Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer, Michael Surmer So our book table is down there. When you go by there, please say hi to Pat Lindsey. Pat is the person who does all the covers of Skeptic Magazine, all the layout and design and typography, and all the flyers and all the artwork you see on the web page and so on. She's my partner in the Skeptic Society, Skeptic Magazine, and she doesn't get a lot of recognition. She's behind the scenes, the power behind the scenes there. So say hi to her and also to Will, who is our webmaster, who does skeptic.com. And when you get a chance, the second favor is, check out skeptic.com and our Skepticism 101 program, which we just launched last week. And so we're taking skepticism into the classroom, how to teach a course in skepticism, how to take a course in skepticism. It's a little bit like ted.com or the Khan Academy. We're accumulating videos and PowerPoints and keynotes and lectures, lectured notes, readings, illusions, projects that teachers can assign to students, things like that. If, and it's all free, you can just download stuff. So if you're an educator of any kind, a teacher or just a person interested in educating people, if you have materials you'd like to put up on the web page for people to use that you think might be useful for teaching, critical thinking, skepticism, all the good stuff that we do. We'd love to have your input on that. So when I was walking back to the green room here, I noticed the crawl said something about Michael Schirmer making a presentation about his previous books simultaneously about his next book. I'm really embarrassed because that's exactly what I'm doing. So I was sitting back there thinking, is there some other talk I can give? And the problem is I'm a writer, so I write about everything I speak about, so it's kind of inevitable. So the next book is, oh, I guess do we have, is it on the screens? No, okay, so if we could put up the, yeah, okay. So what I'm doing here is taking an inspiration from a 19th century abolitionists named Theodore Parker. I'm just trying to get a full screen here. I can see what it actually says. That should do it. Is that, can you see that? You know what, I think it, I gotta go to view. Yeah, you guys, you didn't turn it on to the play. Here we go. It's play is what we want. There we go. So he writes, I do not pretend to understand the moral universe, the arc is a long one. My eye reaches but little ways. I cannot calculate the curve and complete the figure by the experience of sight. I can divine it by conscious and from what I see, I'm sure it bends toward justice. So we've come a long ways in a century and a half in terms of figuring out what has actually been going on. So what I'm doing is I'm taking, I'm pushing forward from these four books, my own, The Mind of the Market. I always pick up in the last chapter and write a new book from there. But Matt Ridley is the rational optimist. Robert writes non-zero and especially Steve Pinker is the better angels of our nature. I've all tracked the trend lines that things are getting better. Things are getting better economically, politically, socially, culturally and especially morally. So where I'm going with this brief presentation is I'm gonna do a data dump of show you that things really are getting better and then offer some explanations for why. And ultimately I think it comes down to the fact that it's reason and science. I'm using the word science, the moral arc of science and the broader sense of reason, empiricism, logic, open-mindedness and liberal values that came out of the Enlightenment. So that's where I'm going with this. So something extraordinary happened from hunter-gatherers to consumer traders, just starting economically and then politically. So if you count up all the items in a Yanamomo village and you calculate what their average annual income is, the equivalent thereof, they average about $100 per person per year and they have about 300 different items in their catalog of stuff. If you walk into the Manhattan village and count up all the goodies and products that the Manhattanites have in their stores, it comes out to about 10 billion different products. That's based on the barcode, SKU stock keeping unit system of the barcodes and about 400 times more income, about $40,000 per person per year. The question is, how did this happen? So here's a different hockey stick curve that is the tracking of world GDP per capita just a little over 60, it's about $6,600 per person per year for the entire planet. And all that has happened in the last 150 years or so. And this is the projection. It'll double by 2030. Every single one on average across the world of the 10 billion or so that will be at 2030 will average about $12,000 per person per year. Obviously there's a big difference between the West and other countries, but we'll come back to that. So as people got wealthy or a lot of other things got better, poverty collapsed dramatically. That is poverty defined by a dollar per day as the baseline rate. That's tracked down fairly consistently. Even in Africa, even though it's been bumpy bouncing up and down for the last half century, the last decade and a half or so, it's getting much better even in Africa. Global serial harvest. So you see the flat black line there is the acres harvested. So we're not harvesting any more acres but the yield per acre has been increasing thanks to science and technology. Life expectancy at birth, world average from just a little below 50 to just a little under 70 now in the last half century. Percentage of increase in world population is going down. World population is not going down yet but the rate of increase is going down and eventually that'll flatten out. And the UN projects that about by 2100 it'll flatten out at about 10 billion people and then we'll start decreasing. We'll be back to where we are now by about 2150 or so. So even though overpopulation has always been a mantra of my generation, I think there's progress there too. So just culturally, just think about King Louis, the 14th, the Sun King who had a fabulous kitchen and hundreds of servants and compare that to the average middle class person today where you can walk into, you and I have hundreds of servants waiting for us right now. You can go down to Starbucks and there's a barista waiting for you to make your vente latte just the way you like it. There's somebody to work on your car and so on. There's kitchens like this fabulous kitchen, way better than anything King Louis, the 14th had that you can find in almost any middle class home being built today. And as life got better it also got safer. This is a little known fact that rates of homicide have plummeted in the last six, 700 years from about 35 murders per 100,000 to in Europe, less than one per 100,000 today. It would be zero except there's always some nut job that does some crazy thing that you can't control for. Otherwise violence is practically zeroed out in Europe. It's about a little under five per 100,000 in America but even that's mostly clustered in inner cities and gang-related drug-related crimes. You can see it in, if we track the databases of a lot of different data sets here, violent deaths in prehistoric societies compared to state societies today. So the red line there is the average of all those data sets to the left of the percentage of deaths in warfare. And here's the United States and Europe in the 20th century, the world for the entire 20th century, the world in 2005 is not even a single digit, a single blip on the screen there. And then you do another data set here of war deaths per 100,000 people per year in non-state societies. So the previous data set were archeological data sets. These are current non-state societies and their average rates of death per 100,000 people in war. So that's the average on that red bar there compared to Germany in the 20th century, Russia in the 20th century, Japan in the 20th century, the United States in the 20th century, the entire world in the 20th century and in the world in 2005, again, not even a single blip on the screen there. So things are definitely getting better in terms of warfare. Again, homicide rates have plummeted from almost 100 in some areas to practically down to below zero now. You can see it in different independent data sets from different countries in Europe and then the overall, the blue dot, the non-state societies average versus over the past 700 years of the plummeting rate. So it's a logarithmic scale there. So you're going almost 100 per 100,000 murders down to less than one per 100,000 in Western Europe. Even wars are becoming more civilized even in the 20th century. So it's hard to get around, it's hard to say things are getting better and ignore the 20th century. But it's good to remember the 20th century was 100 years long, not 50. The first 50 years look bad, but the second 50, as we'll see. Great power wars, here's some more data sets from Levy and Thompson. Great power wars, 1,500 to 2,000, a portion of years that they spent fighting each other has plummeted down, bounced around on the bottom there and is now zero. Duration of wars involving great powers. We're talking about great European powers here. Between 1,500 and 2,000, again, bouncing around but plummeting back down to zero now. Frequencies of wars involving a great power. Just think about it now. What are the chances that France will march an army through the channel and invade London? It's not gonna happen, right? And yet, that was the history of the great power is that they always were at war with one another. So again, remember, the 20th century is 100 years long, so although there's the two huge blips of the First and Second World Wars, the big mystery to explain is how come there haven't been any others since then. In fact, since 1946, there's been zero wars between the US and USSR, zero nuclear weapons used, zero wars between the great powers, zero wars between Western European countries. Before 1945, there were two wars every year for 600 years and that has ended. Even genocide. So these are Rudy Rommel's data sets that have been since collaborated by others that, so that even though there's Rwanda and Cambodia and things are grim, so here's the problem, our brains are designed to, design, evolve, sorry to get past that word. Designed by natural selection. Okay, thank you. To just notice the bad news in the immediate horizon of our time frame and environment. So of course, we noticed Rwanda and Cambodia and so we remember these things more freshly, but they are minor blips compared to genocides in previous centuries, especially culminating in the Holocaust. So how did all this progress happen when we live in such a tribal world? Okay, I'm just gonna blast through. By the way, that was like 1% of the data slides that I could have presented. There's a lot of data to show things really are getting better. Okay, what happened? So five points there that we'll go through. Beginning with the fact that we do have moral emotions. We are moral creatures by nature. We evolved a dual moral nature. We have a good side that is within our groups, we practice enmity, we're nice, we're cooperative, we're post-social, we're altruistic to our fellow tribe members and between groups. We practice enmity. So we have a little bit of Oscar Schindler, a little bit of Amon Gert. We have inside of us both Colonel Kurtz and Captain Willard and we are both a good Kirk and bad Kirk. Hey, you watched that episode again. That's pretty deep. When Spock explains to McCoy why this is such a good experiment to understand the dual nature. And in fact, Roddenberry had really constructed the whole cast to be like that.  You gotta have testosterone and oxytocin. Kirk had maybe a little too much testosterone but that's okay, he always got the girl. Anyway, so there's a little bit of that. In other words, we're both naughty and nice. More seriously, I think both the Stanley Milgram shock experiments and Phil Zimbardo's faux prison experiments show that on the one hand it is easy to get people, even middle class college students to commit acts of violence. It's not hard to do but on the other hand if you actually watch the videotapes and in the replication since then people are very distressed at doing it. It's hard to get them to do it. You can get them to do it but they're not happy about doing it. There's a whole program you have to set up to shift the good part of our nature and squelch that down and bring up the other part of the thing. It's doable so the whole point of civil societies is to set it up in a way to attenuate the one and accentuate the other. And the long-term trend is that there's been an expanding evolutionary circle of sentiments. That is evolution granted us a sense of empathy for our own kin and kind. And the circle has expanded from bands and tribes to chieftains and states to all races and sexes. Well not quite but we're pretty close. We're getting there. By the way I'll make my annual prediction about gay marriage. In a couple of decades this will be like the black and white drinking fountain thing. It'll be much ado about nothing and people in 50 years from now will look back and they'll write the little history about the early 21st century and say what were they thinking? That was insane. And by the way the Christians will take credit for it. They'll say you know that Episcopalian minister? That was our guy. He was one of ours. Yes, right? Anyway I'm just putting that on the records. That's there. So my argument is that we've been climbing this pyramid of on the bottom rungs being most concerned about ourselves, our immediate family, our kid and kind, our fellow tribe members and ignoring all the rungs above it. But historically speaking we've been shifting our empathetic concerns to the higher rungs, the community, people in other tribes, even other species, and maybe even the biosphere. It's a long road to hope but we're getting there. Okay how did this happen? Two, the Leviathan state. You have to have a state. Okay so here's the non-libertarian surmer speaking. You gotta have a system of rules or people will cheat in case you didn't notice. And I'm not just talking about sports. So what basically what a Leviathan state does, this is Thomas Hobbes' Leviathan. This was his argument that you have to have a state that takes a monopoly on violence so all the little mafioso types and thugs and gangs, that's what drives rakes of violence up is they solve their own social problems and conflicts personally. It's called self-help justice. If the state doesn't do it, I'm gonna do it. I'm going over to your house at midnight and we're gonna settle the score. Tomorrow at noon, you know, out of the street, something like that. The state says you're not gonna do that anymore, we're gonna do that. That's why the law says it's the state versus so and so. The state is now taking care of justice. So that reduces the need for deterrence and vengeance and that reduces violence and it makes conflicts resolved in a more peaceful way. The problem is the Leviathan state can turn into an autocracy, a theocracy or secular dictatorship which is a destroyer of peace, prosperity and freedom. So not any state will do, democracies are better. The first theoretician on this was none other than Emmanuel Kant in a little-known book that he wrote called Perpetual Peace. He basically outlined three conditions you need for this to operate. He called it a republic, but he meant a democracy of some sort. And then the second one was some sort of United Nations or a League of Nations or some kind of interdependency between nations and then the third one was sort of an interdependency of people through trade, through commerce. In the 20th century, Rudy Rommel was the first to identify the fact that governments kill a lot of people. So although violence has declined between people, governments got more violent for a while until democratic peace process took over in the last century or so. His books, Death by Government and Power Kills documents some of that. Now Rudy was the first to put forward this idea that Tom Friedman picked up in The World is Flat that no two countries with McDonald's ever fight each other. Well that's actually not quite true, but it was Rudy that first identified that through a smaller data set over the course of the last two centuries, in which he claimed that there were no wars between democratic nations. And of course, Polly Sy, a professor, jumped all over that and said, ah, there's lots of different examples of democracies that have fought each other. The Greek wars, the Punic wars, the American Revolution, the French Revolution, the War of 1812, the American Civil War, these are all democracies fighting each other. So we have to move away from the black and white two categories. You're either democracy or you're not because there's lots of shades of gray in between. The best book on this is Triangle, 80 in Peace. Bruce Russett and John O'Neill, they tested Kant's thesis of the triangle of peace. And this is the correlates of war projects. So they have 2,300 militarized interstate disputes in their database. It's 10 times the size of Rudy Rumble's database. And then they use the polity project, which assigns each country a democracy score. So you're a democracy from one to 10. It's not just you either are or you aren't, it's a scale. This is good science, right? Shades of gray, okay. And those are defined on how competitive the political process is, how openly the leaders are chosen, how many constraints on the leader's power. So they found that when both countries are fully democratic, disputes decreased by 50%. When the last democratic member of a pair was a full autocracy, it doubled the chance of a quarrel. So shifting from a minor democracy to an autocracy increases the probability of violence between states. And so there you can see the rise of democracies and the collapse of autocracies in the last half century. We have to just think about that. There were no liberal democracies anywhere in the world in 1900, zero. Even in America, women couldn't vote. Adult population could not vote in America until 1920. I mean, that's really amazing. On the one hand it's a little embarrassing, but on the other hand, we've come a long ways. So here's the part three, the part that the libertarians will like. And that's trade or general commerce. That is plunder is non-zero. This was Bob Wright's argument in non-zero that there's been an increase in non-zero games and exchange is a way when it's done by the rules. Trade is a non-zero sum, win-win type exchange. And improving technology allows trades of good and ideas.   This is a form of swapping ideas and swapping it. Any time strangers exchange with one another in a positive some way, it reduces the probability you'll treat them as a tribe member in some other tribe who's an other, who's not like us. It reduces those sort of tribal barriers there. So open economic barriers decreases political barriers and therefore leads to more empathetic consideration of the other as a fellow tribe member. So Russet and Oni put that to the test in their dataset and they found that for every pair of at-risk nations, they entered the amount of trade as a proportion of their GDP gross domestic product for the more trade dependent member. They found that countries that depended more on trade in a given year were less likely to have a militarized dispute in the subsequent year, controlling for democracy, power ratio, great power status and economic growth. Democratic peace works only when both members of a pair are democratic, but trade works with either member of the pair has a market economy. I think it was Friedman that said, one reason not to go to war with China is they make my car. Or my computer or my iPad or whatever. So the rates of international trade have gone up dramatically in the last, a little over a century, especially in the last half century. So international trade is good. So you put them all together into the peace triangle, democracy trade and then the third one membership in IGOs, intergovernmental organizations. So Russet and Oni accounted the number of IGOs that every pair of nations jointly belonged to and ran a regression analysis with democracy and trade scores and found that democracy favors peace, trade favors peace, membership and IGOs favors peace. And a pair of countries that are the top 10th of the scale in all three variables are 83% less likely than an average pair of nations to have a militarized dispute in a given year. So that's the growth of membership and intergovernmental organizations. Why does that work? Because evil happens in secrecy. This is why North Korea is a secret society. The moment everybody is watching you and people know what you're doing and people are talking about you, you're less likely to commit violence. This is the whole reason for joining these organizations. Even though countries don't really want to selfishly, it's a good thing that we've shifted toward that. So that's the third in those. Point four, the classical liberalism and the civilizing process. By classical liberalism, I just mean the enlightenment values that we're all familiar with. Since the time of the enlightenment, we've expanded the idea of liberal values, of treating people as an ends in themselves rather than a means to an end. That's the basis of Kantian ethics. And the first guy to create a data set on this is, well, what Steve Pinker calls the most important person you've never heard of, Norbert Elias, the civilizing process. Elias was a sociologist. So his data set were old manuscripts with woodcuts about what life was like in the Middle Ages and books of manners about what you should not be doing. Don't foul the staircases, corridors, closets, or wall hangings with urine and other filth.  Don't touch your private parts under your clothes. Don't greet someone while they are urinating. Don't make noise when you pass gas. When you share a bed with someone in an inn, don't lie so close to them that you touch them.  Don't spit into the bowl while washing. Don't pick your nose. Anyway, you get the idea. People in the Middle Ages were disgusting. So Elias's data set was showing that. In fact, there's been sort of a trickle down from the aristocrats to the middle classes, the lower classes, that we should stop acting like animals and start acting like civilized people. When you do that, you're less likely to stab the guy with your knife across the table or something like that. In other words, violence starts to decrease as argument was with that increase in civilizing process. And all this leads to the humanitarian revolution and the rights revolutions. So we can see, I'll just do another data dump for you here. These are lynchings from 1860 to 1880, 1960. Hate crimes, murders of blacks, 1996. Unfortunately, the FBI only started keeping track of these data sets in 1996. So we don't have a long data set. But the trend lines are still good.  These are questionnaires, if a black moved in, in the neighborhood, would you move? So forth. Those have all been shifting toward more tolerant responses in the last half century. Discrimination against minorities. So countries with policies favoring ethnic minorities has been going up. And countries that discriminate against ethnic minorities has been going down. Rates of rape, again, these are just FBI statistics that have gotten really good in the last couple of decades, but tracks since 1975 have been going down. Domestic violence has been decreasing. Spousal murder in both directions has been decreasing. US states with corporal punishment has been decreasing. There's still some approval of spanking. Even that has been decreasing, mostly in the Western world, slower in the United States, but getting there. Child abuse has been decreasing. School violence has been decreasing. States that have decriminalized homosexuality from 1791 to 2009, world versus the United States. So we've lagged a little behind, but we're catching up. Anti-gay attitudes. Again, the general social science survey and Gallup, these data sets show that people are becoming more tolerant. And that, again, hate crime, intimidation has been decreasing. This is the data set from the FBI since 1996. Even animals, the interest in hunting has been decreasing. It's still popular in the Midwest, I know. But, and vegetarianism has been increasing. The number of animals harmed in movies has been decreasing. In fact, it's zero now, except for that horse movie, I guess, last year or something like that. But even that, the fact that a horse was killed in a movie makes front page story. That's progress, that's moral progress, right? And then finally, I'll just end with the three chairs for freedom and for science. That is that by science, again, empiricism, logic, reason, open-mindedness, open inquiry, because scientific thinking is more abstract and abstract reasoning expands the evolutionary circle of sentiments. Here I'll put forward an idea of a moral Flynn effect. The Flynn effect is that IQ scores have been going up three points every 10 years for the last half century. James Flynn is a New Zealand psychologist who first discovered this. And it's not on the learning parts of the IQ test, like information, arithmetic, and vocabulary. It's in the abstract reasoning, those tasks where you have to rotate a figure in space like three different times and then pick the one down below that matches what it would look like. We're getting better at that. And that's a form of moral, because morality requires abstract reasoning. You have to rotate yourself in space and become somebody else and imagine what it would feel like if that happened to you and then you can decide what the moral thing to do is. We appear to be getting better at that. And so literacy, and what do we do about it? Literacy, education, public discourse, more abstract reasoning, rising above parochial vantage point, and we're replacing the morality of tribalism, authority, and puritanism with the morality of fairness and universal rules. We've expanded the circle of sentiments, which we're continuing to do. And I'll end with the man who picked up from that Theodore Parker quote, Martin Luther King, Jr. Not in his, I have a dream speech, but in his slightly less famous, how long do we have to go speech? And he said, let us realize that the arc of the moral universe is long, but it bends toward justice. Now he was a preacher, so he's crediting probably sources you and I wouldn't. I think I can actually show, I actually have a whole set of slides. It isn't religion, religion is always lagged behind. They're always just like a decade behind the social wave of moral change. It's the enlightenment values of liberal thinking, of democracy, of expanding the circle of sentiments, other consideration. People are valuable in and of themselves. And it's the whole idea of science as an open-ended, open-minded, liberal tradition of testing ideas and finding out what works. That's the best thing that's happened to us in the last half century. It is science that did it. Thank you. Thank you.


The starting point for this project is the fact that currently there is a huge amount of disruption and innovation in the automotive industry. And one of the key challenges facing automotive manufacturers is suddenly that there's a huge amount of data coming into the car from all sorts of places. This could be environmental data, data about preferences of passengers, data about driver intention. This is one of the tasks that we've been addressing at IBM Research and University College Dublin, namely to build parsing engines that enable us to parse information so that only that information that's really, truly relevant for the vehicle is able to affect the vehicle. The other component that we've built is a root prediction engine, which is always trying to predict the intention of the driver and the intention of the car. This companion is really a guardian angel that sits in the vehicle. It looks after the passengers, it looks after the driver in the car in the context of a particular journey. So the basic idea is that the companion is always there, it's always trying to figure out what the driver intends to do and if it senses risk then it will intervene. It will wake up and it will assist the driver and help the driver to avoid getting into difficult and risky situations. It seems you're going to UCD, Bellfield, is that correct? That's true, yes. You should enter UCD through the northeast gate at Stilorgan Road. Is that okay? Can you explain to me why? Because the UCD internal gates are closed now. Can I suggest the best parking spot to you? That would be nice, yes. You should park at Eastside Visitor Car Park. Okay, thank you.


Here's why you should bench press to build big boobies. We're going to make an argument and talk about how to build chess, why I do it with freeweights, and why all your favorite influencers are straight up wrong. A couple of issues when we talk about building the pecs, the basics work, and for many a reason. Some semantics, but some are truth. One of the bigger overarching theories and things I want you to all think about is whatever your favorite influencer, steroids or not, is doing today is not what they have done for the last 10 years to build the physique of today. How they train chess the last two months has literally zero to do with what your physique looks like today. Right on a cellular level and on just a logical level, it takes years to build tissue into the form you want. One, because it literally just takes time to build muscle. Two, genetically how those muscles look has almost zero to do with the exercise itself. We can build muscle and we can shrink muscle and that's about it. We can't form tissue despite the beautiful philosophy of architecture and molding your physique into what you want. Genetics are going to play an overarching rule. So that not only has to do with muscle bellies, what's more likely to build or not, but also anatomically leverages what works best with what exercise. Just blanket statement saying the bench isn't good for building your pecs is one of the dumbest things in the world. If you look at all the biggest bench pressers in history, they all have huge pecs and they spend 80 to 90% of their time on a flat barbell bench. Sure they'll do some accessories, but it's just not the case. And again, if you look at where your favorite guy sea bum whoever is now versus what they've done the last 10, 5, 20 years, chances are they were bench pressing. And that's what helped build the foundation of what they're at now. A lot of people blame rage or motion or at least the stretch, right? When we're trying to build muscle, we need proximity to failure. Pushing ourselves near failure will recruit more muscle fibers to grow. Two, we want a hard contraction, right? The shortening of the muscle and we want a nice stretch, a lengthening of the muscle. And people blame the bench press for that range of motion, right?  But the main issue is how I see 95% of people doing machines or dumbbells, they're getting the same range of motion, if not less than they would with a bench press because it's an arbitrary space that they're trying to reach. If dumbbells, or if you're too strong and dumbbells are too big, some of these hundreds are so thick, no matter what I do, this dumbbell is going to hit my chest sooner and closer than the handle word with the bench. With the weights being on the outside, I can for sure touch the barbell to my chest. But as you'll see in some of the demos, the weight of the dumbbell will hit my chest before that range of motion is even further.  You can obviously change your angle to get a deeper stretch. And I still am a huge proponent of machines and a bench of inclined dumbbell bench to get a stretch. But how I see y'all doing it, you might as well bench press, handle more weight, have more progression over time, and still you'll get more of a contraction and stretch than the poor, crappy form I see y'all doing on machines. Choosing your exercises, obviously we're looking for some kind of press or two, some kind of fly. That'll cover most of your basics. Which ones, which machines, which exercises, which feel best on your muscles, feel best on your joints, and which you can progressively overload the best. So a barbell is just simply easier to progressively overload because we can move more weight with two hands than we can one.  Now, I don't suggest that everyone does a high arching bench if your number one goal is bodybuilding. But I'm just saying that the slander on bench press is way overdrawn. And all these people are supposedly evidence-based trainers. They can't find me data, calling them all out, that specifically shows a stable surface like a machine or a stable exercise versus a free weight will build more muscle. They're simply just not the data on it. So, this is one of my favorite. I have two pressing days a week. Both start with the bench press. One, because I think it is best for progressive overload. Two, because I want to keep a base level of strength, which I think then transfers to the other exercises I do in push. So, if you're stronger on bench, I'll be able to utilize more musculature, more muscle fibers. When I'm doing dips, when I'm doing dumbbells, when I'm doing machines, hence progressively overloading strength will build more muscle over time. And on my secondary day, I do dips, and then I'll finish off with some flies. The last and final factor is that we're enjoying what we're doing.  But we're focusing on the dumbbell because someone said that it's going to build slightly more pectoral fiber muscles in our eight merger feet mission. It's probably not going to be worth your time. Enjoy what you do. Do it for a very long time. Take it close to failure. Each protein. Take your vitamins. Subscribe to Silo Mike. And maybe you'll have some pecs in time. Ladies and gentlemen, 3sb.co, our biggest Black Friday ever coming soon. So, goodcompanydiscord.com if you want to get involved on the exclusives, the early good dibs. Oh, papa. Oh, papa. Early look and discounts like Mighty Community, Good Company Discord. I'll see y'all in there. I'm in there every single day. New videos every Monday, man. Silo Mike, I appreciate y'all. We over me. Be a part of something bigger than yourself, man. We're out.


He was young and he was tough, a 1920s child and growing up in Texas dust. I have had my down moments and my lonely moments and my scared moments and feeling all alone. I've had, I've worked all my life, I've had a company, a 12-year corporation, I worked very hard and stressed a lot and coming to face my own mortality was the toughest thing I've ever had to do. Like today I might be here, tomorrow I might not be here, I really am not ready to leave my grandbaby, I'm not ready, I'm not ready, I'm not ready, I'm not ready. That part I just got through one day at a time and started improving and I'd go over those walks and I'd eat that healthy food. So those little things and keeping up with my music, I love music, has given me the inspiration to continue on. I'm a spiritual person so I say that God's really helped me out a lot again. Those were rough times, those were tough times. Prior to discovering I had a dissected aorta, I had no medical issues at all. I had a little bit of arthritis, I'd had a baby a long time ago, I actually was very negligent about going to the doctor and I of course changed my course of thinking after I had my surgery and was going to be a survivor, I was going to survive, it just scared me, scared me more than anything and I feel God's got me here for a reason to maybe help others not take the course I took and have to be as sick as I got.  One never thinks it's going to happen to them.  A flying target in the sky, flying high with bombs on board.  I receive emails from the Hart Institute and one day I got an email from Dr. Willerson talking about women's heart Houston and I thought I'm going to go to this meeting and here I did so and here were these precious women in their 30s, in their 40s, 50s, 60s, 70s and I'm taking my mom next week who's 88 talking about each other's health and how they got to where they are, what they're doing to get better and how they keep from being depressed and keep a smile on their face and keep going the next day and the next days. No matter how bad it is, you can get through it, there's always a brighter day tomorrow even if you don't believe it, go to sleep, wake up and there will be a brighter day tomorrow and you're going to find it's really true, it's all okay, I can do this, I can do this and I'm going to get better and I'm going to be still good for my family and my loved ones. He was strong all along, he was strong all along. My dad's song.


Hey, I'm Melissa Kilby and I work in the services security engineering team at Apple. It rolls right off the tongue. When I first started in cybersecurity, my initial focus was on applying statistics, AI, ML, and big data to threat detection. Over time, I realized that there were many gaps in terms of collecting the right data. I then pivoted and started helping develop low-level Linux kernel monitoring tools and deployed them to production to gain first-hand experience of what is realistic and scalable. Earlier this year, I became a core retainer of the Falco project. Today, I will talk about how to use Falco with EBPF for runtime threat detection and more specifically focusing on how to use the right data effectively with more advanced analytics on the host itself, including theories and hands-on demos. Sometimes I'll go deep into details, but I promise I always pull back out and I'll cover various aspects. So hopefully everyone gets something out of it. In case you didn't know, AI, ML is pretty hot right now. And then you look back at cybersecurity and threat detection and you think to yourself, huh, this is why we can't have nice things, mainly because we don't have accurate training data sets. Still, there must be a better way because the modern cloud infrastructure attack surface is vast and the stakes are high. Attackers could gain unauthorized access to secrets and identities and subsequently steal customer data. They could inject malicious code into the running applications. Or worse, attackers can infiltrate and tamper with your built systems. It's not 100% true that SysCalls or kernel events never lie. The main message of the slide is that having a tool that hooks into the Linux kernel at system calls of interest allows us to know what is going on with the running application, including being able to detect if someone attacks the infrastructure for a wide range of attacks. Let's see how it's done in a quick hacking demo. Once upon a time, there was a Jenkins server. You know, there won't be a happy ending. Suppose you found a vulnerability that allows you to get a shell back by exploiting the crew we script console. The Java parent process spawns a child process that creates a base 64 encoded file in the temp directory. Subsequently, this file is being decoded and this attack, it is an elf binary. Next, permissions are changed to make the binary executable. Finally, executing this implant results in sending a shell over the network right to the attacker. Over this reverse shell, the attacker can run post exploitation commands, possibly elevating privileges, stealing secrets, or a pivot further in your network. This demo also introduced the important concept of the Linux process tree that I want to explain in more detail as it's going to be important later. In the animation, you saw how new processes are spawned and now you see all of them displayed together as if we locked all exactly E-system calls over time. However, the Linux kernel defines the process tree in terms of how it looks right now, considering only processes that are alive. Falco mirrors the kernel's view of the process tree and also allows you to traverse the parent process lineage in real time for each incoming event. A little shameless black, this is a really slick feature of Falco. Under the hood, Falco keeps a cache of processes or more precisely of threads. We store a struct for each thread that contains all the properties we're interested in, such as command arcs, the TTY, the executable path, environment variables, the secret that belongs to and many, many more attributes. We purge the entry on exit from the table and because things are never perfect, unfortunately, there will be broken links sometimes, partially because of tooling limitations, but also because of edge cases in a Linux kernel that are harder to keep track of. Looking back at what Falco can detect today, the quick hacking demo already introduced remote code execution RCE. RCEs are very critical because they effectively open the door to attackers to do more damage to the infrastructure, such as lifting application secrets from disk, local privilege escalation, gaining higher Linux capabilities, eventually escaping the Kubernetes pod sandbox, pivoting through your network and generally speaking, unauthorized access. That's a lot of things we can detect today with the right Falco rules. The only downside is that you need to know what to look for. Do you feel that light breeze let you step out the door here in Chicago this morning? Despite our constant progress in making cloud native security better every day, threat actors are outpacing our innovation, constantly finding new ways to turn NATO past our achievements. What does doing nothing cost you? It could be everything, multiplying a lot of things that are done right by zero is still a zero. What we can do, however, is constantly raise the bar and slow attackers down. Some of the current primary pain points include the challenges with suppressing noise. This rule shows that for Falco alerts that monitor a file opens, you need to limit the scope of the rule to subdirectories or file naming patterns that you know beforehand. Depending on your environment, you may also need to add many exclusions. Unfortunately, this traditional approach puts you at risk of missing out for an entire family of attacks, namely arbitrary file reads. As the name suggests for this, you need to be able to write rules against any file. Sounds crazy? Let's do it. I compiled a test binary that contains the new algorithm I have yet to introduce. In the left terminal, you will see the Falco alert outputs. Suppose we're alerting on any file open because I want to show you how it looks like when you try to monitor all file opens. Most likely you will get a lot of events that happen all the time. Let's run the same test binary again with the new automatic filtering capabilities and very quickly, we're suppressing the obvious noise. With a feature like this, we could alert on potential application secrets lifting, even if we don't know what they're naming conventions. Therefore, implementing frequency counting of Linux kernel events will be useful for security to build future anomaly detection. It can be a first step to what's shifting the information symmetry in favor of defenders. In theory, we are the ones who have access to all data, so we should take advantage of our ability to learn applications normal behavior. I must admit it's not gonna be exactly that easy. For example, what about memory attacks? Cisco's related to memory or IO are so high frequency compared to even file opens that on busy servers it will be very difficult to process all events in real time without either a massive performance set or starting to chop events. Therefore, just keep in mind that much more engineering work at multiple layers is required to expand monitoring capabilities in this regard. However, the arbitrary file re-demonstration showed how accessing and encoding all the rich information readily available on the host can be a game changer. Because it's one example use case you definitely cannot solve of host in a data lake compute environment. In summary, rule-based detections focus on what we think attackers will do, not on what they are doing. Attackers simply don't play by the rules. They do the opposite, which is why saying ahead in Linux runtime monitoring is so hard. Having data rules and monitoring in place for known attacks is a great baseline, but it's often not enough. This approach is also very time and engineering consuming. So why not stop playing by the rules ourselves and speed up novelty discovery and adaptation? Using mathematical models to determine a pattern of past behavior has the added advantage that even if an attacker knows about it, it will be much harder to plant in and bypass such monitoring. As a result, we may be able to slow them down and drive up the operational costs of their attacks. Switching gears, everything I'm presenting now, including the first early prototype demo from before, is a work in progress for Falco. Let's dive into the frequency counting approach we could use in Falco and real world production to solve some of the challenges I just presented. The background image already sets the stage. Mathematical approaches always involve matrices or tensors in one way or another. By the way, The Matrix is one of my favorite movies. The question for you now is, do you take the blue pill or do you take the red pill? Just kidding, follow me. We're about to enter The Matrix. The North Star is to derive a smart mapping of endpoint processes to Euclidean space such that similar events are close by in that space and unusual or abnormal patterns stand out enabling us to monitor and analyze any behavior outside of past behavior in a more abstract and generic way. In simpler terms, we are talking about data compression. For Falco, we have some interesting requirements. The rate of kernel events on real servers is so high that performance must be prioritized over accuracy while still providing the value you need. We need to achieve frequency counting of large data streams in sublinear space using constant time complexity. I believe in using established algorithms. Furthermore, we need to be able to deal with different data types and create a versatile solution that can be applied to our special field of cybersecurity. As a first step, I proposed to use countment sketch which was invented 20 years ago, an algorithm for probabilistic frequency counting of buckets. I will introduce the base algorithm in the next slides skipping all the variants that exist by now. A countment sketch is a two-dimensional array with d rows and w counters each. The rows will be d independent hash functions. They should be non-cryptographic. 64-bit should be fine. They should perform well at run speed. And have, for example, favorable avalanche properties, meaning slight changes in the input do not result in large changes in the output. The number of buckets is much smaller than the universe of possible values. Hence, this is why it's called data compression. The way to shape the dimensions is providing failure and error tolerance rates. Values are probably going to be something like 0.001. For example, you could end up with seven hash functions and 27,000 buckets. Assuming 64-bit counters, the sketch would be 1.5 megabytes. When we receive a new value, we loop through the hash functions, compute the hash value, and take the modular to the number of buckets w to get the vector index. We then increment the counter-added index. To get the current count estimate, follow the same steps. But instead of incrementing the counter, only look up the counts and return the minimum value across rows. Taking the minimum count from multiple hash functions is the trick that makes this algorithm more robust. Often, the goal is to maintain a cache of the top K heavy hitters. For Falka, I think all that is needed is to make the count estimates available to the rules expression language. Countment sketches are prone to overcounting, but they never undercount. In Linux runtime application behavior, we have heavily skewed distributions, therefore having an algorithm that performs well and determining high-frequency counts adds a lot of value to threat detection. Of course, countment sketch will not automatically find and be able to tag an anomaly that is malicious, but that is not the goal. We want to automatically remove all irrelevant data so that we can be more adventurous and broader in our monitoring scope using normal Falka rules. The key takeaways are that unlike hash tables, we use less and fixed memory to kind of achieve the same results as overcounting will be within an acceptable error. The biggest win will be the safety boundary for Falka rules that could blow up in production but now won't anymore. Lastly, dear SREs, we want to make you happy, so this is for you and for my own peace of mind. I thought a lot about this next step. How many sketches per running Falka do we need is one enough? Probably not. Initially, I believed that we should have separate sketches for each container since it seemed logical to treat each container in isolation. But over time, I remembered that this is what people commonly do in data modeling at first only to realize that it is not as maintainable or as convenient as having more generalized models. For example, Netflix first had separate movie recommendation models for each country but later collapsed them into a single global model. Therefore, I think we should use shared sketches across containers, making them larger instead. That being said, I think there should be separate sketches for the values we're counting. Okay, what are we actually counting? The big leading question is what defines the context of a Linux process in the best and most robust manner or how to do counting in a way that matters and results in actionable information for threat detection? I believe this is why advanced modeling is so challenging and why we probably have fewer breakthroughs yet compared to other domains because you still need a lot of domain expertise and sure enough, you're fighting against attackers who will definitely use any loophole they can possibly find. The short answer is that there is no single combination of signals that will work for all use cases. Instead, you need to encode your data in different ways and slice and dice them a little bit. This is why I propose using multiple sketches. Your first sketch could use the container ID process name TTY to encode interactive activity, the executable path plus parent process lineage, plus names of the process group and session leaders to count how often we have seen the same shape and form of process origins before. You would string concatenate all these properties together and then hash them. To find the vector index, the bucket whose count you would increase as explained in the previous slides. Your second sketch could encode the same signals as the first, plus the file descriptor names, which is the file name for open related syscalls for the use case of abnormal file opens. Later in your file code rule, it may make sense to look at both of these counts for the cases where, for example, the file name may contain random timestamps. In that case, the process context alone may help to still show that this is normal and recurring activity. Next, let's take a look at the process command line or proc arcs for that matter. You could encode in your third sketch. This is where it gets really interesting. Many folks coming into the domain of cybersecurity from other domains attempt to treat the command arcs as English sentences, and then try to train models on them. However, there are inherent challenges. First, often there are no command arcs. Second, the more arcs you have, the more information you have to work with. Think of the good old information theory invented by Claude Shannon in the 1940s. And it's true, some attacks may inject a payload over the command arcs. Really though, this is just a subset of attacks. Command arcs can also be problematic, just like file names. For example, Java processes often have many arcs. Some of them are random looking. This may trick you into thinking that this is new behavior when in reality it is not. So yes, we do want to use the command arcs because they can be very useful for finding normal heavy hitter app behavior, but sometimes it might fail miserably. What I'm about to show is non-animal experts, but to some of you it may come as a surprise that what you type into your terminal as command is not necessarily what comes out as process command line arguments when auditing the kernel via tapping fork and exact syscalls. On the left, you have the full context. This is what I would type into my terminal. This is an input to my shell process. On the right, you have what would be logged as arcs in exactly these syscalls. As you will see, they're pretty different. That's because the left is a full programming language that is being passed and evaluated by the shell, which does its own processing that results in the actual fork and finally the exact syscalls that you will see logged on the right. On the left, you have a program that executes bash and tells the shell to open a TCP socket to the provided IP and who bashed standard in, standard out to the socket. On the right, you see that all of the TCP setup is missed. The next two lines on the left are programs that invoke shell built-ins like echo and read. These are implemented by the shell itself, so no external program is needed. As such, no external exact syscalls are made that would allow us to see these critical intermediary steps. In addition to built-ins, the shell evaluates environment variables and pushes them into the child's process environment map before executing the command. As such, hooking exact VE will only see the occur command being run. Both examples are wonderful examples while you need to be more sophisticated and tapping into the right kernel signals. Logging only open or logging open syscalls or using LSM hooks for that matter and logging environment variables will make that information still available. Finally, for pipeline commands, the shell is going to create a number of pipes in memory four or a few times and exact each command individually with the input output file descriptors pointing to these pipes. Looking just at process listings, we cannot tell which commands are hooked up to which other commands, so we lose a lot of semantic understanding as to what the sequence of commands is doing. To complicate matters further, if you simply run a script, we do not look into the file itself. Therefore, looking at command arcs is more interesting for a command injection attacks. By the way, to spot new executables and containers that should be immutable, it is better to use very precise kernel signals that Falco features. For example, Falco can detect if something was written to the upper container file system layer at runtime. In summary, the terrain completeness of shell inputs and other aspects of Linux makes advanced data analytics for cybersecurity so hard. It's not that algorithms don't work, it's that security still requires a lot of domain expertise to use them effectively. The statement extends to the decision of when to use modeling approaches versus when to better invest into super robust kernel signals like the methods I mentioned for detecting new executables. Here, I would like to reiterate that I think the frequency counting proposed is best used in combination with additional Falco rules filter expressions. So don't try something like this in production, but remember what I showed in my first demo? It's still crazy that we can now potentially detect any abnormal file opens without needing to know the file naming conventions for custom application secrets. It's now time for another demo. Again, on the left, you will see the Falco alert outputs and similarly to the first demo. I will show again how heavy hitters can make monitoring and data collection more risky. The container and the background cats at sea shadow all the time. Now running the same test binary with counterman sketch powered filter expressions will quickly perform probabilistic frequency counting and silence the noisy output. When I interactively drop into the container and cat at sea shadow again, almost doing the same thing, we still catch it because the string we hash contained the TTY, which indicates interactive activity. We see the same effects if I now run some dummy command that mimics random command injection against the vulnerable application, for example. I may be biased, but I think that's pretty cool and can be a game changer in production. Here are a few recommendations for how I tend to go about contributing more significant paradigm shifts to the open source Falco project. Working in the open, showing early proof of concepts as I'm doing today is very important to avoid being that isolated monkey hanging off the furthest tree branch just to see if you fall. The other maintainers have been around to block, so you would be foolish not to take advantage of their inputs to ensure that this solution is not only useful, but also maintainable in the long term. The early release phase is very interesting because now you have to ensure that the software is user-friendly and that you help newcomers to the field learn how to use the new capability. In addition, the framework should be extensible so that other contributors can expand it and improve its analytics capabilities over time. If accepted as a stable feature, the community will have deemed it useful and feasible for real-world production and more investment will be made in the future. In this talk, we have discussed how learning, velocity, scalability, and cost can be improved in security. By learning the normal high-frequency behavior of applications and accessing more information on the host, we can increase the chances of detecting unknown attacks. This is important because traditional security approaches are often unable to detect novel attacks. A big explanation mark here, we still need human domain expertise. We can now adapt to changes in application behavior and detect new attacks more quickly. Then traditional solutions. They can also scale to meet the needs of large and complex environments. We can reduce the cost of security by avoiding the need to manually tune and maintain traditional solutions. Additionally, they can help to reduce the cost of data storage and processing by avoiding the need to send all security data to a data lake for analysis. Overall, learning-based security solutions offer a number of advantages over traditional solutions. Okay, thank you for having me here. And I thought I would be going close to the end of the presentation, but it seems like I do have some time for some questions. Do we have a microphone? Okay. Outside of the detection, do you have any remediation options with that, too? Is it just mostly just detecting? Yeah, so this talk was only about detections on the host itself. There probably would be many other talks about how you would go about similar algorithms or procedures in a data lake compute environment or, as you said, for incident response or for other aspects of security. So again, this was only focused on do more advanced data analytics on the host itself because you can tap into data that otherwise you could not. This is why I was highlighting the file open example because it would be crazy to send off all open syscalls of the host. You basically cannot do it. Okay, no more questions? There is one more. Hi, yeah, I had a, wow, that's loud. A quick question on, basically, what you're doing effectively is anomaly detection because you're learning some amount of the normal behavior and then pulling out the anomalies. The question I have is how that scales because when you get, when I think of anomaly detection at Apple scale or Google scale or something, there's so many events happening that anomalies happen all the time and so you still end up flooding the team with alerts. So how do you handle that?  That's the kind of essence of scalability challenges. Correct, I totally agree with you. This is why I recommended to not use the simple accountment sketch filtering while monitoring all file open. So definitely don't do this. And I believe the first next step would be to use these probabilistic counts to, for example, if you look at the upstream file code rules, there's one for sensitive files and that's also the one I showed here. But it only looks at a subset of the Etsy directory. So maybe with this probabilistic counting, you could expand your monitoring to all of the Etsy directory. So I believe in going to small steps and see how it works in production, I would never turn this on for all file opens. And to your point of, there's always going to be anomalies, yes, common entire patterns or SIEs doing ad hoc debugging. People maybe being more new to Kubernetes, they don't know how it works yet. And they also do a lot of interesting debugging. And as you said, at a large company, at a large scale, there will always be a lot of data coming in. But I also believe it's not a problem to over-collect a little bit and capture some more data. And I think the main message of this talk is that you don't have to log all of the exact VE system calls. You don't have to log all of the network system calls or file opens to be able to do very comprehensive forensics, for example. So again, it's really about that you can be more adventurous in your file code rules and expand your logging without plowing up your data lake and production at the same time. I think we have one more question right here. Okay. So you talked about monitoring system calls in particularly file descriptors. But what if more system activity or host activity is added? Wouldn't that lead to more unique events, so to speak? So let's say network calls are, you know, just pairing it up with other activity on the system and wouldn't that lead to more alerts in general? So is it just if we are monitoring one type of system calls or is it possible to scale all into every attribute of a process, let's say? Oh, so I mean, since I'm presenting here about Falco, Falco can hook into, I think by now it's over 300 system calls. The way it works in a kernel, we hook into the system call enter and exit events and you can create your custom rules and monitor any system call you want. In addition to that, you have more options in the kernel like Linux security module hooks or another option to, for example, monitor file opens, there's added benefits to it. And I didn't quite get the other part of the question. I mean, basically it detects one common pattern, right? And then that way it's able to reduce the alerts. But if we add more monitoring, wouldn't that lead to more unique scenarios or cases leading to more alerts, so to speak? Okay, yeah, I bet. So this is why I always recommend to be very conservative in production and first try one little thing and then go from there.  Sometimes what can happen is that it works well for months and then it totally blows up. So I would really like to stress that the biggest advantage of this will be the safety boundary, that these super heavy hitters, you can just automatically tune. And in addition to doing this manually, it's a lot of engineering time and effort. So I would be, since I deployed to a very large environment, there's gonna be more time left for me to work on these features and I constantly tune the rules. So pretty new Falco here. If you could tell me, maybe using a tool like S Trace that's a lot more lightweight versus, what's the advantage that Falco brings and is there any overhead added or if you could go a little bit into that.  My favorite part of Falco is the rules expression language. It's very powerful to really tell Falco what to monitor on the host. And in combination with that one, I think we can really shift the information asymmetry just a little bit. Cool, thank you so much. Melissa, do we have time for one more? That's 38 seconds left. Okay, this is our last question. Real quick, does Falco have any way of mapping processes to the pods that are running that process so that if a pod moves to a different host, you can maybe track that behavior? Okay, so track when it moves to a different host. That's an interesting question, but yes, we do hook into the container runtime socket and we fetch all the common Kubernetes and container information such as container name tag and also name space and pod name. And by the way, we're currently reworking the K8 client to tap even into more Kubernetes fields. Okay, we're down to zero seconds. Thank you.


Hi, my name is Dan Whaley and I'm the founder of the Hypothesis Project. Thank you for the opportunity to apply for the May 2013 Fellowship. In 1945, Vannevar Bush wrote a famous article in The Atlantic entitled As We May Think. In it, he outlines the concept of a web browser, which he called a memex machine, that would enable people to blaze trails through the world's knowledge, creating links and associations and notes that others would be able to follow. Headingly, in 1993, Mark Andreessen built a collaborative annotation capability into the very first version of NCSA's Mosaic browser, which he subsequently turned off when he realized the scale of the service he'd have to run to support it. Since the Talmud first brought rabbis together to annotate their shared oral history over a thousand years ago, scholars, schoolteachers, and ordinary citizens have been writing in margins and sharing their thoughts with each other. We now finally have the infrastructure to bring that capability and with it the dreams of those pioneers before us to the sum of all knowledge. It's clear to me that we are at the beginning of an extraordinary transformation in our thinking, in our culture, and in our relationship with each other and with the planet we call home, a modern renaissance that promises to change nearly everything we know about life. It also seems obvious that this transformation is essential for our sustainability as a species. The seeds of this change have already arrived, principle among them, the internet, and the global shift in consciousness and power that it is already creating. But we need more, some core infrastructure, to catalyze the rest of what's possible. At Hypothesis, our vision is an open source, non-profit organization that will build technology and with it provide a service to crowdsource the world's best analysis, insights, and references on top of information everywhere. Exactly the idea of trailblazing that Vannevar first imagined nearly 70 years ago. Our goal is a revolution in how we derive knowledge from information, how we know what's credible in the world around us, and ultimately how we collectively make decisions about our future. Not as dictated by a top-down editorial bureaucracy, but as organically derived via collaborative peer review over time. We've brought together some of the leading minds in language, rhetoric, reputation, distributed systems, and internet technologies to help build an open source platform using emerging standards for annotation, together with an innovative reputation model and permanent data storage at the Internet Archive. We've partnered with the Open Knowledge Foundation and have assumed primary stewardship and development over their annotator project. In that foundation, we are implementing a new capability to surface annotations from potentially thousands of individuals or more on the same documents in a beautiful and elegant user interface. In addition, we're also now beginning implementation of the distributed peer review capability that will ensure that high-quality voices rise to the top. Others have tried elements of this before. In fact, we've counted over 50 different efforts over the last 15 years. Essentially, all have failed. We took a year and interviewed many of those involved in previous projects. Our research led us to key conclusions about why these efforts didn't achieve their potential. Among them, that they failed to implement an effective reputation model, that they didn't use an inline approach to annotation, that they weren't open source and weren't nonprofit, that they paid little or no attention to partnerships or standards, and that they didn't focus enough on the cold start. We're not just building technology, we also have to nurture the seeds of a global community of thoughtful contributors around the world's most important documents and important issues. Hypothesis has been conceived both technically and organizationally to address those issues. Our goal is to implement a global channel for collaboration around any content, to be open source, nonprofit and transparent, with strong protections for privacy and a lack of political or ideological bias. In the years since I first applied for the fellowship, we've gotten a lot done. We built a functional prototype of the annotation system, and thanks to the Sloan Foundation we brought together over 50 of the world's leaders in reputation design at San Francisco for a three-day workshop to help us design our peer review model. We've also partnered with the Open Knowledge Foundation, the Internet Archive, and have joined the Open Standards process, which has now become a W3C community working group. We've also raised over $750,000. The Open Knowledge Society you've articulated resonates strongly with my vision of a wiser world, both one that has a perspective and the capability to make decisions rationally and to plan thoughtfully for its future. It's the reason I started Hypothesis. It's clear that you believe that profound positive changes in our society are possible at the time when we most need them. It would be my honor to join such a fellowship. Thank you for your time. This moment is here at hand. We now have the means, I think, for everybody on the planet to know as much as he or she wants to about anything. But the way in which that's done has to be done on the basis of an evolving authority, an evolving set of connections, perceptions, views, and editorial processes that you folks are thinking deeply about, and not enough other people are. When we talk about moving the web forward and communication on the web forward, what we don't want to do is create another walled garden community. What we want to do is publish in ways that are accessible to everybody who wants to get on that bandwagon. That's what brings us to be involved in a W3C community group, to define an annotation standard for data exchange. And that's what makes our story really compelling to me vis-a-vis any number of startups doing some kind of web clipping sort of project. To me, I don't want to be sharing little snippets. I want to be sharing real references to real web content with URLs. That's the decentralization of the web that Tim Berners-Lee imagined when he set out to build it, and I think that's the direction that we should be going.


The federal government has approved the Ministry of Petroleum Resources' request for the NNPC Limited to execute a memorandum of understanding with ECHO as for the construction of the Nigerian Morocco Gas Pipeline. Minister of State for Petroleum Resources to Mipri Silver announced this as part of the resolutions reached today at the Federal Executive Council meeting. This gas line will take gas to 15 West African countries and to Morocco and through Morocco to Spain and to Europe. Sorry. Yeah? Twenty-twenty-three elections are drawing attention from all end sundry, but that is not putting governance on hold. The Federal Executive Council has decided to set up a special team to look at the sectors of the economy that are not growing and also to look at how to grow the other sectors better. This follows the review of the report from the Ministry of Finance, Budget and National Planning for the first quarter of 2022 GDP report. The report shows that the Nigerian economy has grown by 3.1 percent in the first quarter of 2022, which shows a gradual economic stability from the recession witnessed in 2020. Meanwhile, the Executive Council has now approved for the Nigerian police trust fund to award different developmental contracts with a total sum of 8.315 billionaires. This project aimed at improving the efficiency of the Nigerian police. Also, the Council approved the supply and installation of an emergency restoration system for 230 KVA and 132 KVA transmission lines for ongoing rehabilitation works in Lagos at the sum of 968,000 dollars.


The U.S. Navy's four-deployed aircraft carrier, USS George Washington, welcomed the board carrier Air Wing 5 one day into its 2013 patrol. It's been a little while, so it was awesome, it was a rush, yeah, safe and predictable first time, that's what you're looking for and I didn't scare myself. Through hard work and determination, the Air Wing's more than 60 aircraft from nine squadrons safely flew on over a two-day period. I think we both play an important role when it comes to what we have to do out here as far as operations. For USS George Washington, I'm Petty Officer, Brian Abel.


Deep sleep staging networks have achieved high accuracy on large-scale data sets, however they struggle when trained and tested on smaller data sets due to data inefficiency. To address this issue, researchers have explored transfer learning approaches whereby models trained on larger data sets can be adapted for use on smaller data sets. This paper proposes a new method called domain statistics alignment, DSA, to bridge the gap between the data distributions of different data sets. DSA modulates the domain-specific statistics of deep features stored in the batch normalization, BN, layers of the source model, allowing it to be adapted to the target data set. Additionally, the authors extend DSA with cross-domain statistics alignment, CSA, to allow the model to adapt more efficiently to the target data set. Finally, the authors evaluate their methods on two state-of-the-art deep sleep staging networks, DeepSleepNet and UTIME, and demonstrate improved performance on target data sets compared to other transfer learning methods. This article was authored by Jiahao Fan, Hanyu Zhu, Sinyu Jiang, and others. We are article.tv, links in the description below.