In the months of August and September 1973, a second crew of astronauts lived and worked aboard the Skylab space station. During that two-month span, these men generated a staggering amount of scientific data, data that in some cases will take several years to analyze, and whose impact the scientific world has yet to fully comprehend. For the record, it was the second manned mission of Skylab. But owing to overwhelming success, it might well be called a scientific harvest. July 28, 1973. Skylab, with well over a thousand Earth revolutions, begins its 75th day in orbit. Except for ground solar observations, its systems have been mostly silent for more than a month. Having been powered down when its first tenants departed. Today, the slumbering space station will again be brought to life when the second crew arrives for an extended stay. Their journey will begin at Kennedy Space Center, Launch Complex 39, embarkation point for most of space history. Transportation for the flight is the two-stage Saturn 1B, which is well along in the pre-dawn countdown. In nearby launch control, the vigil is centered in firing room 3. Here, the staccato of digital readouts tells the launch team that all systems are go. The countdown is smooth, almost routine. For the crew, the lectures, the briefings, the simulations, almost two years of intensive training is behind them. Today, they begin the real thing. Navy Captain Alan Bean, senior member of the crew, is Skylab commander. In November 1969, as lunar module pilot of Apollo 12, he walked on the moon. The science astronaut and civilian member is Owen Garriott. He brings to this mission a well-rounded background in science and engineering. The pilot, Marine Corps Major Jack Lausma, who served on support crews for three Apollo missions. For the three of them, the longest space flight ever is about to unfold. For liftoff, right at the T-zero mark, we pass the 15-second mark in the count. T minus 10, 9, 8, 7. We have ignition sequence start. All ignition, all ignitions are running. All engines running. We have a liftoff. Never been a smoother launched sequence. rendezvous occur just off the U.S. Pacific Coast, almost eight hours following liftoff. Oxidizer leak in one of the quad thrusters was the only blemish on an otherwise perfect flight. The leak would mean a slight loss in attitude control on the return flight. But at this point, it appeared to be well within backup control capabilities. Leaving the detailed analysis to ground specialists, the crew wasted no time moving into their temporary home. Within an hour, they had begun restoring Skylab to a living working environment. Activation consumed the better part of the first week, because not everything went according to plan. Because of built-in mission flexibility, the delay had little impact on overall scientific gain. The flight plan was adjusted as required while the crew continued to make headway. The solar astronomy instruments were, meanwhile, delivering data in the unmanned mode. Medical experiments got underway. And some of the corollary science and student experiments were initiated. For example, these minch-mog minnows, being set up for observation, appeared to lose orientation in zero G. Another passenger from Earth was Arabella the spider. This was a student experiment designed to find out the structure of the web she would spin in the weightless state. On mission day six, a second quad thruster indicated failure. Even so, command module control was still adequate for the return flight. However, the uncertainty of additional failure prompted an urgent decision. Hey, uh, how was it, Chris Kraft? It's aced so that we would have a rescue vehicle available to us should that become necessary. Okay, now, I guess, and I'd like to say that further that we're proceeding here with We can call us in any way if you want to. So as a precaution, rescue plans were set in motion. Whether they would be carried out completely depended on assessment of the thruster problem, a problem that could now be fully explored. As the mission entered the second week, the crew stepped up the medical protocol, somewhat slighted up to now because of more pressing needs. We also have a way to measure our heart rate. If this reads out our heart rate, it beats per minute as we're pedaling. Of course, the harder you peddle, the harder your heart has to work, and the better it is for your cardiovascular heart system. While we're pedaling this bicycle during the medical experiment, our breath is analyzed in this metabolic analyzer so that our pulmonary system can be thoroughly evaluated during the period that we're up here. This is used in combination primarily with the lower body negative pressure experiment. The man slides in from the top here. The purpose of the rotating chair is to determine the response of the vesticular system to zero gravity. We've been doing many experiments on this to see how the balance mechanism in the inner ear is affected by weightlessness. Other medical data was compiled from an accurate recording of the daily food and fluid intake. Body waste and food residue were weighed daily, and the wastes were either dried or frozen for return to earth for analysis. The weight of each crewman was also checked daily, not by conventional scales, but by a device that electronically counts time of oscillations of the subject to determine mass, and blood samples were taken. The samples were frozen and later returned for post-flight analysis. The earth resources package was enabled. It's six remote sensing systems put into full operation. Look at earth and its resources. We want to look at its forestry and its agriculture, its freshwater resources, its weather, its pollution, and the number of other resources that do us on the earth. This is called our earth resources experiment package. Consist of about the six experiments with which we look at the earth, and we spend a lot of time taking data here. This particular instrument is a telescope, and we can see a resolution down to a quarter of a mile square. For example, we can see a city block with this telescope. Another battery of experiments also that are associated with earth resources, and they are these cameras that take actual photographs and different wavelengths of light, and then these photographs will then are returned to ground and processed and evaluated. And the purpose of course is to learn how to use our resources on earth more efficiently and more effectively. Hand-held cameras were also unstowed. Their lenses aimed at earth through the ward room window. This was the first of three scheduled EVAs. The amount of work to be performed would make it the longest. Erecting a new sunshade over the workshop was their most difficult task. The parasol, deployed from inside by the first crew, had done an adequate job of thermal protection, but temperatures were still high in places, and to the life of the parasol was questionable. The sunshade would even out workshop temperatures, and it would endure well beyond the final mission. The EVA consumed about double the time allotted, but all tasks were successfully performed. The total time outside the workshop was six and a half hours, a new record for orbital EVA. Temperatures began to fall before the day ended. They eventually stabilized at around 75 degrees, providing the best environment in the workshop since it was launched. The following day, the Apollo telescope mount was put into manned operation, allowing quick and accurate pointing of the telescope array at current solar phenomena. At sunspots, we can see network, we can see filaments, all of these things on the sun, in great detail. Now, this coronagrad visible part of the wavelength, which makes it something that cannot be observed very often from the ground. And this is, it has some occulting discs that are in front of the telescope, so that the center of the image, the disc of the sun, is blotted out, and all we see is the very faint light coming in from the solar corona. Those of us on the ground can only see this at those very infrequent intervals when we have a total eclipse of the sun. Now, up here, we're essentially looking at a total solar eclipse all day long, and we monitor the changes that occur in the corona, and once we tie all of our preparations together here in Skylab, we will monitor the changes that occur in the solar corona over a period of over five months. And some of the changes, solar corona, it stretched the magnetic field like that, like rubber bands, and finally burst the rubber bands, and the gas continued far on out into the corona, and eventually reached the environment of the Earth. Now, when these gas bubbles do reach the environment of the Earth, they cause some very interesting things which we can see, or you can see that they are produced at the magnetic field disturbances, and when they arrive and perturb the Earth's magnetic field, in some way, I fully understood. Dr. Garriott went on to explain instruments that record in the extreme ultraviolet. And instruments that provide data in the X-ray wavelengths. And he talked about that interesting phenomena we call solar flares. Had to get a portion to see several of these since we've been up here in the last four weeks. And when these events occur, we very quickly go over and train all of our instruments on those flares. He photographs as rapidly as possible in as many wavelengths as possible. And we hope to better understand what produces these flares, what is the size of the flare. Better understand the mechanism by which these things are produced. Skylab telescopes also reached out beyond our sun to record the ultraviolet spectra of distant star fields. Early type stars, too faint to be seen with an naked eye, were photographed. As were the abundance of young hot stars in the Milky Way. In conjunction with this experiment were two student investigations designed to obtain ultraviolet spectral data from known pulsars and quasars. In related stellar studies, other instruments were activated to provide a panoramic view and measure ultraviolet brightness of a large number of stars. In evaluating the requirements for future manned space flights, high priority is placed on a machine that will allow an astronaut to move freely in space. Such a machine is the astronaut maneuvering unit. Here, being flight tested by Alan Bean. Need to fly, as you know, I believe this is me flying in here and Jack flew it. And we wanted to ask Owen to fly it since he had gone through none of the training. And he got in there and flew it just as well as either of us with the minimal training and just the on-the-job training up there. Kind of gave you a feeling that this sort of a maneuvering unit could be built where pre-flight training would be minimized and yet you could still do the job you wanted to do outside. A foot-controlled maneuvering unit was later tested. But in its present configuration, it got rather low marks in performance. The future design that will shuttle astronaut between spacecraft or from spacecraft to satellite will likely be similar to the hand-operated model. In web building, Arabella was getting a handle on 0G. The adult minnows, meanwhile, were still confused about which way was up or down. But strangely enough, their children, recently hatched aboard Skylab, came into the world without ever having to adapt to 0G. Will body motions of crewmen affect attitude and control of a space vehicle? This question was put to the test in a series of crew vehicle disturbance runs. A force-measuring system, which senses loads applied to the workshop, is matched with concurrent control system data to find the answers. The tests will clear up many uncertainties about crew motion effects and will influence the design of spacecraft of tomorrow. The subject of attitude and control became a more immediate concern during the second scheduled EVA. Skylab's rate gyro system, which instructs the computer as to the amount of attitude drift, had a faulty gyro package. Jack Lausma would install a new one. The package was installed and placed online. Within minutes, the results were in. The EVA lasted four and a half hours. All tasks were successfully performed. Early next day, the crew set a record for the longest manned space flight. They had already traveled 11 and a half million miles. What's more, productivity was at an all-time high. They were now running well ahead of schedule and even requesting jobs to increase the daily workload. One such task was the behavior of bubbles in 0G. The oscillations are much less damp. It exhibits almost all of the pre-modes of oscillation that you would expect for more liquid like that. You will spin up those oscillations again by just blowing an air jet. There were also demonstrations of angular momentum, magnetic effects, a wielder force pendulum. There was even an attempt to find out about the aerodynamics of a paper airplane without gravity. It's welding good. That doesn't look like a welding good. We have a land that we can grow perfectly out of. Presents of gravity and we're examining that. While most of the time was devoted to experimentation, a part of the astronauts' day was spent on the more mundane aspects of living. There were meals to prepare, cleaning, taking out the garbage, equipment repairs, personal hygiene, and always the exercise. Although a few hours away from the routine was rare, it usually found expression in the novelty of 0G. By mid-September, it became apparent that the rescue mission would not be flown. Analysis had shown that command module alternate control modes were more than adequate for the orbit, and the condition had remained stable. In addition, contingency plans were defined for the defective quad thrusters in the unlikely event they would be required. It looked like a nominal mission all the way. Skylab cameras, meanwhile, maintained a steady flow of pictorial data, such as Earth's horizon air glow. These photos will tell scientists about the behavior of ozone, and its importance to the thermal balance of the atmosphere. For the science of meteorology, strong weather systems were closely documented. As were these very striking wind convection patterns, volcanoes, they were photographed around the world to perhaps form a basis for predicting volcanic activity. The Alps, the Straits of Magellan, Italy, Gibraltar, Washington Baltimore, the Grand Canyon, Cape Cod, the Drought Area of Africa. From handheld and Earth resources cameras, our planet was photographically documented as never before. Number 25th, Mission Day 60. And for this mission, time had about expired. Recovery would be off Southern California by the USS New Orleans. The scientific journey had ends, gravitational pull. One where your legs feel strong enough, and it doesn't feel like it's too heavy to move your body, but I think your lateral balance is sort of funny. We didn't seem to have much problem with wanting to pitch forward or backwards. It was mostly the sideways correction. It would take a couple of days for the crew to regain their steadiness, a normal part of the readaptive process. Many hours of medical tests would follow in which all data would be within normal limits. Long-term medical effects would take several weeks to analyze, but for now, they felt well. Their spirits were high, and they looked forward to home and family. I didn't know we had so many friends. I'm glad to see y'all here today. Reunion took place at Houston's Ellington Air Force Base amid welcome home ceremonies, just as they will for many months to come. The crew attempted to share some of their experiences, experiences out of which a store of knowledge was gleaned that will shed new light on our troubled planet, and experiences that have served as a proving ground for the next Skylab mission and for our future course in space. He's in space right now. He's in space to stay. He will always be in space in the future. The business we're in at the moment right now is trying to develop the abilities to carry out these explorations and advancements that are sure to come. It may not be five years from now or 10 or 15, but if we could all return to the Earth a thousand years from now, we'd find that there are many people here, but there are people that have gone from this Earth to the other planets of the Solar System and perhaps even the other stars. He's embarked on a most fantastic journey and it will never end.


Earlier this year, I talked about the baby formula crisis in the United States. We did a show on that, Scott Linsecombe, who is one of my favorite commentators on economic policy these days. He's excellent. If you don't follow Scott Linsecombe, L-I-N-C-I-C-O-M-E, on Twitter, you should. He is excellent. Glenn, thank you for the $100. Really, really appreciate it. See, that's how we're going to get on these shows, the 250, is if people jump in with that kind of support. I really appreciate that. Scott has been on top of this baby formula story from its beginning. There was a massive shortage in baby formula in the late spring and in the summer. I mean, parents were frantic. Parents were desperate. 75% of babies in the United States depend, to some extent, on the availability of a baby formula. And there was a real shortage for a variety of reasons, which I covered before, a closing by the FDA of a particular plant, but more deeply, a complete distortion of the market in the United States of baby formula because of the way welfare is allocated, welfare to poor mothers, who that money is used to buy baby formula and how they allocate that and how they subsidize it, basically, government involvement in this market, completely distorted the market, and it helped create very few suppliers domestically. And when they shut down the Abbott plant, there was a significant shortage. But also, the shortage is caused by the fact that we don't import baby formula. For example, Europe is a massive manufacturer of baby formula. And what's interesting is Europe has very stringent food safety regulations. Why don't we just accept the FDA equivalent in Europe as a good standard and just import all the baby formula Europe can produce? The shortage would have been gone if we had done that. It took the FDA a long time to allow for more baby formula to enter into the country from Europe. Ultimately, the U.S. lowered tariffs on baby formula earlier in the year, so we have tariffs on baby formula. Who knew? You see how these things and that, of course, restricts importation, but also the FDA doesn't approve a lot of the companies and they have to go through an approval process. Why when food in Europe is just as healthy if not healthier than in the U.S.? So why doesn't the FDA just say, if you get approved in Europe, you're okay in the United States as well. And vice versa, if the FDA approved something, the Europeans should say, sure, it's approved here as well. They should do that with drugs and they should do that with food. Anyway, in spite of the fact that they opened up, in spite of the fact that the FDA allowed some formula to come in from Europe, in spite of the fact that tariffs were lowered, 25% tariffs on baby formula. Why? To protect American manufacturers, to protect the welfare system, basically. I mean, again, I'm not going to go through the whole story that I went through in the baby formula story I did earlier this year. Anyway, there's still a baby formula shortage. It's not as bad as it was. It's a lot less, but there's still shortages in significant parts of the country. And Congress suspended the tariffs earlier in the year in order to reduce the impact. The Abbott plant in Michigan has been reopened, but there's still a shortage. And tariffs, I expect that to snap back in January 2023. I love, tariffs is like the dumbest tax of all. Why are we taxing baby formula? I mean, is it because we have a trade deficit with Europe? Anyway, let's hope, hope, hope is all we have. Let's hope that people like Scott Lindsicom and others who put pressure on Congress to try to get rid of these, maybe, maybe even permanently, permanently eliminate tariffs on baby formula coming in from anywhere in the world. And, you know, let's get real pressure on the FDA to allow the importation of baby formula from Europe without the FDA having to give its own additional stamp of approval. Same should be with Canada. There's certain countries that even at the current regulatory structure, we can make things a lot easier to import stuff by just accepting kind of each other's regulatory regimes. Now, I'd like to see the regulatory regimes eliminated completely and privatized and for private certification to arise and for baby formula and everything else. But short of that, we've got an FDA, it's not going away. Let's at least do some rational steps to make it function better. Thank you for listening or watching the Iran Book Show. If you'd like to support the show, we make it as easy as possible for you to trade with me. You get value from listening. You get value from watching. Show your appreciation. You can do that by going to iranbrookshow.com slash support by going to Patreon, subscribe star locals and just making a appropriate contribution on any one of those, any one of those channels. So if you'd like to see the Iran Book Show grow, please consider sharing our content and of course, subscribe. Press that little bell button right down there on YouTube so that you get an announcement when we go live. And for those of you who are already subscribers and those of you who are already supporters of the show, thank you. I very much appreciate it.


I found in my life, when I started to just put spirit first in everything and I really started to just deeply pray and listen, okay, what would you have me do? Where would you have me go? And I would get these strong guidances and prompts and then when I would follow them, I would have such glorious, expansive experiences, like expansive joy. Follow the next prompt. Another expansive joy experience. Follow the next prompt. And whoa, another expansive experience that pretty soon I started associating following my guidance with the happiness and expansiveness. I wanted to go into a place where my guidance would lead to an expansion of my mind, my awareness, and that would be the proof. That would be all the proof I needed was that expansive, glorious state of mind.


Thanks very much. Great pleasure to be here today. So first of all, I want to say, the future is better than most of us think. And the interesting part, when you're looking at, for example, watching movies from Hollywood, X machine, especially always a robot warfare against the world, that's the biggest topic, and terrorism, and all of the lovely stuff. But when you look around you, actually, there's a lot of hopeful things happen in the world. For example, childbirth rate has dramatically declined. Poverty has declined, even though it doesn't look like it. There's lots and lots of good things happening. Technology is now solving major problems. And of course, technology is also creating major problems. But if you're looking at what's happening, for example, in climate change and solar energy, all of a sudden the oil industry is on its way to what they call a transition plan. It will cost them roughly $6.4 trillion to make that transition. But we'll see what happens there. And for example, solving cancer, diseases, gene editing, right? Gene gnome editing, it looks like a science fiction. But what you see around yourself today is a lot of science fiction is becoming science fact. Think about, for example, automated language translation. There's now four or five apps, including Microsoft Translator, SayHi, Skype, that allow you to have a real-time conversation in 34 languages. That's like Star Trek, right? So three months ago, I was in Japan. I had a half-hour conversation with the sushi chef. I spoke German, not Swiss German, just regular German. I don't speak Swiss German. I just live there. But anyway, we would talk for half an hour. And we didn't talk about really intimate stuff, of course. But food, right? Simple. And things like the self-driving car. I drove the other day. I mean, a friend of mine has a Tesla. We went on the highway, not on the Autobahn, but American highway. We drove for three hours without touching the wheel, eating, having a conversation. You can't turn around the seat and you have to be near the wheel. It drives itself. And think about what that means in five years. Toyota has announced now that by 2035, they will stop making cars with gas engines. I mean, that is science fiction. I mean, the possibilities of technology are mind-boggling. So I contributed to a book that you were, that's your surprise. I'm giving away the surprise. This is a book that's also very good for self-defense. You know, if you, I'm not the publisher. But I told the publisher not to print the book, right? Because anyway, 62 Futureists writing about the future of business. So if you read this book, I guarantee you'll never sleep again. It's a definitely good read. Give it a couple hours. And I wrote one chapter called The Relationship of Man Machine that you can also download for free on my website. But it's definitely a great book to read. You'll get a copy each later. So first of all, what do I do? A futureist, my work is not prediction. There's no such thing. As you know, predictions are kind of mission impossible. There are some people who have done it really well. Big futureist, Alvin Toffler. I like Asimov. Einstein type people. I don't, unfortunately, I can't expire on that level. So I work on insights. And insights are really what you do when you listen. In China, they say, if you want to know about the future, ask your children. And it's so important because children don't have to produce money, right? They don't have a job. So a good thing to be ready for the future is you should spend between three, five, sometimes 10% of your time to looking at what might be rather than what is. And this is a very tough exercise. But I'll show you why that's really important in a minute, because this curve is the most powerful curve we have around us today is exponential technological change. Now what that means is that when we count linear 1, 2, 3, 4, 5, we get to 5. We count five times exponential. We get to 64, 7 times to 128, 30 times to a billion. Technology, as you know, is doubling in power and halving and cost every 18 and 24 months called Moore's Law. So you basically have all these things happening around us like data. The exponential amount of data is just absolutely mind boggling. And many people have said before, data is the new oil. In fact, now the companies that deal with data, Google, Amazon, and of course Facebook and all those usual companies, I call them the data oil companies, they make more money than the oil industry. Last year, they made $7.1 trillion selling data, data mining, more than the oil companies did. That's why they're so powerful. So then we have other things like the man-machine convergence. Things that we used to do are now done by machines. Resturant recommendations, automatic email replies, devices you can talk to. Gmail, Google has an app that replies, uses your email to send automatic replies using artificial intelligence. That's a very big trend. And the other one, of course, security. You're very familiar with this topic, I'm sure. There's lots of predictions saying in 10 years, 80% of the entire military budgets will be spent on cybersecurity, cloud, digital security, cyber warfare, terrorism. All 80%, right? So you can simulate a battle. I didn't say, you won, I lost, without actually having a battle. I mean, these things are becoming really, really powerful scenarios. The number one primary problem is that because we're all connecting at very high speed now, and the internet of things is connecting our cars, our houses, our wristwatches. So the amount of data goes up exponentially. We have to make sure that this environment is secure and safe. And of course, partly regulated, right? We have to have a social contract, what is okay and what's not. There are many things that come with this. So exponential technology is the first thing we have to consider. So what you think today is impossible, is probably not impossible, we'll just take longer. Digital money. How long have we talked about digital money? 15 years. Finally, it's looking like it's gonna happen just like solar energy and electric self-driving cars. Well, take longer, yes. But digital money is inevitable. It's just exponential curve of technology that will make it happen. And part of that curve is that humanity is gonna change more in the next 20 years than the previous 300. And I mean this quite literally.  They'll never read a book that's printed. They won't have a driver's license. They will never know a bank that's in a building. Well, some of them maybe. Maybe we're talking about the world changing at mind-boggling pace. And so a lot of these things are quite positive because for example, prices get to be lower when they're more efficient. Like take the music business, I used to be in the music business as a producer and musician. And now the price of music has gone down from about 20 euros per CD, that's 12 songs. Now you have Spotify or YouTube is free. Spotify is eight euros for 18 million songs. Imagine that would happen to banking, right? This kind of margin reduction. Not good. But that's gonna happen to banking, not all of it. But for example, transactions, right? Technology makes transactions essentially not free but very close to free. Music is essentially free now. I mean, eight euros for 18 million songs makes it basically free. Netflix, same thing. Kindle, prices dropping. So technology is really moving at mind-boggling pace. And there's a great book on Hemingway where he talks about how do people change and how do they encounter problems. And he says, well, basically what happens is it's very gradual and then very suddenly. So I'll give you some examples in robotics. If you have this thing called the lipstick robot. It's not very good, right? This is actually very hard to do, right? Then you have robots that are trying to walk. This is the DARPA video, the defense video, right? For years, the robots couldn't walk. It's very hard to walk for a robot or to understand language, right? Same thing, right? It goes on forever, just all failure, right? Now, three months ago, Boston Dynamics, a company owned by Google at this point. I don't think they will divest of it soon. This robot can walk like a person. You can kick him. He gets back up, right? And you feel pity for them. This is like a human, right? And this robot, first I was going to say, her or it, whatever you want to call it, right? They understand language almost fluently. This happened just three months ago. And then right after that, the hardest game in the world, the Chinese game Go, has more combinations than there's atoms in the universe, which means a lot, right? The human champion of Go got defeated by a machine that Google had built, right? Called DeepMind. This happened 15 years before you thought you could. And the key was that this machine, sorry, I'm not going to give away this slide too early here. Sorry about that. This machine essentially has learned how to play Go. It wasn't programmed. This is the important part, right? So the computer wasn't programmed to play chess or play Go. It observed forever. And then it played a million rounds against itself, another 100,000 against others. And after a while, it figured out what the deal was, how you would win. And it actually won the games by doing things that humans don't do. Now imagine you would apply that to bank transactions. That is going to happen. This giant global brain looks at 100 million transactions a day, as many as you can feed it. And then it devises the rules of how you could change it and make it more efficient. That's what IBM Watson is trying to do. I'll show you some examples. So let's go to another example. I'll skip the other ones. You've seen those already. Here's the important point, what happens here, right? If you look at the Tesla example here, Tesla is selling more cars in Western countries, US numbers right now, than any other luxury car company. And now it has actually pre-ordered something like 380,000 cars that don't even exist yet. And nobody knows if they're ever going to exist, really. I mean, I keep my BMW for now. But Tesla is wildly successful doing something completely different. This car is software on wheels, right? It's not actually a car. It's software and mobility. That's how Tesla has changed the game, right? So look at this graph. We have to expect exponential growth surprise factors. And banking and financial transactions, the hard stuff behind the scenes, that will change exponentially in the next five to 10 years. Based on technology, but also based on user behavior. And some of that you will discuss later, I'm sure, is about the blockchain and using technology to make it more efficient. So in this world of transactions of highly computable numbers, there's a couple disruption factors that my friend Rachel Boltzmann has outlined. First, you can be disrupted if you have complex experiences. That is certainly the case with you. Do we have broken trust? Will you be the judge of that? I think some banks do have broken trust, including my own in Switzerland. Won't cover on that. Redundant intermediaries, absolutely. Do we have intermediaries that are redundant? Well, part of the discussion I'll have later. Limited access, limited information, ripe for disruption. So when you're looking in this direction, there's some stats from Accenture saying that 72% of millennials, kids are around 30 now. There's 72% are likely to bank with a non-financial services company, and 81% of Indians and Brazilians are ready to buy a car from a tech company, from non-traditional car buyer. That's how the relationships are changing because of technology. So my son, who is a young son, is 22. When he moved out, he had to get a bank account. He didn't get a bank account. He went and downloaded an app to his mobile, and that's the bank.  I'm using credit service. I mean, how old-fashioned can you get?  Remember, it used to be good enough that you can buy a DVD of a Hollywood movie, and you watch that. And it was region-encoded. You could not take it to Hong Kong or whatever. That's over. Now it's what, Netflix, Hulu, YouTube, everything on demand, much cheaper, much better. So if you're selling DVDs now, you're just not good enough. And that's happening all across all sectors now. The pharma business. Very soon people say, well, not taking a pill is just not good enough. I want to do some things so I can improve myself without having to take the pill, go beyond the pill. We're talking about a roughly $7 trillion business here as well, revolutionizing how that works. So basically what we're seeing here is, first, it's consumers, and then it's businesses. In fact, now the distance between B2B and B2C is shrinking. When you go online here to look at your Facebook page and send an update or do a tweet or go to LinkedIn, when you go home, you're going to expect the same thing from your service provider, from your bank, from your insurance company, the same level of service. The most brutal part of this is not us that are the problem because we're used to that. It's the millennials that are going to be 75% of the workforce in 10 years. And they'll be the new CEOs. And they will not bank with you or work with you or do whatever with you if you are 10 years behind that curve. Wealth management, for example. Do you really think a 30-year-old guy that has $20 million somewhere in Asia is going to stick with the same kind of wealth management that his father has not going to help? So big change is coming up there. One of that changes is we're going from products to services to experiences. This is a key thing for financial transactions. It's not enough just to have a great product, provide a great service, provide security. It also has to feel great. Has to be an experience. Lots of examples like Tesla, again, when you drive to Tesla, it's an experience. Not just because the way it drives, but you can talk to it. You can say, please order a cappuccino. We'll find a place to do that. I mean, it's mind-boggling the experience you have there as compared to other cars. Experience, for example, is behind this phone in Switzerland called the Black Phone that you may know. It's the world's only secure phone system that you can buy, basically encrypting from A to Z. And they're completely sold out. The number one primary reason is they're using an Android system that's completely set up to be secure in any possible way. Lots of bankers are using this now, by the way. So it's a really interesting experience shift that we see there. I think most companies will shift to provide experiences. And financial, of course, should be such an experience. I mean, when you put your Tesla in the garage and you plug it up to the Wi-Fi, overnight it downloads a software update, and boom, next morning, you have a new car. Literally a new car. You get the autopilot in an update. You don't have to go in some garage somewhere and spend 500 euros getting a software update or a DVD, as we know from some of the brands. I mean, it's basically completely a different lifestyle, different experience. The other thing that you're going to see, I think, for a natural industry, I think you're quite aware of this, right? We're going to have huge food chain conflicts. So all of a sudden, what you do, for example, in transactions and what maybe Swift does and what other companies do, you have business models evolving that say, oh, yeah, all of a sudden, we're closer to you than we used to be, or we're moving to something that we used to do. Like, for example, social networks are getting into banking. And Google gets into everything, like literally everything, including health. There's a Google project that wants to end dying. That's a minor mission. We'll probably take them 18 months or so. But it's about two things, right? The future is about hypercollaboration, especially with those that you compete with. Because the outside guys are coming from the technology sector. They don't compete, they just eradicate. Do you know how many rooms Airbnb, the company that rents rooms like eBay, they're adding 45,000 rooms a week. They're the biggest hotel company in the world while kind of accommodation, whatever I want to call it, right? They don't own any hotels, any property, any real estate. They own a database. So think about something similar for financial transactions. You know, I was in the music business for a long time, and it makes a great example of how to not transform.  But basically, the music industry said in the late 90s said, oh, this is really bad. People are getting music for free. And if they do that, then we don't have a business. Well, it turns out people want music cheaper. They want it in the cloud. They want it at their command. They're not willing to go back. If you buy a CD today, I don't know if you buy any CDs today, but don't show your kids. Because they'll call a therapist if you buy a CD. It's over, right? The red line is the CD sales, right? I mean, I have a good collection of vinyl. I love vinyl stuff. But I'm not 15. But if you look no longer, if you look at this slide here, the key message here is the following. The music business will recover. It will make money, but it won't be the old guys making it. The new music industry is YouTube, Baidu, Facebook, Spotify, the tech companies. And the music guys, Emi, Sony, Bertelsmann that I used to work with, they've lost 71% of revenues in 10 years. I mean, that's an accomplishment. You have to try hard for that. Don't let that happen to you. They lost their runway. Their runway ended in 1999 when they didn't realize what people wanted. Or they realized, but they said, not with us. We have different plans. So the disruption of traditional gatekeepers happening everywhere is happening in these waves. And basically, music industry now has displaced, diminished, disintermediated, and done. If you're a musician today, you will not sign up with Sony Music. You go to YouTube. You still need Sony Music for other things, like catalog, copyright. But still. So these waves of disruption are happening all around us. And here's the key learning from this. Whatever you see happening in other industries is flowing down the line in this order. Information, music, media, films, transportation, Uber, and so on. And you're here. You're next in that wave. The good thing is, it's not too late. Unlike the music business, it's completely gone now. You cannot sell music. I mean, music cannot be sold. It can be provided, some sort. So this disruption now, if we can learn from the other guys from the film business, it has made a very good adoption from the book business, which is now digital. Amazon sells three times as many books on the Kindle as it does in print. And Amazon is now the biggest publisher in the world as well. So what we can learn from here, this is a big opportunity. The future belongs to those who can hear it coming. That's what David Bowie said. And he heard it coming. He was a very feature-focused man. So when you're looking at this, you can say, well, really what's happening here is that the playing field is tilted, right? It's completely tilted because the technology companies, they are liquid, they are fast, they're agile, they have money to burn like you would not believe. They're highly unregulated. Unlike the oil companies, the data oil companies can do whatever they want until just now, Google versus the European Commission. So this is all happening now. Basically, this is what I call the unification of everything. If you're looking for disruption, look no further than Silicon Valley and China. Financial is the next wave. I looked up yesterday how many companies are funded to disrupt the financial services business all the way from the back end to the front end and all the steps in between. Take a wild guess. Funded above $5 million, $3,247 companies. And yes, many of them won't survive, obviously. But this is coming in a really quick way. So I think there's a Tesla moment for the financial services business on the back end and the front end. It will take much longer on the back end to be clear because it's very intricate, highly regulated. Obviously not easy to do. So a little bit safer there, in many ways. But of course, the changes on the front also make changes in the back. So think about that. If the German car companies had said six years ago, and we happen to give a workshop to one of those companies, I just say Dieselgate. And you know which one. Six years ago, we said the biggest trends are kids are not getting licenses. They're sharing cars. They want to drive electrically. They want to share. They want to have autonomous driving. We got laughter. That was six years ago. Today, number one initiative, electric autonomous vehicles. Now you have a few years to discover that. Think it's a very good time to discover what the Tesla moment would be. Because as Marshall McLuhan says, a famous futurist said, it is the framework that changes with each technology, not the picture. Remember years ago, we talked about social media? Remember that? What a great headline or big data, one of those artificial intelligence same kind of headline. It's not about those pictures. It's about the whole framework. The way that we do business, who we talk to, how we innovate, that's the framework. So here's a framework for you. There's a lot of stuff here so you can download most of that later. But basically what's happening here is that we have 10 what I call Asians. And you can guess why they're called Asians. They all end with Asian. At least there's actually about 20. But I'm sorry for the rest. This is kind of the roadmap to the future. And basically, you know all this world. Mobilization, for example. 80% of all internet traffic in four years is going to be mobile, not desktop, not computing. And you do it with your voice. It's voice-controlled. Computing moves in the background, and you just say, computer. Get me the latest stock report. Shift those shares. Get this banker off my email list. Whatever. It'll do all those things. 90% of that is really good. We're really excited. And there's another one that's not so good, like disintermediation. Right now, we're at the point where most technologies are extremely hopeful if we only understood them. If we don't let the other companies that come from technology come into the backdoor, like Airbnb came into the backdoor. And now, if you're in New York City hotel, 28% of your bookings go to Airbnb.  It's like, that's the backdoor. So you have to look at those trends. These are all interfacing. The interesting part is that they're not just individual trends. They're also overlapping. For example, if you have lots of data in your system called big data, can you use that data to derive decisions? Well, yes, only if you have intelligence. If you have software that discovers the data for you. If you can actually link it, if you can use the cloud, these things are all interplaying. And that is, I think, the challenge, ultimately, when you're looking at this rather convoluted slide. This is from a friend of mine, Frank Diana, from Tata Consulting. This is a real consultant slide, but I'll show it to you anyway. You can download it later. But if you look at this slide and say, holy, this is basically like, all these things are now happening at the same time. Machines that can think, the internet of things, nanotechnology, robotics, the blockchain, genomics, drones. It's like, hard to keep up with this. Well, I didn't tell you right now, these are the key trends that you have to be aware of to define your future. They're all interconnected. But the good news is, it kind of seems like it's all about technology now. Because most of it is so new. But the reality is that most of us can master technology and become a lot more efficient. In the end, the big thing is about what you do with it. There's a great philosopher who said, technology should not be what we seek, but how we seek. So I'll talk more about that in a second, the meaning of humanity here. In the meantime, one of the key Asians is mobilization. You've noticed probably that our mobile phones are becoming our external brain. We keep things in there. Not just phone numbers and bank records and PDFs and Dropbox and music and books, but we actually keep it as a memory. We make notes with it. And this mobile phone world is expanding. Now very soon, we're speaking to our mobile phones. Many of you may already use Siri or Cortana, those assisted machines. And we can use that to do things for us. And now the next thing after mobile phones, of course, is that we have intelligence that lives in the cloud that comes to the mobile phone. I'll show you an example how that is working. Basically, everything around us is connecting to the same cloud.  And then you have the future.  That's because of connectivity. The cloud, some businesses can be 95% more efficient using cloud computing. There's lots of debates about why we should do that and how it could be quite dangerous. The medical records in the cloud without security, that's a bad idea. I mean, the cloud in the US is by nature insecure because it's governed under emergency regulation. They're paid to add the fees according to the NSA. Still is, all these years later, governed under this regulation. Lots of ethical issues about the cloud who's allowed to go in it. But I'll tell you one thing. Until a couple of years ago, many companies said, now we don't want to use the cloud. It should really be right here and stuff. But the reality is that that's just not going to work. You want to be fast and agile and competitive. You are going to use the cloud. And we have to solve those problems of governance, of regulation, of social contract, and of security, of course. Keep in mind that security is not just a tech issue. A supercomputer, which is currently being invented, of course, who else, by Google. This machine is a computer that can actually have computations a million times as fast as any existing machine, called the quantum computer, the D-Wave, they call it. This computer can crack any encryption, including RSA encryption, in 14 seconds. Because it runs all 40 trillion possibilities. So what's going to happen with security then? Who's going to be allowed to do this? So that really creates huge issues about this. And once we have this kind of power, right now the D-Wave takes the power of the city of Zurich to run. So it's not exactly like we can just get one. We talked about the millennials before. The millennials will expect this stuff to just work. They expect everything that they can do on the social networks and on the internet from their service providers. The telecoms, the banks, everyone. Never offline, always available. Voice control, we're only two or three years away from everybody talking to their computer. That sounds like a strange thing, doesn't it? But many of you as households now have this box called the Echo, it's from Amazon. You put it in your living room, and you can speak to it and say, tell me about the weather. Or how do I get divorced? Whatever, it will answer any question, right? In fact, there is about 40 apps on the app store that you can download to get divorced. It's too late for me, but you may want to try it. But I already divorced my American wife. In any case, this is a really mind-boggling trend, right? I mean, I was at the Intel facility the other day, looking at the future of TV. I sit on the couch, and I just say, I want to watch Colombo in 1974, the scene where his wheel falls off the old pigot, right? Boom in place. No buttons, no searching, nothing. That already works, it's complicated. But in the future, you can sit down and say, let me see the wire transfer from XYZ, and it's just like, you know, minority report where you go with your hands into the data. It works. So that's mind-boggling what we're seeing in technology, and this is primarily based on artificial intelligence. Now again, future is better than we think. It will be a long time before a computer has human-level intelligence, right? Thinking machines, they can think, but not like us, right? Because no matter how fancy a computer, they may be able to simulate thinking, but they can't be, right? Well, they also don't have a body as a minor issue, but as you know from the movie Her. But the strolling of dollars now invested in artificial intelligence, that will learn the rules of markets, and here, keyword is actually learn markets. Learn markets, not like your old computers that can do what you tell them to do, right? That's a few years away. It's coming, you know, there's lots of money invested in this. So there's two things I want to alert you to. One is artificial intelligence. That's like this, right? The self-driving car. This will not happen for a long time in the way that it's being pictured right now. This car needs one terabyte of data a minute on a wireless connection. It needs to constantly maintain to do this. It needs to make ethical decisions that we make in the split of a second. These cars will drive from the hotel to the airport on dedicated lanes. They'll take you around the casinos in Las Vegas. And they'll do those kind of things, right? But driving up on the Swiss mountains with a car like this, and that's a long time away. And I'm not sure we would want that because the next thing the car would do it would say, you know, I'm pretty intelligent and people really shouldn't drive, right? No, that's a fact. We are lousy drivers in general, right? Just like we're lousy pilots compared to a computer pilot but still, you know, who would want to go in a plane without a pilot. And then we have intelligent assistants and that is where you should put your money. That's called IA, that's the reverse basically.  Just like when you use Google Maps, that's intelligent assistants.  That's intelligent assistants. The map does not know, for example, that you intend to buy a new car next week. Not yet. I'm sure Google is working on that. So IA is really where the sweet spot is right now and I've talked about this already, we skipped this. So my friend Kevin Kelly, who works at Wired Magazine, he said something really important. He said that basically the business plan of the next startups, 10,000 startups, are all about X and add AI, right? Add artificial intelligence to everything and that includes, of course, banking. It's really interesting, this startup in Los Angeles, their headline is, intelligence becomes a utility. I would say this is because you're dealing with lots of data information and lots of rules and lots of what ifs, right? This is clearly the key to the future. You need that data and you need intelligence. You need both. Intelligent becomes a utility and that is the place to invest because then you can change how you do things and sometimes they're called as the global brain of how this data comes together. In many ways, transactions have already formed a global brain, right? But is it really smart enough to go to the next level? Here's a really amazing brain called Slack. You may know Slack as a collaboration tool, right? Slack is a tool that's used by lots of geeks for development and what this tool does, for example, it schedules automatically your meetings without phone calls or emails, right? If everybody's on the system, it will invite people and coordinate independently. It's a bot, right? It's a robot. It's mind-boggling how that works and how much time it saves. And now there's dozens of those, including bots for booking flights and all kinds of things. And here's a bot that does financial investing. Hello, I am technology that is changing investing forever. I am a fully automated investment advisory service. I can help you choose the right portfolio, monitor it and even rebalance it. I've been called innovative, revolutionary, and just being smart. I'd blusher the compliment if I could, but I can't, so I won't. It's Charles Schwab's intelligent portfolio. You know how many banks are investing hundreds of millions, you probably know, in intelligent robots that replace low-level banking, low-level banking, right? Simple advice. This was said by Mark Andries in the years ago. You know, the founder of Netscape and Silicon Valley Investor software is eating the world. Basically allows you to see all the way through, look at everything. And I'd sometimes turn this around and say, well, maybe sometimes software is cheating the world. Because it's telling us things that are not actually complete. It's telling us important things, but if we rely on them too much, then we get cheated. I take TripAdvisor, you guys know TripAdvisor. If you only go to eat, where TripAdvisor tells you, you are in deep trouble. It's useful to use TripAdvisor, but it's not the reality, right? It's a mirror of reality. It's a slice of the reality. So when you use data, the most important point about data is to use as much and as good as you can, but then add the human element to it because that is the actual human reality. When I meet you in the hallway, it takes 1.4 seconds for us to decide if we could talk further of the interest, if there's interest, who we are. It takes 1.4 seconds without speaking. Find a computer that can do that without input.  Yes, but that's quite a different level. So it's really important to think about what technology does learning machines, for example, are a certainty. But they will not take our jobs as long as our jobs are actually human. If your job is to work like a machine, and the key word is routine, machines will take it. The key word is not job, it's routine. And of course, machines are very good with routine because they don't have unions, they can work all day long, right? It's a very big difference. The rule of the digital age really is this, anything that can be digitized or automated will be. Like years ago, it was music, and it was films, and it was books. Now it's banking being digitized. That sounds kind of like bad news, but it's actually not because the flip side is also true. Anything that cannot be digitized will increase in value. And what is that that can not be digitized? Well, relationships, negotiation, understanding, emotional intelligence, political intelligence, social intelligence, context, design, creativity, all that stuff that we didn't want to actually be a big part of what we do. Emotions in other words. I think the future of what we see in the industry is really this, us riding on top of really and powerful machines and adding those elements to it. There is no business without relationships. You could foresee a world where machines do business with each other, right? But what's the point of that? I mean, ultimately it's about human happiness. It's about those things that are provided by us. And this is the most powerful investment you can make is A, in great technology to help you achieve this. And B, in great people that can achieve this. And we should not separate them. And we should not put too little resources in just one of them and not the other. Think about this kind of scary idea that we would have intelligent agents doing our transactions for us. That is a certainty as much as Tesla is a certainty that BW has to put up with. So we need to figure out what that means for us and how we can add value in the future. And Kevin Kelly again says computers are for answers. People are for questions. You know, when you work lots of companies that I've worked with to help them figure out the future, they want me to give them answers. How can I give answers from the outside to something that's really complex like the pharma business or something, right? You have to ask the right questions. That's how you get to the answers. So if you take one thing away from the day is that to determine our future, you have to ask the right questions. The skills we need, the World Economic Forum has a great slide on this. You can download from their website. It's talking about the skills that we need to be successful in the future. And it's really interesting, 2015 and 2020 are the same top one complex problem solving, right? Same skill and that's what you do. It's complex solving problems. But the other ones, critical thinking and the best one is this one, right? Number six, wasn't even on this year's flight, emotional intelligence. So that is kind of the key for technology and humanity because some technology will kind of make us super human. Like self-driving cars, like robots, like devices, health devices, like this, right? It's interesting to see lots of companies that are in the business and it doesn't go anywhere, it just bloops, right? So there's nothing else happening. But it's really, I mean, we feel like supermen, right? And the U.S. sometimes say becoming as God, right? Because now you can actually do things that used to take 100 people to do. And in five years, one of you can do things that used to take 10,000 people. That's bad for the people who may have left then, right? But those are different discussions about how that will shake out. But with great power comes great responsibility. The whole Apple FBI debate, right? You followed that, I'm sure, right? Not sure what to think about this, what's right or wrong, but it's suffice to say, if you have a lot of power, you have a lot of responsibility. And you have to be aware of unintended consequences. And you have to be aware of machines becoming extremely powerful. Does that mean we shouldn't be using machines? Well, there's no way around that, right? That's like saying, I don't have a telephone. Yeah, you can do that, but maybe Richard Branson can afford to be removed from reality in such a way if he desires to, but really hard to do, right? So what is everybody's responsibility? It's basically this, right? I had this graph I just created a few days ago. Technology is now leading us on this right, right? First technology is magic, right? We can share a dinner bill through an app, right? Fantastic, right? We can pay and do all these mobile things. And then it becomes kind of manic, like there's too many things happening all the time. And the third step, it's toxic, right? Toxic, for example, imagine a world without cash. As much as I would propose that a world without cash would be extremely efficient and cheaper and faster, it's probably not a good idea. And why is that? Because we will be entirely naked in that world. And until it's clear that we're not, I don't think it's such a great idea. That would be possibly toxic, right? If your insurance company knows every drink you've had, how many, at what time, at what time you get up using your Fitbit, I mean, this is George Orwell, right? That's something that we wouldn't want. And money is very much rate. So we'll be all about striking that balance, right? Security, privacy, anonymity is a fantastic business, right? Paying for privacy is a business model, as I'm sure you know. But it should not lead to the simple conclusion that you have to be rich to be private. That would be also quite bad. The internet of things, for example, allows all the information to flow. Now, we really have to think about standards, ethics, social contracts. We have to make those companies responsible for what they are doing with it. This is why we have a debate about the big internet companies and all these things, right? So we're entering the age of digital ethics. Digital ethics means what we do in a digital world has large consequences because it impacts everything around us. I don't mean how we share stuff on Facebook and those kind of things, right? But the rules of engagement, who owns the data? Who controls it? Who is in charge of my identity? What are the ground rules? I mean, we have those rules for nuclear arms. We don't have them for artificial intelligence. We don't have them for data. And that just is bad. I tell you, we're going to see in the near future what are called data Fukushima's. A hundred million health records exposed. I mean, it's unthinkable right now that on the scale that we're seeing is, right? We have to think about how technology can harm us or be good for us, what the balance between freedom and security is. That's your job in this business, right? Everything you do in the future will be largely about ethics, right? But what is right? What is wrong? What serves the customer? What serves yourself, right? As I was saying, the end of good enough, that's one of those things, right? You can't just be good enough. You have to be brilliant. Thought leadership. I'll skip this, because I have to come to the end and do a summary. This kind of stewardship, right? Who will do what? Should there be some jobs that shouldn't be automated?  And I'll tell you the most obvious candidate at Fukushima is call centers, right? It was 25 million people working in call centers. All of them will get fired, except for 5,000, because software can do that. Not the really intricate stuff, but the simple stuff, right? Should they pay a tax to do that? Those are all debates that we're going to have in the near future. So let me summarize this, right? Our future is going in this direction. Three different points. Data. Data is a new oil. Clearly that has become the most powerful driver. Second one is intelligence. Using technology to actually figure out what the data says and what we could be doing with it. For example, intelligent data would be able to save a lot of money in transfers and logistics and those kind of things and possibly solve global warming, possibly. And the last one is human purpose. Adding things that creates relationships that we build with each other, things that we're going to see in the future become much more powerful. So it's a quick summary and takeaways and point number one, exponential. If you're still sitting here and saying, well, it will take a long time for that to happen, think again, because in most cases it's not.  It took longer, but it's here now. All the stuff you think of science fiction is a lot closer except for very top level like colonizing Mars or something, right? But in business, very quickly. It's the framework that changes. You shouldn't just change one thing in the company to make it work better. You have to do that anyway. But think about what would you do if you started today? I mean, I asked myself the other question the other day. What would I do as a futurist if I started work today? Well, for me, the answer was, I would focus on saying things that computers can't say. So I would focus on not being smarter, but being more human. Because being smarter is a losing battle. Computers can be smarter. So think about what that means. Ecosystems, platforms, banking is a primary target for disruption. I mean, across all of the pieces of what you do and the back end even more than in the front and just takes longer. And there's a protection of regulation and those kinds of things. We talked about this already. Balancing technology with humanity, I always like to say we should embrace technology, but not become technology. I think that's where the value of us, people goes in the future. Digital ethics. You know, years ago, when I talk about ethics, companies used to yawn and say that's just like CSR, like sustainability, right? Nice to have if we had time. And you wouldn't believe how many tech companies I talked to, they say, well, ethics, what do you mean? That's not business, that's another department, right? It's losing money. If you're not good on ethics and you can't figure out where we're going with this, you will not win in the future, right? Because everything is now about decision making that impacts people. Business models evolving to experiences. How would that look like for you? I think that is one of the key questions. That's the final quote. I think I would wish that for you and that you can hear it coming because the future belongs to those that can. David Bowie, rest in peace. Thanks very much and thank you.


Your Majesties, Excellencies, colleagues and friends, today we have a moment to demonstrate how important forestry is for the future we want. We want sustainable development for all. We see the whole world unit in one single universal agenda. We have one planet and it's our shared responsibility. The community proposes the area and they will get help from task force. We establish many task forces at the provincial level.


My name is John Lille Marcus, and what I want to talk about is thread modeling, mechanical and locking systems by analyzing puzzles. So what I want to talk is this is a security awareness, but a different, different type because whenever there's security awareness, we see billboards like these. It says already this year, 19 burglaries and please prevent burglaries if you see something call us, et cetera. But for me, that's not really the point, like you can give a lot of advice, like keep your lights on or don't leave your variables laying around, but there's more to it. Let's go into it. So first off, can we prevent burglaries? I would say no, but we can make it a lot harder. Then there's a lot of arguments about breaks and lions. The one is why should I buy good locks if someone can break a window with a rock? That's totally fair. As for lions, people always say, I don't need to outrun, I don't need to outrun a lion, I just need to outrun the persons with me. I think that's fair, but it's still not very nice. So I'm going to try a different way. So first, why puzzles? First they are fun. I have a few here, I have a few at the lock picking village. And examples are, there are plenty of them. I have a small collection, I do a lot of very hard Sudoku's with the guys from cracking the cryptic where I solve those puzzles often. But the foremost reason is that nobody cares. So whenever I talk about security topics, then it's always people have opinions about it. And when I talk about puzzles, then nobody cares. That's very nice. So one thing about tool, we exist, there's the open organization of lock pickers. It exists here in the Netherlands, it exists in the United States, United Kingdom and Australia. Here in the Netherlands we have weekly lock picking sessions. And if you want to learn more about the topics I'm sharing here, then please consider visiting us at our lock picking village. It's just right next door on this field. So let's go into thread modeling. This is a simplified version. It will just take a lot longer, but it will get you started. So before we start, start to thread model, we want to find what is an asset, what's an attacker, what are vulnerabilities. Let's just be clear on the definitions, or at least the definitions I will be using during this presentation. Because if we use different definitions, if I say thread and you mean you think on a vulnerability or risk, then we're thinking about different things and it's going to be confusing. So for the asset, that's the thing of value. This is either a valuable to the defender or valuable to the attacker, because if the asset is not valuable to the attacker, then of course your system will not be typed. And this can be anything from information or money, but I've also seen on this camp data being locked up. I've seen toilet paper being locked up. Just whatever is your system. For the threat or for the attacker, I would define it as an entity that is skilled enough to gain access to the assets. The attacker needs motivation, opportunity, and a method. And if it either lacks one of them, then you don't have an attacker for your system. I define it as skilled enough, because also if the attacker is not skilled enough, then again, for your system, you don't have an attacker. It's not necessarily intent, but the achieving for the vulnerability. We define it as an unintentional flaw in a system that leads to a compromise of an asset. And these vulnerabilities can be exploited by an attacker. Let's take a look at a few case studies. Here I have a box of woods. It works like a mechanical combination lock. So in this case, it has sliders. It's a puzzle. And if you move the sliders past these notches, then the lock will open. The box will open. And for this, because it's a puzzle, it's intended to be carefully handled. It's created to not use damage. However, for this model, I found that someone else was before me. And they just ripped the pieces apart. That's a different model. And what I found for this particular box, it has a congratulations message. And it also assumes that you didn't use a soul. Did brute forcing, did damaging its fit model? I don't really know. The second one is this puzzle. It's a deal-all ring. It's a hidden maze puzzle. And there are several types of them. They started around the 1990s. And this should have become the best thing ever after Rubik's Cube, but it never became that big. And the goal is to move the ring from the puzzle.  This is the orange version. And as we see on the box, we have the instructions. And we also have different levels. So there is the easy yellow up till the terrible black. Because I only had the orange one, I assumed the black one would definitely be a lot harder. But a few people in the know told me, now it's just all psychological warfare to some extent. So that's nice. But at the moment, I don't have access to any of the other ones. I can only find the yellow and the orange ones for sale. So if anyone has the green, blue, red, and black, I'd like to be an attacker. I'd like to have the opportunity to defeat them as well. So I mentioned for this puzzle the intended solution or the intended way of manipulating them. But we can list the possible attacks. And here's just a very short list. And I separated them to solving the maze in different ways, using brute force, or just trying out all the combinations, building a robot, just like we manipulate saves at some point. But we can also learn the maze some other way. Maybe someone else already published this on the internet. Or I can just find someone that knows the answer. Or I can use more advanced techniques, like getting an echo or an x-ray made. These seem quite far-fetched, like an x-ray. Why would you solve a puzzle like an x-ray? Well, that all depends on the asset. Is the asset valuable enough for the attacker? And so I like to list them and then cross them off if they're not applicable to my threat model. But we can also bypass the save by just filing away the knob or just using a lot of force and just pulling the maze free. That's all something to consider. Just for fun, I tried it this way. So I taped a piece of paper around the cylinder, built a contraption, and just solved the maze. And it drew out the maze very nicely. And I solved the puzzle in the end. So I did solve it a few times beforehand, but now I have the real maze as it is inside. So let's talk about locks for now. Because puzzles are interesting, locks are more interesting. For me, locks are puzzles. For a tool, locks are puzzles. And the question always arises, can any lock be picked? And is lock picking realistic? I think it's an interesting question. And I think if you buy tens of a lock, if you take them apart, if you study the same lock for tens of hours, hundreds of hours, thousands of hours, then put the lock back together very carefully and start manipulating it, it might be possible that you open this one particular lock. But for me, because it's a puzzle, that's for me the form of realism. That's not the same as if this lock was on the door or being used. For this, I used the thread model of a lock picker. And what it wants, it wants to open a padlock, open a shackle, call it open. But more precise, it wants to rotate the cylinder without using the key. And what a lock picker has, or at least in this model, the lock picker has lock picks and infinite time and infinite patience. So if this is a type of attacker you want to keep out, then maybe you need to do other things. You need to consider this. Another thing the lock picker has is these rules, ethics. So only pick your own locks and only pick locks that are not in use. The CTF people, they have a nice idea about this. They made a contraption of 3D printed plastic, and it has a slidey bit, which has the CTF flag. So you can prove that you've picked it. At that moment, the asset becomes the CTF flag. But then the lock is in use, so are we allowed to pick it? So for the lock, we have here a basic euro cylinder, just no name, no brand, nothing special.  Just to go over it quite briefly, we can use a normal, we can use the key to set all the pins to the red line. We call this a shear line, and this allows the lock to rotate. But the wrong key will not allow the lock to rotate. We can also use lock picks like these and go through the lock, pin by pin, find the binding pin, get feedback this way, and open the lock. That, of course, takes a lot of practice and also a lot of time, but it is a nice challenge. What's even more of a challenge is when locks started having these security pins. They're different shapes, different feedback, different puzzle. There are a few more of them. For some lock pickers, they think normal locks are boring, so they start creating their own. And we call them challenge locks.  The first two from the left are normal pins, and the other ones are created by lock pickers themselves. This one, in particular, is from a community-built lock. It has 10 pins and two sides. What was very funny about this one is they glued the two sides together. So you have to pick the front side and the back side all together to open the lock. So definitely a challenge. And then there are people that create unpickable locks, or at least they claim them to be unpickable. This is a handy book that's a friend in the UK. I created this particular lock. He uses unpickable with an asterisk, like asterisks like not picked yet. He has a patent on this particular design. From the front, it doesn't look too bad. But if you take the lock apart, we see that it consists of quite clever mechanisms already. We have an inner core. We have the housing, and we have an outer core. And what he bases lock on, and what he bases his patent on, is a probability game. Like he used a lot of master wafers, as we see here. And all these small wafers create a lot of different shear lines for the first core. But the second core can only rotate if both of the shear lines are met with the one thicker pin. So the probability of hitting the second shear line are much lower. And it also drives us from our usual feedback. So that's definitely a fun puzzle. The next one I have here, I bought at some point a few racks of safety deposit boxes. I used them to store my locks. And I removed all the cylinders, because I didn't really care to lock them up. But these safe deposit boxes are usually, you can usually rent them at a bank, where they are in a basement, in a vault, and you can rent just one locker. It's not that expensive, and it's sure to quite a bit. I found myself, and I use it to store backups, and a few documents that I don't want to lose. But each is their own. It's sure to such a high value that it might, you could also put your valuables in there. But in particular, I want to talk about this lock. This is the Rosengrenz Safe Deposit Box lock. It's quite an interesting lock. And it's quite an interesting lock. It's a form of a disc retainer, but the discs are quite big. And this is quite difficult to manipulate. And they did so intentionally. They made the keys hard to duplicate. They made false notches in the discs. And that's all to prevent someone from getting access to the assets without damaging the lock. So here we have the key interacting with the discs. So off this lock, we have eight elements of six different shapes. And this is more than a million different combinations. You cannot get the blanks. Of course, the most determined attacker can make these. But the assumption is, if we just have two keys, these keys only belong to the owner or the renter of the lock, of the box. Then if the lock is intact, then no one has access the valuables. And I believe this is more of an insurance thing, but also, of course, how you build your treadmill. But what I found surprising about this lock is even though it has so many features to make a lock picking hard, to make key application hard, it isn't drill resistant. The core is made of a very soft metal. This isn't a flaw. This isn't a vulnerability, only if you don't know about it. Because this is a design choice they made their lock. So it is very hard to manipulate, but easy to destroy in case they need to destroy it. Let's now go from lock picking and the infinite patience to a simplified model of a burglar. What a burglar wants, access to the items that you have locked up. And some burglars might have fast entry tools and methods, including bricks, including hammers, including axles. You name it, but it has very little time, just under two minutes. Again, when we have this same cylinder, there is a very known flaw. In this cylinder, it's mounted with a screw hole, and this is also a pivot. So there's very little material there to hold the lock together. And this is such a common issue that the better brand locks, the better certified locks will have hardened bridges or anti-snap features. So this is a lock from the UK, where it has as both sides anti-snap features or pro-snap features because they will snap before the cylinder snaps in too. I like this design, and it works quite well. Because at least you need two attack methods to gain entry to open this lock. Even more pronounced are our locks like these, also from the UK, where it has two snap features at both sides of the lock, so both internal as external. That's not too common. And also, when you snap the second feature, it has a relocker. So you can never open it from the outside if the part has been snapped, or so is the idea. And then the middle bit is a hardened bridge. It's a very tough metal, and it's very difficult to get into this. And all these features are required by the standards. They have the British standards up to three star, and they also have the solid secure. And this one is rated solid secure diamond grade. That's the highest of the high. And circled here in orange is also some protection against non-destructive attempts. And these are trap pins. So if you pick the lock and it rotates 20 or 30 degrees, these trap pins will fall into the lock. And it is very difficult to get out of them. It's certainly not impossible, but I've been practicing with one of these locks, and it took me a better part of a week to get past these trap pins. So in all normal circumstances, where you say your burglar only has two minutes, this will be plenty. Let's now go for some other security advice. Again, you cannot prevent burglaries, but you can make it a lot harder to get in.  I don't know how to protect against elephants, but it would be quite a beefy lock to do that. What you should do is consider the whole system and then protect your assets accordingly. One of the advice we usually give is key control. So who has your keys? This particular picture is one I put on Twitter a very long time ago, and also on the tag. You can read that it's from a CTF. So if someone fancies, please make me a key. Find me somewhere later, and then we will test it. I don't have the locks with me on site, but we'll arrange something. So if we have a picture, then a determined attacker with enough skill, enough knowledge, can duplicate a key. This is what we call usually key control. And lock manufacturers notice for a very long time, and usually you're not able to find the blank keys to make duplicate key without the authorization of the manufacturer. And here I have a, on the background, this is a 3D printed key. It was quite a nice challenge. It took me hundreds of attempts before I got the FDM printer to work correctly to print these almost tens of micrometer steps. But with an FDM, as less printer, it was first attempt. It worked flawlessly. So again, consider these things in your threat model. Also consider existing security schemes. There are plenty of them. Just find the relevant ones for your country. One you should check is what your insurance wants. And then you can go much higher from there. One most common here in the Netherlands is SKG. And then three stars will give you five minutes with a selection of tools. The lock on the background is an MNC. That's a quite affordable lock. Maybe not this particular one. This is their latest model. That's the MNC move. It has a movable element in the tip of the key. And it has some other interesting features that make it very difficult to duplicate this key without the authorization from them. So to recap this presentation for your system, you want to find your assets. So think of what is valuable. What are the things that you want to protect? Is it your data? Is it money? This can also be your feeling of safety. That's a difficult asset to protect. But it's definitely an asset. Then you want to define your attacker. So is it someone? Is it an entity that has all the time in the world, all the resources in the world? Then it's going to be very difficult to protect your assets. But if it's my simplified model of a burglar, then that might be already a lot easier to protect against. Then you want to find vulnerabilities in your system. So either just start listing all the ways to attack your system, all the ways to get to your assets through an attack tree. But you can also just ask for help. And for nonprofits, is definitely able to help. But we don't do consultancy and no paid kicks in that sense. And lastly, you want to implement enough defenses so it makes it impossible for this one attacker to get access to your assets. Or at least to delay them enough, et cetera, et cetera. Wrapping up, there are two books you should consider. The Thread Modeling Book is very nice. And also, we have a book about locksports coming in the very near future. And that's written by Jos Weyers and Walter Belgers and a few other locksport friends. I do have time for questions now. But if there's any interest to you, please come and see us at the Lockpicking Village. That's next door. Thank you. So there is actually some time for questions. If you have any questions, please line up at the microphones in the middle of the room. And while you do so, I already have a question. Do you have any special locks you use at home, or are they just normal ones? They are definitely just commercial locks. But they are of a special type. For me, it's most important that if someone ever would get in, there is damage. I would definitely hate that I'm is someone in my house, or am I losing my mind? So I'd rather have them break my door than take my locks. OK. So are there any questions from the audience? Don't be shy. He's still here. No. Then just thank you very much for the talk. And if someone has a question afterwards, you can always find him and ask that. Give a round of applause for the question. OK. Need a few seconds to come up with a question, of course. That's an impeccable lock. Yes. If it were to be a commercial lock, how much do you think it would cost? He has a patent. But just looking at what other people are selling, then it would be 150 pounds, something like that. But he is not commercially making them yet. He is just testing the waters with his patent. And hopefully it's just an inventor. And inventors like to invent things, but they don't have the capability to mass produce locks. So if anyone is interested, please find Andy. OK. Then again, applause, please.


Alright, so here's a summary of what Raoult's law can tell us so far about binary solutions, ideal solutions. First we just have a sketch of our binary solution, A and B in the liquid phase in equilibrium with their vapors. Raoult's law, of course, tells us that the partial pressure of any one of those components above the solution is its mole fraction times the total vapor pressure, summarized in this somewhat complicated looking diagram that has a very simple interpretation, which is that as the mole fraction changes from 0%A up to 100%A from 0 up to 1, we change from a pure solution with pressure equal to the vapor pressure of B up to a pure solution with a pressure equal to the vapor pressure of A and we just move linearly from one to the other. So that has all been in terms of the mole fraction in the liquid phase if instead I want to think about the mole fraction in the vapor phase. So I'm going to use, instead of x, which is the mole fraction, I'll use x for the mole fraction of the liquid phase and I'll use y for the mole fraction of the vapor phase. That's a fairly standard convention so we can keep track of which mole fraction we're talking about. The mole fraction in the vapor phase is going to be, we can think of it as moles of A over total number of moles in the vapor phase, but since it's in the gas phase of the vapor phase that we're talking about, I can think of N as PV over RT. So it's PV over RT for A, so in other words partial pressure of A times V over RT divided by total number of moles and that would be total pressure. In this case, if we think back to the case let's say where we have a 50-50 mixture that had 100 tor of B and 200 tor of A just as an example, if we have 200 tor of A and 100 tor worth of B, then after some cancellation here the V, all these systems are in the same volume, they're at the same temperature, R is a constant, so the V and the R and the T cancel and we just have PA over P total. In this case, PA of 200 over total pressure of 300 for that 50-50 mixture of a solution where A is more volatile has a higher vapor pressure than B, it turns out that the mole fraction in the vapor phase is two thirds, it's bigger than one half. The important observation here is the vapor has been enriched in the more volatile component. The more volatile component with the higher vapor pressure is A, the mole fraction in the vapor phase is greater than the mole fraction in the liquid phase and that's going to turn out to be a general trend. If we want to draw a more general conclusion about not just for specific cases with specific numbers but if I want an expression for how to compute the mole fraction in the vapor phase in the general case, let's go back to this expression. So before I plug actual numbers in, the mole fraction in the vapor phase is pressure in the vapor phase of that component divided by the total pressure. So partial pressure of A in the vapor phase, Raoult's law tells us how to calculate that. That's mole fraction of A times vapor pressure of A and I want to divide that by total pressure. But we know something else about the mole fraction of A and or the total pressure. This expression tells us what the total pressure is as a function of the mole fraction of A. So in fact probably the easiest way to think about this is to take this expression and rewrite it to solve for mole fraction of A. So if I write mole fraction of A, so I'm going to insert that in right here. So if I'll solve this on the fly, I'll write mole fraction of A is equal to total pressure minus Pb star, moving this one to the other side and then I'll divide that by this quantity in parentheses, Pa star minus Pb star. So all I've done here is I've solved for mole fraction of A in terms of the total pressure, inserted it here for the mole fraction of A. I still have to multiply by these terms Pa star and P total. That, if I know these numbers, if I know enough to plug into the right side I can compute now the mole fraction of A. What I'm actually more interested in is drawing a graph like this one pressure as a function of mole fraction. So I'd really rather rearrange and solve this equation solving for P total which appears here twice as a function of mole fraction in the vapor phase. So let's work on that. To get rid of the denominator, I'll just take these two terms and multiply over to the left. So I've got P total times vapor pressure of A minus vapor pressure of B all multiplying mole fraction. That's on the left side. That's all equal to what's left on the right side is this numerator, P total times Pa star minus Pa star times Pb star.  If I want to isolate the two terms involving P total, let's put the Pa star Pb star over on the left side and bring this term with the P total over to the right side so that everything on the right will involve P total. And I've got P total times Pa star.  And if my goal is to rearrange this and solve for P total, I'll do that over here. I can take the term in brackets, move it over underneath the Pa star Pb star on the left. And I've got Pa star Pb star in the numerator. And then in the denominator, Pa star minus mole fraction in the vapor phase. And again, this difference of the mole, the vapor pressures, Pa star minus Pb star. All right. That's what I claim to be after. That's the total pressure of the solution as a function of the mole fraction if I also happen to know these vapor pressures. So I can draw a graph much like this one. If I draw a graph of total pressure as a function of mole fraction, but now mole fraction in the vapor phase, I'd have to graph this function. We can find the two limiting cases relatively easily. When the mole fraction is zero, if I put a zero in here, so the whole second half of this denominator disappears, the Pa star is cancel, then I'm going to have just as before. And unsurprisingly, when I have mole fraction zero, if the vapor above the solution is purely B, then the solution must also be pure B and the partial pressure is equal to the vapor pressure. On the other hand, if all of the vapor is A, if 100% of the vapor above that solution is A, because the mole fraction is 100%, if y sub A is equal to one, then let's see this negative one times Pa star is going to cancel this Pa star, negative one times negative Pb star, that Pb star cancels this Pb star, and all I'm left with is a vapor pressure of A Pa star. So far, this is looking exactly like it did in the case we considered before, but we can look at this equation and know that it's not going to be a straight line connecting these two. This is no longer the equation of a straight line. It doesn't look like this is a constant plus a slope times the variable we're interested in. It's a nonlinear function, and if we stared at it a little bit harder, we could convince ourselves that it's actually going to not only not be linear, it's going to dip below linear, so I'll draw this graph as a sagging line of sorts. It still is equal to vapor pressure of B on this side, vapor pressure of A on this side, but it's not a straight line. In fact, if I combine these two graphs onto one, if I plot total pressure as a function, so this upper curve is total pressure as a function of x of A, the lower curve is total pressure as a function of y sub A, the two curves are different. This expression is different than this expression. So I have two different equations, two different curves for how the total pressure depends on mole fraction, because mole fraction in the liquid and mole fraction in the vapor are not equal to each other. That itself has some interesting consequences, and if we think carefully about how to interpret this diagram, we'll learn a lot about the equilibrium between liquids and vapors above a solution. So that's what we'll do next.