilization. This is actually the way that nature builds. Nature says, let's try lots of variations, not all of them live. And actually, in a short amount of time, I'm going to go create a massively diverse and beautiful world through just trying a ton of variations and never stopping. So nature is incredibly good at this. We're newer to the game. This is what we're kind of good at. But we're learning to do this, and we're learning a lot from nature about how to do this. But these are the two phases to keep in mind. And when you're at your work, you want to ask yourself, are we in development or are we in research? If you're doing something innovative, then you're definitely in research because you don't know how it's going to turn out. There's still possibilities, there's still places to go look at. If you've done this thing a thousand times, you're going to do it a thousand and one times. You're probably in development, right? Because it's like Oh, I already know how to do this. It's just like the previous thousand times. I'm going to do it one more time. And that's about efficiency. Make yourself really, really good at a thing you're going to do a thousand times in a row. Research is about broad and shallow. Go hit everything. It doesn't look efficient. You're throwing away 95% of your prototypes. Minimum. Right. Efficiency is not the game. Rate of learning is the game. But be really clear in your head about which side of that line you are in, and you'll know whether you need to be optimizing for learning or whether you need to optimize for efficiency. All right, last slide, and then we're going to take some Q and A. So this is a slide which is a little bit more like, you know, big picture slide. It's from a children's book that my wife and I worked on. And basically it's a reflection on why do we do all this stuff? Because I've worked with lots of teams to teach them these skills and practice, and when they actually adopt these practices, I've seen teams speed up by a factor of 10, speed up by a factor of 100. It's a lot. Now, what happens when you do that, when you start solving your problems 10 times faster or 100 times faster? Is actually the nature of your relationship to problems change? Because when most of the time we wake up in the morning and we think to ourselves, one of the main things on our minds is, here are my problems. Can I solve my problems today? Can I solve my problems today? So, like, most of your mind is occupied with the question, can I solve my problems? At the point that you have a way of solving problems which is 10 times faster, 100 times faster, you start solving enough problems that that actually doesn't become the interesting question anymore. You've solved enough question problems where it's like, well, we did it last week and the week after that and the week after that. So solving problems is not the hard thing. The harder question to ask yourself, and one that might take much longer to work through, is what problems in the world are worth solving? And this is a thing that has led me from working on breakthrough hardware at Google, to working on problems in the developing world, to working on things like global climate. Because with each revision, I was like, no, there is yet a harder level of problem, a more important level of problem to chase after. Let's do it. Let's bring these skills to that. And each one of you guys, to the extent that you adopt these practices, you will go on your own journey of, you know, solving the problems itself is not hard anymore. It's like, what problems are worth solving in my life? What is my life for in terms of what it is meant to be here, to serve, to solve. All right, with that, thanks very much. This is my team on day one. This is my week. This is my desk after two weeks. And if you need to contact me, like for corporate consulting, and I also have an online course, it's all good. Thank you. I'll take some questions. Yes. Okay. Nice. Where's that microphone go? Well, there's actually nobody raising their hand, so it all works out. Okay. This guy. Wait, hand. He's coming. Two more seconds. Yes. Really loved the theory you shared. Can you run through with us, like, an example? I would like to know your thought process on how you minimize the time of learning. Perhaps an example of how you think about minimizing the time and how you move from that. So just tell me something specific you want to do right now. Give me the hardest one you can imagine or just, well, give me something that's real to you. Don't make up something you wouldn't care about. Okay. If you want to solve poverty, for example. Solve poverty. So this is a classic example. If you go and pick something that is super, super vague, then actually the problem with vague things is you can never make progress on them because you don't exactly know what progress is. Right. That one thing that I didn't share but is an important aspect of innovation is specificity is the friend of innovation, because the more specific you get, then the faster you can actually find out whether something is going to work or not. When I told you some of the numbers about climate change, was, I like saying vaguely speaking, there's some problems. No, I'm like 10 gigatons. And let me explain to you exactly what that is, and then let me talk to you about some of the approaches and how much they affect the number of gigatons. That's incredibly specific. If I kept it super vague, let's solve climate change somehow, we would literally get nowhere. I mean, we could complain about it for years and literally get nowhere. What's way better? And this is the thing that's very hard for people to do is to get prematurely specific, because people feel like as soon as I get specific, I might be wrong, and then it's going to be a problem. It's like, no, screw that. Actually, you're going to be wrong 95% of the time period. So Just get used to that. That's totally fine. What's way more dangerous than being wrong is not being specific, because you'll never know whether you're right or wrong when you're not specific. Right. What's way better is like, hey, what if we, you know. Some of my first cuts on how might we attack climate change weren't the drones And I tried a number of things, but when we got specific, I was like, no, this doesn't hit anywhere close to the scale. When you look at this operation plant, it doesn't work. And we prototyped it and we can show that it works at this rate, but that's not fast enough. And actually, I'm experiencing that with coral reefs right now. I've talked with five different teams on different restoration approaches. I have not found one yet that hits the speed and scale, but I couldn't even evaluate that unless we got really, really specific. Oh, this one is about electrified rebar that speeds up coral skeleton. This one is about pouring artificial reefs using a special porosity of concrete. Oh, this one is about, like, these are incredibly specific things that we get to try. And then I can tell you, based on how they're working or not, that, yes, this doesn't hit the scale or not. So you can pick any problem. It can be the biggest problem that you ever heard of, but the way that you solve it is you get crazy specific. You get prematurely specific, and then you're gonna be wrong the first time, and you'll be the wrong. You'll be wrong the first 15 times almost for sure. And then around the 15th, 16th time, you're like, this is starting to work. And around the 20th time, you're like, oh, this is actually awesome. And the 30th time is like, okay, this is how we do it. But it's like we get all spun up in our heads, like, trying to be right in the first trial, second trial, third trial. It's like, I've had this idea for a startup for five years. It's like, I can tell you for sure you're wrong. Then if I ever hear you say that, it's like you've been holding the one for so long, it means you haven't tried anything. You are definitely wrong. And, like, that instinct is the instinct that you need to fight if you're ever going to be innovative. Anybody that's innovative, you never hear them talking about how long they held onto their first idea. That's a horrible way to get anything done. Next question. Okay, yes, I had a question regarding how you decide on. So it ties a bit into the specificity, right? How you decide on what metric during the research process anyways, how do you decide what metric you're going to use to decide which branches to extend and which branches to prune? You almost don't need to because like the kind of dissection of metrics and analyses and driving factors and correlation and causation of different attributes or whatever, that's like a game for later. And why is it a game for later? It's that before you start, you actually don't know what variables are going to be important. So like when you try to go optimize it for that, I'll give you a real example. This is from the developer developing world. So like I was working with a team that was. And their vision was, hey, there's all these child soldiers in Liberia. And like after they grow up, like they don't have any vocation other than to be bandits, right? Because let's say you became a child soldier at 10. Well, now you're 18, it's like, well, you don't have any skills. You spend all your time like murdering people. So like a lot of these folks, like the only vocation that they have is to go rob people on the street as bandits in order to keep living. Now this company had thought of the idea of like, well, why don't we teach these folks to do something useful? And in the particular case they were talking about was, hey, let's go teach them to go grow chocolate beans. And then those chocolate beans, you know, we can sell them on the international market. They get steady income, they'll get learn to scale all these sorts of things. So your first thought on that is like, well, the main problem is going to be like, how are you going to get people to stop being bandits and go grow chocolate? That sounds really hard. Turns out that that's super easy when you actually try to do it. There's all these people that are 18, 20, 22 now, and they have wives and girlfriends and they have kids now and they don't want to be gunned down in the street anymore. And when you're 10, it doesn't matter. And when you're 19 and you have somebody that you care about and a child that you care about, you don't want that anymore. And any way of making money that is not that where you are guaranteed not to die by the end of the day, they're interested. So like a thing that you might think that's really hard. Let's go Measure that turns out to not be hard at all as soon as you try. And like, as soon as we got that, we actually had too many people wanting to be chocolate farmers. And we had the second problem, which is like, how do we procure enough land? Because we were like just going to do this on like a little pilot with five acres and now we actually need to procure 50 acres to go, you know, deal with all the people that want to go do this. So that was actually a harder problem. Like doing the real estate was a harder problem than getting these people to put down the guns. But actually even harder problem after all that was done, and you would not expect this is they were growing and they were producing chocolate. And we got the chocolate to the quality that it could be traded on the international market. And we discovered that, hey, there's certain times of the year where the rains are so hard it washes out all the roads. We have a ton of chocolate and we can't transport it to market. So we started needing to think about how do we outfit vehicles to go deal with washed out roads in the rainy season. That ended up being one of the interesting variables. Now, when I started this discussion, you probably weren't going to pick that as an interesting variable, right? Which vehicles and which tires. But that actually ends up being really important to making this business work. Because when you can't move those beans during those seasons, you lose so much of your grow time, you lose so much of your harvest, the business doesn't work anymore, right? So do not worry about selecting your variables right at the beginning. Literally just start to try to do it. And actually you might find out that some of the things that you thought were hard, like will they put down their guns and decide to be farmers? Ends up being crazy easy. And a bunch of other things that you thought, like you never even thought would come up, like, why am I selecting tires? Right? Like ends up being one of the things that make it so that you have 20% better throughput and sell through on your crop. So now once you've done enough of this stuff, you will learn very fast which variables are interesting. And like, this is the stuff that is going to have you solve the stuff really, really well. Oh, this is a good side thing because most people that come to my talks are pretty smart. And this is the problem with being smart, which is, no, no, you guys will totally get this. A lot of people that were smart actually did pretty well in school. And here's the thing about school. Like every single question in school had an implicit set of assumptions in it that they never told you about. And that implicit assumption in every single question and every single test that you took that you did well on was in the question. There's enough information in the question to answer it. That is true of every question that you answered on every single test. If you couldn't, they couldn't grade it right. So you definitely got trained in this 10,000 times answering these questions. Now, the truth about innovation problems in life is there is never enough information on day one to answer the thing. So your instinct, whenever you jump into new problems, like, let me think about it harder. Because if there is. If the assumption is true that there is enough information to solve it, then thinking about harder is a great strategy because it's somewhere in there. So if I have the equation X plus 5 equals 10, yeah, you just think about it a little bit harder and you figure out what X is. It's no problem. That is the solution form of most of the problems that you're going to go get inside of a test. But the actual problems in innovation look more like X plus Y plus question mark plus question mark plus question mark plus 234 divided by 7 plus question mark equals question mark, question mark, question mark plus 3 solve. Right. Thinking harder about that literally makes you insane. And what people will do instead is like, well, I see a 3 and I see 234, and I see it gets divided by things. So let's think about the things that I can see. But clearly you see how many question marks in there, you're gonna be totally wrong. Totally, totally wrong. So what's way better is like, sure, if you can see a couple numbers that are exposed, a couple variables that are exposed, think about them for 20 seconds and then go do something that makes enough sense based on what you can see, but then get into the doing, because then you'll find out really quickly what the other question marks are. And as the question marks reveal themselves to be, get tires with huge treads, ground clearance needs to be over two feet, stuff that you would not even imagine. Here's how you lease agricultural land. Here's how you prep it for chocolate beans, stuff that were question marks until you tried it. As soon as you actually get the question marks in front of you, you solve it. Really. Once the question marks stop being question marks, you solve it really fast. And I have a phrase that smart people tend to do a 100% optimization on 25% of the variables, right? Because they're staring at the 25% that they can see and they try to optimize the crap out of it and they debate it forever. And the best you can do in that world is 25%. Right. But if you could actually just jump into the doing and you discovered 90% of the variables in a month, then even if you did a terrible optimization, even if you did a 50% optimization, 90% of the variables, you're miles ahead of that team that's still trying to tweak out 100% on 25% of the variables. So I call teams out on this all the time. It's like you are so over optimizing. Not the problem. You have not even seen the full problem yet because you have hardly even tried to do it. And once you do it, you're going to discover the rest of the question marks and you're going to be smacking your head all day that you spent the first three months optimizing that 25% that you could see. All right, one or two more questions. This guy. Okay, one more question. Okay, where is that question? Or it could be zero questions.

Anybody else?

This is. You guys are so easy. Yes. Hand a mic to that guy.

Can you, like, pass the mic?

Oh, it's coming up from here. It's coming very slowly. I taught you guys how to be fast. And I get this.

Sorry, it seemed hard at the beginning, but now we found out the question marks.

Oh, yeah, no, like once. They passed it once or twice slowly. It's like, boom. That's actually pretty indicative of what the process is like. Go ahead.

Yeah. The question is if in a field operation question, if somebody wants to do an innovative thing. Innovative, I don't know, just a startup or a project or any way we want to categorize it, do you prefer or suggest that that person raise money by himself anyway or try to find investors for his idea, for example? You say you prefer I particularly get money from my father to do an innovative thing to fund it or try to do like stuff that. Making me money, for example, doing a website for a person. Just a question. So which one? You say we just find money from someone or we start to rise money from things are not really innovative, but they make money somehow. So what's.

So it really just depends on what you want your career to be like. There are absolutely people where there's not an innovative thing that they've done in their career, but they still do something of service. Right. So it's like, hey, you know, whatever. I'm good at making WordPress sites for people. It's not crazy innovative, but you can make money on that and like you just do that over and over and it's fine. You can can make a whole living off of that. And there's some people that like, that's the thing that they enjoy and that's the life that they want to create and that's fine. The stuff that I teach is really about like if the thing that you're trying to do in your life involves doing something new, trying something new, expanding what a business is capable of, expanding what you are capable of, then that's what that is.

So do you like encouraged to sacrifice the services over innovation over the services? So somebody wants to be innovative must not to do like services. It stops the innovation, is it?

No, it's totally fine. Like look, you can actually make innovative stuff happen in a pretty short amount of time. So I actually have the lived experience of I'll go innovate with a team for a couple days and they need to integrate the stuff that we did together for the next three months because like a lot of stuff got done in that time period. So actually I can go and do a thing for a couple days and they're busy for a while and I'll go work with another team, you know, the following week and then two weeks will go by and I'll do another thing. Like it's not necessary now. Look, if you're strapped for cash and you need to work 60 hours a week to go pay the rent and get food and whatever, then yes, that will absolutely impinge on your innovation time, if that's an important thing to you, in which case you might need to go find a different balance of vocation that's going to give you at least 10 hours a week. I don't think anything serious can happen unless you put at least 10 hours a week to it. Right? But it's like if you can carve out 10 hours a week on a thing, then you can absolutely start anything really. And around funding, it's like, I actually encourage a lot of startup founders bootstrap the first three months, like get your first 20 prototypes built for $1,000, right? And it's like once you get there, you're going to have discovered a lot of the variables. And once you've discovered a lot of the variables, we can talk about how are you going to go enter this market or not. If you got a great plan to that and you know, and you have a plan to go develop it, then you can build something amazing out of that. But don't actually spend that much money on it. Literally test it tomorrow. So, yeah. Thank you. Cool. Thank you.

All right, that'll be all the questions for the evening. So, Tom, any closing words for everybody before we wrap this up?

I think the closing thought is just that I use a lot of these examples to shake up your thinking a little bit. Because the main thing where people get stuck is they've just never seen it happen faster, so they don't believe that it's possible. Now the best possible thing is you just don't hear it from me or somebody else. You know, Jeff Hawkins got great examples. You know, George Campbell has got great examples. You don't just listen to people like us and like, you get with your own hands, you sit down and like in one week you try that business out, right? Because when it happens from your own hands, then you can never take back the feeling that, oh, I can do this. And what I would encourage each one of you guys to do, if you were inspired by this at all, challenge yourself to go make something that you've been waiting to make this week. Challenge yourself to go make it and put it in front of somebody this week. Because that's how you're going to discover the variables. That's how you're going to get onto this path to learning. Or if you're a little more sheepish, go into your regular business and challenge yourself to take your time to try and reduce it by half. You know, that's not that aggressive. Reducing it by 10x is aggressive. Reducing it by half. Actually, most of the time ends up being easy because most of the time at work is wasted on stuff. And you guys know that's all true. But it's fine. Just look at your calendar. It's mostly wasted time. So, yes, that's it.

Everybody give it up for Tom Chi. So if you guys like like that, we encourage you guys to follow what Mindvalley is doing. So just look up mindvalley.com. you'll get to see a lot more videos from Tom Chi as well. He's actually only going to be here today. He's already leaving. He was only here for a day. He just managed to swing by and said, you know what, I'm gonna give a talk for everybody since it's passing by. KL anyway, you're like supposed to be in Johor, right?

I did four things today. That's crazy. Sorry.

So straight from a flight. So come on, guys. I put in all the effort.

Give him one more round of applause.

And I guess you guys can also ask him questions while he's here. And with that, good night. Thank you guys for coming. And check us out at Mindvalley.

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