Add this nice little construction where we had our two points that we started with, and we had an interval. And we called this guy some some LAB. So there's a line segment from A to B. And we called this particular guy S naught. And then what we did right was that we start making new examples by coming out to a Saucerly's triangles, boop, boop, boop, boop, moving out some some epsilon times the length in this direction. And continuing this process so forth and so on to get our S's. So as we had written up before, our Si, which was supposed to be a union of Li j L ai j plus 1, a piecewise linear guys. And what we did was we let Si plus 1 equal the union of L epsilon, which was exactly what this thing here was. We applied each line segment of the ai j's ai j plus 1s to get our piecewise linear guys. And what we said was we got this nice sort of Reifenberg curve in the end that was bi-holder. And we sort of outlined where the bi-holder construction was going to come from. So two points on this. One is that as was pointed out by several of you, that's not Reifenberg. It's a one line fix. So what I did wrong was the following. So the way I described it is I said, OK, let's push this out. And then let's push out again. And push out again. And keep pushing out like this. And of course, that's silly because after like just stare at this point, what you're going to have is an angle that looks like that after a fine number of steps. And clearly, that's not Reifenberg. What you have to do is alternate. You can always go out this way or go out that way. And you have to alternate. So what you need to do for step two, for instance, is that should actually look like this. And then this guy for step three will be something like this. That was down. Dump, dump, dump, dump, and so forth and so on. I mean, it's 10 lines to check that fixes it, but it's one line to fix it. So what you should really do is view this as the following, i plus j times epsilon. So if it's negative, that means you move in the non-oriented direction. And what happens when you do it like this is that the angles will still move in every switch direction as they have to. But they'll be continuous with respect to one another. So when you fix at one point, it'll still look like a line on a scale, so it'll have the Reifenberg condition. And every other computation we did is absolutely verbatim. I mean, that actually didn't depend on this, just that one condition. So yeah, you've got to alternate. We will come back to this example. I think the way I'm going to do this is the following. So I actually want to understand the bi-holder a little better for this example. In fact, I want to do it way different than the way I outlined before, because it's more motivating of how Reifenberg will work. But lecture four is dedicated to the proof of the next structure theorem, which as I said, the proof of the classical Reifenberg is set up to mimic this. So I'm going to come back to this example in lecture four and do it more carefully at the beginning of that. And for now, we'll just move on and recall this as being a nice Reifenberg example that showed the sharpness of everything. So what I'm going to do today, then, is the following. I want to talk about a more general Reifenberg theorem, something for measures to deal with a few issues. And we're going to basically build a lot of background to try to understand this. I think I'm going to leave this here in that board blanks. I am going to come back to a slight refinement to this example in a moment. So the idea is what? The Reifenberg was knee, right? So it said that if we had a set and we could approximate it by affine planes in all scales, then it had to be bi-holder to a manifold. And this is pretty interesting. In practice, when we want to apply these things to singular sets, it doesn't work like that. It's not quite so clean. So there's a variety of issues that appear if you're trying to use the classical Reifenberg. And let me list them for you. So the first issue, so one of these is not such a big deal. The other two are bigger deals. So the Hausdorff distance, I'm not going to write every line. So Hausdorff distance used in the definition is like an L-infinity bound. And as happens in PDEs, you don't have L-infinity bounds. You have LP bounds of some sort or another. In particular, for most of the equations, this is an applied to so far. It's more like L2 pounds or integral bounds. So in practice, we want an integral bound on things. Integral. So this is going to be not horrible to fix. So what we're going to end up doing at some point in this lecture is introducing something called the Jones beta number, which is to fix this, the main point that one really wants to think through is that you're not applying it to sets anymore. Where L-infinity makes sense, you're going to apply it to measures. So we need to move to the measure world. And when you move to the measure world, it's now open that you have things besides L-infinity of other LP estimates. And this is what the Jones beta numbers are. And we'll introduce those and work with those probably for half this lecture. I mean, this is what we want to get a little bit of a feel for. Second problem. In applications, our sets or our measures, which are supposed to be like singular sets of things in practice, the measures have holes. Actually, more to the point, they simply don't satisfy the Reifenberg condition. Which is to say, it's not a question of holes or not holes, you just don't have a Reifenberg condition. So that might sound like a deal breaker. But what happens is basically the following, that this is where the notion of a neck region is going to come into play and the notion of a neck decomposition. A general measure is a general measure. But we will break it into pieces where it turns out if we have some sort of integrable control, even if it's some large number, on our beta numbers, it turns out that most pieces, there are a lot most, but at least there will be lots of balls for which it will have sort of a weak version of the Reifenberg condition. So on the whole, it may not be true, but we can at least focus on so-called neck regions where we have sort of a weak version of this to actually work with. So we'll need neck regions to deal with this. And the neck decomposition theorem, which the decomposition is basically saying most regions either are neck regions or at least have some other bounds that are useful. And the third point, and this is also a deal breaker, by holders too weak. So in practice, right, when we're studying things, say singular sets of nonlinear equations, we want two things. We want manifold structures, rectifiable structures, which I also defined for you today, which are like bi-elliptic manifold structures. And we want volume bounds on the singular sets. We want to know the singular sets on too big. And bi-holder doesn't do this, right? Bi-holder's all kinds of crazy. We need control ingredients to do this. So what we need essentially is a stronger condition to get a stronger result because we know Reifenberg doesn't do this.  I just don't like leaving that up there. It bugs me. Let's fix that. We should stare at something pretty. And let's say boop, boop, boop. Okay. So let's look at the same example where we keep taking our piecewise linear guys and breaking it up into more piecewise linear guys, but let's do something else. On top of this, right, so how do we get from our S0 to our S1? We went up by epsilon, right? So to go up from here, we went up by epsilon. Well, instead, what we could do actually is move up by a different amount on each, right? There's no reason not to. It's a perfectly interesting thing to study. So we can move up by some epsilon not here, whatever that is. We can move up by some epsilon one here, whatever that is. And in general, we can move up by some epsilon i plus one, whatever this is here. So it's the exact same construction.  I'm interested in small in that big here. But we could, if we wanted to actually move out by less and less. And now what happens when we do this? So recall our computation from yesterday, which was simply that if we want to know how the length changed, right, then the length of Si plus one, well, we got to it by saying it was the square root of one plus epsilon squared times the length of Si. This is just because we do our nice little Pythagorean theorem here. And now, of course, if we're moving out by a different amount at each stage, it's gonna be more like, I think this is like an i the way this is written, but whatever. It's gonna be one plus epsilon i squared. Now, for curves, right, by elliptic structure, gradient structure, and volume are all the same, right? So life's very easy. So what we're really asking here, right, the problem was that the volume of this thing for a constant epsilon was going to infinity, right? So that meant in principle that our actual volume was four times the product of the square roots of one plus epsilon i squared. And that clearly just goes to infinity if these are all epsilons. But now one can ask the question, well, when does it not go to infinity? And you get a pretty clear answer from this, right? And the answer is pretty interesting because the square root of one plus epsilon squared, let me just sort of fake it out a little bit here. This is, roughly speaking, four times the product of one plus epsilon i squared, right?  And this here is gonna be finite, right? If and only if the sum of epsilon i squared is finite.  It's finite if and only if that sum of epsilon i squared is finite. What that's telling you is that if I actually want a rectifiable curve here, an actual curve of finite length, then what I am stuck with here is that not only do these epsilon i's have to be going to zero, but that's not enough. They have to be going to zero sufficiently fast that their squares are summable. The fact that there's a square here is really good and really bad. So it's much better than it being epsilon i. And the fact that the square lets you get away for nonlinear equations. It turns out that square, it's precisely what you can control for some nonlinear equations. No better, no worse. If that was any other constant, you'd be in bad water. Let me point out that this sort of moral from this example was refined by DeVito and Toro into a theorem that said if you had a Reifenberg set for which on each scale write your epsilon i, Reifenberg, with it being summable at each point and bounded, you actually do in fact have a rectifiable curve at the end. Okay, good. So now that we have some motivation of where we're heading, we need that and that. So let's start with the following. I'm going to crash course you on content. So when you are doing, well, this or any type of quantitative analysis or PDs that nowadays, you wanna talk about sizes of sets, of course. And there's more than one notion of a size of a set. And what notion you deal with actually is quite important. And the three notions here I'm gonna talk about are Hausdorff and Minkowski and packing content. Now they're extremely similar. Let me just give you the definition so we can get some feel for what's happening here. This will make a difference when we start getting really careful about all of our analysis. So I'm taking a side route now so we're totally changing topics. Definition. This is of content. So let's take a set. Doesn't need to be closed. It can be whatever you want, some set. And R positive, both of these are fixed. Then the K-dimensional Hausdorff R content. That's a lot of words. I'll write the first one out. K-dimensional Hausdorff content of this set is the following. It's, well, we denote it by HK sub R of S, right? And it's defined to be the imp over the following. Essentially, we're gonna look at the imp of all coverings of S by balls of radius at most R and sum up their volumes, their K-dimensional volumes. So WK, R, I to the K, such that S is contained in the union of the ball of radius R I or X I. And R here, R I's all have to be less than or equal to R in our assumption, right? So I'm saying, let's draw a picture.  It has to be covered, they can't be bigger than R. And then I sum up the K-dimensional volumes of these things to figure out how big you are. The K-dimensional Minkowski R content is the following. So with an M, so this is, and we can write this two ways, actually. It's R to the K minus N times the volume of the ball of radius R around S. Equivalently up to a constant, right? That this is the imp over the sums of the K-dimensional volumes of balls of radius R. The R I are not allowed to vary anymore, such that S is contained inside the union of the balls of radius R of XI, right? So for Hallis-Dorf, I can get any covering I want. For Minkowski, I have to cover by balls of radius R, right? So it should be clear, this guy here should be bigger than this in principle, right? I'm very much restricting the amount of covers I have here. They all have to have the same size to them. And three, the packing content of a set, if you want the R packing content, but actually in practice, I don't care about the R so much, is actually I'm gonna make this a soup now of the sum of omega K R I to the K such that the balls of radius R I are on XI or disjoints. So I'll explain this, and XI is an S. So when you soup out something like this, basically a Vitaliy argument tells you the balls of five times that radius cover it, right? So what's happening here is that here I'm covering by balls of any radius and saying if I can find some covering for which this is finite, then I have control. This is saying if that covering is by balls of the same radius, then I have control. And this is saying I have to be able to cover it by absolutely anything and I have control, right? So packing content insists that not only is there some covering which is control, but every covering of it is controlled, yeah. Yes, thank you. They're all constrained, yeah, they're constrained to be a most R. Thank you, exactly, thank you. I am running out of room. If you have my notes, this is written verbatim. I'll try to write bigger after this, sorry, I was getting squished. Okay, so classically speaking, people control this, house dwarf measure. This turns out to stink for lots of reasons. Sometimes it's all that's true, mind you, but it stinks. Right, let's just look at one example to understand why. In particular, if you're doing anything quantitative, if you're solving PDEs and trying to get estimates, this is a horrible thing to control. And let's just do one example to see this. And in the problem session, your TA will work out a series of examples a little bit better. You have an exercise on this, which I've written incorrectly, so he's gonna fix it and then solve it. So let's let S be the rationals inside the ball of radius one. Then for any R, what do we know? The key dimensional house dwarf, our content of this set S, well, I mean, I don't know exactly what it is, but it goes to zero as R goes to zero. This is basically set up for any K, sorry, positive, strictly bigger than zero. So if K here is bigger than zero, then the K dimensional R content goes to zero, right? Whereas if K is zero, well, it's actually just gonna go to infinity. So what this means here is that this is zero dimensional from a house dwarf point of view. That's exactly what this statement is here, in fact. So roughly speaking, how do you see this? Just to give an idea. This is a countable set, right? So what I can do is enumerate it in some way, pick the radius R, let the first element be covered by a ball of radius R, the second element be covered by the ball of radius one half R, then one fourth R, then one eighth R, so forth and so on. And in fact, I think we just proved that's like two R. So this is, well, bounded by two R anyway, is what we just proved. So countable sets are very well behaved from the house dwarf point of view, right?  Now, why is that awful if you're doing analysis? Well, if you're doing quantitative analysis, the closure of this set is the entire ball. It's everything.  I mean, if you're trying to push away from this set, it may be smaller dimensional sense, but it's a big set in the sense that you can never get away from it, right? It's dense inside the ball of radius one. And one sees this directly through the Minkowski and packing content, right? So if we look at the Minkowski, and this turns out to be roughly equivalent to the packing content of this thing. Then in fact, this is just covering all of them by balls of radius R, right? Which means you've now just covered the entire ball of radius one by balls of radius R. So all you're getting here is that's roughly equal to R to the K minus N. So in particular, if K is less than N, it goes to infinity, right? And it's only bounded if K equals N. So from a Hausdorff point of view, this is a zero dimensional set. From a Minkowski and packing point of view, it's an indimensional set, right? And actually, we like that, right? Because if we can control sets in a Minkowski or packing way, which will be very important in what we're saying later on, we're really doing a much better job of controlling our set. All right, so this is, let me point out actually in words why you're gonna care about packing estimates in a minute. So the end results will prove packing estimates on things, not just Hausdorff. We will directly use that in a corollary because what a packing estimate gives that that other estimates don't, right? Is that imagine you have some set, right? You're trying to control the set. So maybe the first thing you've done is prove some sort of control, Hausdorff control or packing control over the set. But now imagine you're trying to prove something more refined about it. So what you're gonna wanna do is cover this set, but not by some arbitrary collection of balls.  This makes sense. This is what we do as analysts, right?   Maybe you can prove there exists some nice balls, but you have no idea what they look like, at which point a Hausdorff control is not sufficient. You have to know that you have a packing control and therefore whatever covering this is, we can control the covering by nice balls. And we'll actually have a direct use of this and by the end of the lecture, I think. At least I'll point out where it's directly used. Also, when you're proving a priori estimates for nonlinear equations, it's the Minkowski estimates that do it, not the Hausdorff estimates. So one really wants this sort of effective control. Okay, so fine. We've crash-courced packing estimates. Yay. Crash-courced number two, rectifiability. So, and I'm gonna focus on sets. You can do something very similar for measures. Okay, so what does rectifiable mean? So what is a nice space? Well, the nicest space out there is Euclidean space. What's the next nicest thing you might do? You might be a manifold, right? So maybe you're Euclidean space, but geometrically speaking, maybe you bend a little bit. These are things that we know how to do analysis on. We like these things. So we like subsets of Euclidean space that are themselves manifolds. That will be best, right? It'll be really nice to talk about, let's find a, let's like it with the Reifenberg set, let's find a set which is actually a manifold in one sense or another. So what we want about these manifold things are two pieces. One, we like the topology, but we're gonna give that up in just a minute. And two, we like the fact that we can do analysis on them because there's a bioliption structure. There's a notion on manifolds of things like derivatives, gradient integration, everything you need to sort of work as an analyst, it's there. And if you think for a while about, well, what's somehow the strongest looking set that's completely awful, but we still have all those things in Euclidean space, rectifiable sets kind of fall in that category. So they're very much like k-dimensional manifolds, but we're gonna basically throw some stuff out because it turns out if you throw stuff out, we can still work with them as analysts. So let me start with what's gonna be an annoying definition. So the flat-out definition is the following. And one can be sure people struggled for a decade to get this one right. So let S be a subset of Euclidean space. We say S is k-rectifiable. I'm gonna define something called, there's actually about 16 different names you might throw in front of rectifiable for different versions of rectifiable. I'm gonna technically define what some people call countably rectifiable and I'll point out the differences. S is k-rectifiable if there exists a countable collection of Lipschitz maps, whatever. If you want good English, you're gonna have to look at the notes. I have limited room, Fi, which maps from some sets, Si, which are subsets of Rk now, right? So this is supposed to be k-rectifiable. So now I have a whole bunch of subsets of Rk, right? Into Rn, such that the images of these sets are gonna cover S up to a set of measure zero. That's the statement. Oops, did I define measure for you? I might have skipped that. That's okay, I still have my board over there. It's one line. Such that the k-dimensional measure, you just limit R to zero. I'll write it precisely over there. Of S minus the images of these sets equals zero. So almost every point of S is in the image of a Lipschitz map coming from Rk. That doesn't sound like a lot if this is the first time you've seen this structure. That sounds pretty bad. However, you can essentially restrict yourself and assume that these Lipschitz maps are actually bilipschitz maps, by Lipschitz embeddings, right? There's no harm in that. So view of these things as actually being images that are fairly nice, right? They're spanning a sub-manifold that's by Lipschitz. And the k-dimensional Hausdorff measure, I'ma set S, is literally just the limit of that as R goes to zero. So that's all. Okay, so let's talk about a few examples here. Just to get a feel for essentially how nasty this can look. And basically, the example I'm gonna give you is really more or less as nasty as it gets, give or take. But I'm gonna follow that up by seeing how nice these sets are. So examples. What's that? Right now, I'm not assuming anything about it, right? So there's two of right. So what he's really asking about here are two things. So first off, sometimes you might assume S has finite k-dimensional measure, right? That's oftentimes done. I'm not doing it. I will explicitly simply say when I said it has finite k-dimensional measure and what I want, usually, because I care about packing in Minkowski anyway. Secondly, when you say this, you might actually assume it's a finite number of balls and not accountable numbers. Some people call this accountable rectifiable. So, right? And there's a whole bunch of other versions of this floating around. So examples. Let S k in R in, and I don't know if you can intersect this with the ball of radius one, if you want it to be a compact set, that's fine. Be a k-dimensional sub-manifold. I'm going to assume smooth, but the point of the definitions, you really only have to assume kind of Lipschitz. But let's just say smooth. Why not? Clearly, this is k-rectifiable, right? This is the point. So essentially at every point, there's a neighborhood of this thing, which is gonna be diffeomorphic to a ball in Rk, right? Union all those maps up, right? So this is gonna be k-rectifiable. First point of nastiness. Let S tilde k be a subset, any measurable subsets, your favorite measurable subset in the world. This is also k-rectifiable. So the key difference here, right, is that sometimes people will sort of fakely view a k-rectifiable set as being a k-manifold. And this is kind of true, but the point is it's true away from a set of measure zero, and that measure zero set need not be closed, which means all topology goes away. All right, so this can be all kinds of nastiness sitting inside here. It turns out not to be that bad, right? There's still gonna be tangents at almost every point here. It's still gonna really look like a manifold from every analysis point of view. So we're okay with this. So this is it. How do you get this, by the way? Take your diffeomorphism maps for this guy, and for each of these guys just pull it back on this, and those are your SIs over here, right? So any subset of Rk in particular is k-rectifiable. And now just to make this frustrating, let's let S as a tilde, maybe I'll call it a hat, whatever, okay? Be the union over all rationals of this S tilde translated by q, right? So think about dimension one for a second. I'll draw a picture. Pictures are nice. So if we're in R2, here's the plane R2, right? Here could be my S1. I can take any subset that I want to that, and now what I can start doing is moving it up and down by, by, by translations, by, by rationals. So what I actually get is a union, a countable union of all these things that are floating around here. So that's also k-rectifiable. So why can you still work with a countable union of such things? Because if you're an analyst, you can basically just work with each one individually more or less. It's more subtle than that, but as a first approximation. Okay, and now I'm not gonna go through it, but you have at least written your notes and actually.


Hello, everybody, and welcome. My name is Greg Marsden. I'm responsible for Linux kernel development at Oracle. We provide OS and kernel services for Oracle Cloud Infrastructure, upstream Linux feature development, upstream kernel packaging, and case-placed rebootless patching. A large part of that role has always been security, but never more prominently than this year. In this talk, I'm going to talk a little bit about various approaches to OS security from a design and process perspective and some of the lessons that come out of these experiences. As more services start to rely on containers for isolation, what are the ways to protect yourself and your data? For those of you listening who were involved in this past year of security vulnerabilities, that was an amazing accomplishment to get the patches done and shipped for each vulnerability on time. Thank you so much for sticking with that.  We need one more patch in there. As for the user community, security isn't new. It's just finally in the budget. Take this time to get good security policies put in place, ones that really guarantee that your systems will stay up to date. The other day, I got a call from a friend. We have a winner, he said, for our system with the longest uptime, 2,258 days without a reboot. On your kernel, we found it in a closet, 2,200 days. That's more than six years without a reboot. I'm still not sure whether to be proud of that accomplishment or not.  But on the other hand, it's now tempered a little bit by the knowledge of security exploits, vulnerabilities, and sympathy for whatever poor soul is going to have to someday upgrade that application to use system D. If there was one benefit to our year of security, it was rooting out boxes like this one, an artifact of a simpler time. Just try starting a server on any large cloud providers public IP block these days. Watch your log files. Even without a host name assigned, attacks are going to start to roll in, security probes, SSH login attempts, Apache post requests. It's not academic research. Security breaches are up. One way to handle that legacy OS problem is through containers. Containers are really popular right now. And for good reason, strict container usage provides process isolation, creates a natural sandbox environment should an attacker be successful. After all, they're still stuck in that container. And this makes for pretty decent security to an extent. Containers do share a lot with the host OS and share a lot with each other. It's one kernel running underneath all the containers. And a vulnerability that affects that container is a vulnerability in a kernel that's going to affect every container running on that system. Meanwhile, each container has its own user space runtime stack with their own sets of security updates. Containers will still be updated if the on-disk version of the library is updated, but only if the container is actively restarted. Until it restarts, it has the old version of all of those libraries. Applications, which are written to live in containers using a microservice architecture, those would actually be updated because they're easy to update. But if it's going to be a legacy type application, those real-world container workloads are going to have the same uptime and availability requirements as a classic data center service, which means that despite the advantage of deployment and packaging, container security isn't really that much better than the old model of application development. Containers also provide a perfect jumping off point for side-channel attacks, running on shared processor resources and sharing kernel and system services between each other. Side-channel attacks work against processes running on hyperthreads. And C-groups and namespaces don't necessarily give native protection against sharing processor resources with potentially antagonistic workloads. We are really excited about the promise of the Cata Containers project. Rather than running as processes and namespaces, Cata Containers take advantage of hardware virtualization for process isolation and using a stripped-down kernel that boots in seconds. These special containers use those hardware virtualization features to defend against cross-contamination with other containers and will be able to take advantage of KVM's defenses against side-channel attacks. That problem of one vulnerability showing up in every container is only magnified in the cloud world, where containers share one kernel across a computer, clouds end up sharing a hypervisor across the entire fleet. Clouds still have plenty of software diversity at the guest layer, but they enforce much stricter controls at the service and hypervisor layers. Clouds have managed to standardize, to some extent, the hypervisor and virtualization environments to provide an enforced consistency across that whole environment. An ideal cloud would have just one OS platform running all of its services, just one hypervisor version that's running in those services that's always kept fully up to date, fully patched, and can be patched for security at a moment's notice. Because when security vulnerabilities are fixed, they need to be fixed everywhere. Because having a homogeneous environment means a faster response time, and it means that a vulnerability that can be patched there will be patched on all the systems instantly. There's a saying for this. Put all your eggs in one basket and watch that basket. For our cloud, that means relying on rebootless live patching. Live patching is now fairly commonplace. It used to be magic, and the case-play team worked very hard to convince sys admins that they really could patch their kernels in real time without requiring reboots. Here's why you want to think about live patching solutions for your production workloads. Cloud service providers often can get early disclosures for security vulnerabilities, but end users really only found out when those public disclosures come out. So live patching is really the next best thing. Having a system that can actually respond and pivot to attacks in real time towards a self-healing OS. And the abilities of live patching have scaled farther than we ever could have imagined. For the latest variant of Spectre, we were actually the L1 terminal fault one. We were actually able to apply, in real time, a patch that ran more than 2,000 lines of kernel code across 50 kernel files in real time without rebooting. Now, that's how you keep a fleet secure. And why has patching been in the news? Well, the latest raft of security vulnerabilities come from a new class of exploit known as speculative execution side channel attacks. Like other side channel attacks, they take advantage of external, measurable characteristics of the processor, like power consumption or temperature. And in this case, it's timing the loads and stores precisely in the speculative execution pipeline and timing those results. It's not directly reading data, but the latest optimized proof of concepts have refined this to a data exfiltration tool. What slows that attack down is that each bit of data requires sometimes hundreds or thousands of attempts and comparisons. And the good news is that we don't actually know of many real-world exploits of this yet, probably because it's easier just to send out some spearfishing emails. But as people get smarter about their SOP security, we need to start thinking about some of these back-channel attacks as well. The bad news is that many of these speculation-based attacks are indistinguishable from correct processor operation and can be mitigated but not detected. There's been a lot of discussion about the vulnerability disclosures that came out even just a moment ago. Despite the very late notice, I think all the OS vendors were able to scramble and have those vulnerabilities patched at the same time. It was not a fun exercise. There's an inherent conflict to keeping embargoed security vulnerabilities private in an open-source community. But it's going to do more harm than good if those security vulnerabilities are exposed before they can be patched. Therefore, sometimes it is necessary to have secrets even in an open community. Those vulnerabilities don't stay secret forever. They do get published. Even the vulnerability code sometimes becomes open. Responsible disclosure gives the vendors a chance to fix the bugs and gives Linux developers a chance to fix those bugs. And I want to thank some of the researchers at TU Graz and many of the other ones who have ensured that the Linux community had the chance to patch those vulnerabilities in advance. Intel also has significantly improved their cross-vendor collaboration and helped to build a mechanism for responding to these types of issues across the entire Linux ecosystem. Even when everything goes right, security is a race against time or attackers. And time and again, patches have come out at the literal last possible minute. So what's next for security? We've already talked about the promise of Cata containers and the magic of live patching. In the side channel realm, work focuses on restricting available secrets within the kernel with proposals including looking at removing page table entries entirely from the host OS while it's running in a potentially untrusted context and only replacing that entry when it's flushed those secrets out. We also need to focus on traditional security and traditional attacks because where else is this innovation progressing? We're looking at developing runtime patches for G-Lib C. That already exists to some extent with CaseBlyce, but I think there's a lot more room to make that efficient and effective across thousands of active containers. Using SecComp to prevent containers from touching unpermitted system calls. Combined with SE Linux, we can provide a very good traditional security isolation model for containerized workloads at the penalty and there is a bit of a performance penalty, but we're working very hard to remove that. So how do we prevent the inevitable firefighting that comes when security vulnerabilities are revealed? By ensuring that our infrastructure is in a state to be patched quickly. Security comes at every layer in the stack from hardware to virtualization, OS to container, and of course at the application layer too. The most important thing we as developers can do is to make sure security is easy. After all, if applying security fixes is difficult or impacts end users, then most companies will delay weeks or months or longer before the scheduled critical downtime to patch the OS. Don't let that be your company. Insist on a regular maintenance cycle and applications that are designed with patching in mind because when a security issue is revealed, it can turn into a week or a weekend long patching nightmare. A combination of preparedness and rapid response can make the difference between security and outage. So that is the silver lining to this year of security vulnerabilities and it is that people are finally starting to take security seriously. We are finding those machines that have those 2,000 day uptimes and scheduling them for maintenance and modernization. We as an industry are building a robust infrastructure that can be patched quickly and safely. And I go into the next time that I hear someone say, hey, I've got just one more patch. We'll be able to pull it in. No problem. I hope all of you will too. Thank you very much.


Everybody forced here ripping three boxes of 2022 Leaf Best of Sports for Brendan Kay. Thanks again Brendan for the order good look That nice bugs earlier see what you do with a little nicer here. See some big big big. That's pretty nice At a 2020 prism Anthony Edwards variation fast break PSA 10 Yeah, very nice There you go Brendan very good start Sweet variation Edwards the disco of the fast break next up is a 1985 1986 all-star rookie team or star all rookie team John Stockton BGS 8 GS 8 centering 7 5 corners 9 edges 9 and surface 8 5 Stockton on the throwback there. There's a rookie Stockton then I believe that's what it is Nice Stockton BGS 8 HDC slab I haven't seen a thick as you see some before it's a 2021 spectra Davis Mills aspiring patch auto neon orange five of 15 The auto graded a 10 the card graded a nine Love the orange ink on those They sweet Davis Mills five of 15 Nine mint ten good few boxes there for you Brendan. Thank you again, man. Get him right out to you


going into this final round. Great fight, great. Bizer all comes down to this main event. UFC 296, we fought the fight. Take many shots to that bad cut. Here's to start the smiths with the right hand.


I was born and raised in really, you know, it's my hometown. Played high school there. Unfortunately, I had a great high school career with great coaches and teammates that had led me here. You know, I was very thankful and wanting to come here, you know, continue on that tradition, that legacy that was already built before I got here. You know, you got football here, which is a great atmosphere. You got basketball. That's like Alabama's a complete package. You know, it's a great campus.


What I'm going to kind of share with you is very, very different, very something which I truly believe and I think all of us have been defrauded in last 20 years of our existence of on internet where our labor of love, our labor of time, our effort has been really used and misused and appropriated by the platforms who are supposed to be the fiduciary of our information and become zameerdars of our information and I think that's what something which really riles me and I'm going to share what it is. How many of you play games? Can I have some show of hands? What do you, what does the rest of you do if you don't play games, right? In today's day and age, how do you entertain yourself? That's really kind of, I think you need to kind of come up with the time and start playing more and more games. That's what is really going to be the dominant form of entertainment and if you happen to have kids, nephews, nieces and you want to interact with them, I think those of you are not playing games are enough for trouble. I can really tell you on that. So I just, how many of you made resumes, LinkedIn profiles, right? Almost everybody would have made your LinkedIn profiles and resumes. And does your work experience is taken away from you? Yes or no? Your work experience stays with you, right? Right? However your gaming history doesn't remain with you, isn't it very, very funny that you are in spending your time in a job, you are improving your skills, you are embellishing your resume, you are really kind of saying that I have become a better coder, I have become a better manager, I have become a better marketer, better consultant.  Your game data is not yours. It is being monetized by somebody else and you really, how many of you purchased assets in the game, right? Have you ever seen how many have you purchased a house or a car or any goods or a TV? How many of you purchased a TV or a car or a house? Most of us, right? Does it belong to you? Yes or no? But when you buy an asset in the game, does it belong to you? Is it right? Does it intuitively, are you seeing that something is being done wrong to you? Your house, your car, your painting, your TV, but you don't have assets in the game. Who is owning the platform? Who is owning it? Who makes money? The game makes money. So your history is not yours. What you have spent in the game is not yours. Who is creating wealth out of it? And who is contributing wealth? Isn't there a paradox? Who is making money, guys, here? It's the platforms. And who is helping them to make money? It's you. And what you are getting is a ganta, right? That's precisely what is happening here. Is this something which is acceptable? And that's what I would love to kind of really ask everyone of you that intuitively if there was a platform which can say that my data is my own, the assets which I create I own, and I can carry it anywhere, and I can monetize it, would you be happy about it or not happy about it? Guys, speak up. This is your time, right? I'm here to just provoke your thinking, right? There is a video I will not show. The video belongs to 1984 Apple ad. How many of you have seen the famous Apple ad of 84? They broke the shackles. They've changed the industry. And now the same Apple is charging you 30% tax. It's the same company in 84 which promised a revolution to people who were just listening to something is not charging 30% tax to people who are playing games. How is that really innovation and revolution is coming? But I think all of that is game is going to be over.  So it's your asset you have created, you own it, and that's what is going to happen. And from a mindset point of view in gaming, why we are very excited in gaming, I've spent 13 years in making games, designing games. When a gamer is today spending money like most of you, it's an expense. The moment it becomes his asset, he becomes an owner, and that asset, if it's useful in market where he can sell and he can rent, that expense change to investment. Now can you see the flip of the mind? The moment the mind flips from an expense to investment, my propensity to pay increases. And that's what we believe is going to really harness growth of gaming, which is kind of plateaued worldwide. If you see most of the global gaming aspect, it is plus 1%, 2%, 5%. And if the moment asset ownership really comes into picture, the gaming growth will happen. Even more so in countries like ours, where we are talented, we have time, we have skill, we are playing games, asset ownership is going to create an amazing amount of opportunity for us to really build it. We are talking about identity.  Now my Janam Kundli is my Janam Kundli today, but my gaming Janam Kundli is not mine. Now if I can take that identity and I can take it anywhere, I can really monetize it. And that's where we believe the wealth creation will be equally distributed along the value chain, but the gamer will also get its fair share. Today gamer is getting Ghanta, and that's what needs to change. And that fair share is what is the innovation we are talking about. And gaming has always evolved with innovations. Thampi was talking about machine learning, data, experiences. All of that really came when the freemium gaming happened, when people can download games and they can really figure out their own consumer journeys and cohorts. And I believe this asset ownership and identity ownership is the next evolution, next change. I came into gaming in 2010 when the freemium was coming in. Then I saw e-sports streaming. But I think now this is what we are really going to be seeing in countries like India, which have just started in gaming four or five years back. This has got sent because it's intuitively enables people to use their talent, their time and skill to make money. And that's what we want to believe. And I truly believe India can be worth a digital factory. The last 20 years, China was a physical factory. We could be the digital factory. We have 500 million gamers, which are spending 20, 25 minutes per day. These guys have time, skill, and we can really enable and be the catalyst to make India the digital factory. And that's what I think IndiGigi is on a mission to do. That 14 to 25 age group of gamers, which gets scolded every day by her mom, by her dad, by his mom or his dad. And saying that you're wasting time. If you can really provide a career, I go back to 1980s when I was growing up. And cricket was something like this, that you don't play cricket. You have to go and study, become a doctor engineer. And now today, IPL changed that. We believe that if you are able to make a digital goods factory, we can change that perception. And that is where IndiGigi is all about and willing to kind of really do that. And this is something I take a very, very strong inspiration. That our middle class today, we are all product of that middle class, which got created with the IT services. We became a product nation, and now we are going to get the digital goods leadership is what we are going to take. And we will play a small part in this. We will like to be the biggest catalyst in among the gamers community to build these kind of digital goods factory. And that's it guys. Thank you very much.


Hi you guys! Lindsay here. Welcome back to my channel, Inside the Hymn.  It is very early in the morning. 6-11am. Still dark outside if you can see that. But I am here at the airport. I don't know why I'm singing. It's early. That's probably why. Anyway, so yeah, this is my third annual New York City vlog. So welcome. It's a short trip. By the time I land today, wheels down to wheels up will only be 28 hours in the city. So it's a really quick turnaround. But I have packed a lot in and I have lots of really fun plans, including meeting up with some of my internet friends, people that I know from Instagram, and people that I met when I went to New York Social Hour last year. And I think yeah, Social Hour is coming up again this Tuesday. So if you're in the city and you so go to Social Hour. It's a lot of fun and you meet a lot of really cool people who share some more passion as you. What's better than that? So yeah, I have some plans to meet up with them. Of course I have plans to go shopping. I have plans to go to the Met Museum to see the camp exhibit. And then tomorrow is really just all about the Taylor Swift concert. So if you're not here for that content, that's fine. You can stick around through today and then just abort whenever it gets to tomorrow. Things are going to get a little, let's say excitable. Let's say maybe immature, young, but I am very, very excited about that as well. I cannot get rid of this cold. I don't know what to do. It's in my chest. It's congestion. I'm trying to let it run its course, but work on Thursday will be two weeks.  Let's see. What else can I talk about in the intro? I'm wearing my rainbow pastel seersucker dress today. I had to check my bag. They made me check my bag. I've never checked a bag before. I just don't do that. So I feel a little empty-handed. All I have is my little backpack here, but you know, I'm rocking it out. It was a little strange, like knowing what to bring on the plane and what to just get when I get there. I'm just not used to it. But anyways, it's fine. It's fine. We're going to be good. So yeah, I'm flying into Newark and then I'll take the air train into Penn Station and then I'm going to head straight up to the Met Museum. So here's a lot of really fun traveling content, a lot of really fun flying content, just to show the passage of time. And I'll see you guys on the other side. I could not make it. She has a friend who has terminal cancer. So she's headed there this weekend to see her and give her all the love she deserves. It's going to make me emotional. So no more sad stuff. But yeah, Amber can't be here. So it's really strange because we've come together the past three years. So it's really odd seeing all of our favorite spots and places that we've hung out, but she's not with me. But that's okay. At my first destination, can anybody tell where it is? That's right. I'm at the Metropolitan Museum. I'm going to see the camp exhibit. It's the fashion one that the Met Gala is based on with all of the crazy outlandish avant-garde. I almost called them costumes, but they're not. They're garments in fashion. So I'm going to head in there and check it out. I have one more than an hour. So we'll see how much I can get done by myself in an hour. So here's my take on what it's like inside the camp exhibit at the Met. I was pleasantly surprised to see the walls covered in this beautiful pink. The first part of the exhibit explores the evolution of the definition of the word camp. First camp as a verb, then camp as an adjective, and then as a noun. You can pause the video to read these explanations, but basically camp has evolved from meaning to flaunt the verb to explaining like cross-dressing the adjective and also kind of defining what a homosexual is, the noun. During this part of the exhibit you could hear over the rainbow playing through the speakers. Then in the 1960s, this woman, Susan Sontag, wrote this thing called Notes on Camp. The audio in the exhibit switches to the sound of a typewriter, and these next displays illustrates Sontag's 58 different notes, the notes on camp. Then Sontag also explored the idea of unintentional camp versus deliberate camp, and these next displays show one of each of these side by side. They didn't allow video beyond this point, but I wouldn't be a good vlogger if I didn't take some anyways. I didn't get a lot, but if you want to see more of this room and hear the exhibit explained in much more detail, the Met has this really awesome video on their website. I have linked it in the description box, so you can check that out. But in general, I thought that the exhibit was more of a kind of broader audio-visual experience rather than kind of just a fashion exhibit that was just about the clothes on the mannequins. Once you entered this main room, you couldn't really get up close to every garment, especially the ones that were on the second floor. But when you stepped back, kind of zoomed out and took it all in, it was very visually kind of stunning, very bright colors and so many textures. So all of that kind of taking it in, like taking in all the senses, what you're hearing over the speakers, what you're seeing with your eyes, you know, all of that together was really quite an experience. But I wouldn't say that I walked away from this really getting a better understanding of garments or construction or anything along those lines. It was really just kind of a beautiful audio-visual experience. Sorry I've been a bad vlogger, but I have just been bouncing around by myself in and out of different stores, not necessarily staying for very long. What I'm trying to do is find fabric to make this Reformation dress and the trim. So I went in, I don't know, 45 trim stores and the closest I got was this from Lauren Trimming. So I'm at mood trying to find fabric and no pun intended, but I'm not really in the mood. I know I'm in the right section, I just, I'm not feeling like looking for it for some reason. It's also really hot and humid out. But I went to Metro Textiles and B&J and all the usual places and no look. So I'm going to keep going though. I'll keep you posted. Okay, so I came to Sheik. Don't mind this, it's very humid and look what I found. This is my social mashup fabric. I suspect you got it from Sheik and sure enough here it is. So if you're in New York City, come to Sheik fabrics on West 38. They have a ton of it left and come get you some. All right, you guys, I am back at the hotel after a very long day. Look, there's a TV in the mirror. Wait for it. Cool. So where did I last leave you? Okay, I'm delirious. I don't know how important TV is that you need it while you brush your teeth, but I know I can't turn it off. Here we go. I don't know how important TV is. Okay, so I last left you in mood. Was that the last time we spoke? That seems sad. I ended up meeting up with a few sewing friends, some girls I know from Instagram. We went to fabrics and fabrics and got some fabric. And then we went to dinner at some Thai place. It was not in the garment district. So I'm not going to tell you what it was. It's kind of a bit of a trek to get out there anyways, but it was really good. If you want to know and I think it was in the Hell's Kitchen area, let me know in the comments. But I thought we would do a fabric haul. Doesn't that sound like fun? Okay, full disclosure though. I didn't get a lot. I only have three things and then some trims. So better than nothing. And also to be quite honest with you, I still haven't even touched some of my fabric that I got at the last trip or the trip before that one. So I really had no business buying a ton of fabric. I think last time what was the count? Like 30 something pieces? That's insane. Don't do that. But I did pick up some stuff. So I'll show you what I got. First up, we have this and the lighting in here is not great. This is coming. This is not as beige, but there's not really any more lights. It is like a Ponty-esque fabric. It has this really pretty black, gray, and cream, which I really do not have enough like neutral patterns. Like I love patterned fabric, but a lot of it tends to be very colorful and whatnot. So it would be nice to have something that's just a little more subtle for the days where I'm not feeling like being so colorful, but it's still not a solid. You know what I mean? So this will be a really pretty like fit and flare. I got this from Chic. It was two dollars a yard and there are, I think there was two yards here. So I got that and then also from Chic, I went back and got the Carolina Herrera Zebra fabric. So if you don't remember this story last year when we went, excuse me, I got a couple of Carolina Herrera fabrics. And so whenever I went home, I went to try and find them like on Carolina Herrera's website. Like what did she make out of these fabrics?  So when I saw it on her website, I was like, oh my god, that's that Zebra fabric. I got this from Chic and I think that they just don't know that's what they've got. So they had some of it left today. I got it for six dollars a yard and I got three yards. I plan to make a shirt dress of some sort from it, probably sleeveless, but they still have plenty of this there. So if you're in New York or will be in New York and you like this, go check it out. They don't really have an online situation happening. But I also went to fabrics and fabrics and got this gorgeous brocade. So this is Christian Siriano. It is navy, although it's looking a little black, but it's navy with gold metallic thread and then these digitally printed flowers. So it's kind of like two processes. One is the fabric is printed with the flowers and the navy background and then this gold thread is woven throughout. And I just think that's going to make such a gorgeous dress for the holidays for, I mean, I don't have to go to any weddings, but if you did, it would be perfect for that. Perfect for any, you know, work party, anything where you want to feel a little bit fancy. So I think this is like $40 a yard pricey. But like I said about fabrics and fabrics before, they have really great quality stuff. So I mean, even the back of this is sort of pretty in a neutral, quiet kind of monochromatic way. Anyways, and then when I was at Pacific Trim, I got a whole bunch of ribbing. So I have a project in mind. This would be the waistband. These would be the cuffs, like for a bomber jacket, you know, and this is going to be like the outer part of the welt pocket. But then I also found these, this little cutie, let me see if I can show you how it works. Basically, you would attach it to a sleeve and it has this cute little like sleeve ruffle thing happening. So I'm thinking like sweatshirt fleece and then attached like black sweatshirt fleece and then attach this to the bottom for like a really, really pretty girly touch. I don't know. It was speaking to me. It was also in the 50% off bin. So I couldn't pass that up 50% off here and here and here. This, sorry, all of these were 50% off. This is the only one I paid full price for. So I got all this for like $17 or something like that. And then remember earlier today, I was showing you guys that reformation dress that I want to make the like botanical one with the trim. So I found this place, I mean, I went in a lot of trim stores today. This one Lauren trimming had, it's not focusing, had the closest thing to the inspiration photo. And they have like a natural color and then one that's more vanilla. It's not totally true white. But I mean, either of these would be good options. I'm tending to lean toward the bigger one because it would stand out more. But it will depend on what fabric I find. I went everywhere. I could possibly think of all the really nice stores as well as the kind of, you know, cheapy stores and could not find that fabric or anything like it, like not even close anywhere. So now I'm thinking instead of trying to find something that's like just like that, that I'm going to just do like an inspired by. So it'll still be like a lightweight linen or like linen cotton blend. It probably still floral. I would love to find a botanical. But I'm not so beholden to it being exactly like the inspiration.  So that's good, I guess. Because if you can't find it here, I mean, are you really going to find it anywhere? You know what I mean? Like I went to all of the stores today and showed the picture to the employees. And they were like, Yeah, no, we don't really have anything like that. So I mean, it is what it is in a way. I'm kind of glad that I didn't find anything close because now I'll make my own creation. And I really feel like the what makes that dress so special isn't necessarily the fabric. It's the application of the trim and how unique like all those tiers are. So that's my story with that dress. It is like nine something. Oh no, it's a little after 10pm. Madeleine is my Swifty, my sewing Swifty friend. We are both equally passionate about sewing as we are about Taylor Swift. So we are headed to this concert tomorrow. And for those of you that think that we are crazy for getting up and going at three in the morning, like I'll have you know there are already people outside. Taylor Swift and her father had someone deliver them pizza when they heard they were out there. So I think us going at three or four in the morning is not the big of a deal on the grand scheme of things. But we are going to chat and talk and hang out and be girly and have a lot of fun. Sorry, the video cut off and then I rerecorded it without recording. It is late. It is late and my brain is not working today. It's already been I got up at 4 30. So what is that 16 hours? Yeah, long day. But we're going to have a good time making the most of this, you know, very unique opportunity to hang out and possibly meet Taylor Swift. I mean, I don't know anything can happen tomorrow. Like literally anything can happen. We could become best friends. Right? I mean, why not? The possibilities are endless. But yeah, so I will I guess be back when Madeline gets here. I don't know if she wants to be on camera or not. That's kind of like putting her on the spot. Either way, I don't know. I can't think much past five seconds from now. So I'll see you soon one way or another. Well, it's been maybe four hours since I spoke to you last. I took a little nap. I got ready. As you can tell, I'm adorned with my Taylor Swift lover eye heart patch, whatever. And we are getting ready to head down to the park. Apparently there's already hundreds of people there. They've been camped out since 9 p.m. last night. I slept in a comfy bed. It was great. So who knows, we don't really know what to expect. But we're just telling ourselves it's going to be awesome no matter what. So I'll see you at the park. So it is 408 a.m. and there are thousands of people here. Supposedly they all got here at like some people, I guess the first person was in line at like 3 p.m. yesterday. So hopefully that will have been worth it for them. But we're just excited to be here. Like everyone in line is dressed up and excited and has their merch on. So we'll see. Hold on, waiting for it to focus. Focus. Focus. Oh, I'm a mess. It was very hot. Very humid. Very crowded. There were 7,000 people there, supposedly. Hannah Brown, the Bachelorette. Tiffany Haddish, of course the entire GMA hosting team was there. And it was just magical. So they did a sound check with just the band. And then Taylor came out for a sound check, three songs. And then she did a little on-stage interview. And then she performed those three songs for the TV show. So all in all, we heard the three songs three times and got to see an interview. And I was definitely like the closest to her I've ever been that I know of.   But while also still like engaging with the fans, I don't know. It was a lot and it was great. So I have a bunch of videos that I shared on my Instagram story that I'm going to insert here in case you guys want to see what it was like there. And if you have any questions about what it's like to go to a GMA, summer concert filming thing, let me know. I'm happy to talk about it more. But I have, it's 10 a.m. I almost said p.m. This is, I got up at what three? 3 a.m.? Yeah, 3 a.m. Yesterday I got up at 4.30. So yeah, running on fumes. But I have to get to the airport and head home and get my sunny. So this is probably going to wrap up my trip here in New York City. I know it was super short and I know it was only really only one day of like sewing stuff. But I still hope that you enjoyed coming along with me. I loved having you and I had a really, really, really great time. I was really able to cram in a lot of great fun stuff and see all my friends here. So that made it all worth it, even though I've gotten three hours of sleep. Yeah, three, three and a half hours of sleep. So anyways, thank you all so much for watching. Enjoy these next few clips and I will see you all very soon. Bye.


This is ThinkDex Hawaii, Community Matters here. This is Craig Thomas, your host on Much More on Medicine, part of ThinkDex Hawaii's live streaming series, and our engineers today, as always, and it's wonderful, Rich and Ray. And joining me today is Ralph Godo, my friend of many years. Thanks for coming, and tell me a little bit about yourself. Well, the most important thing is that I'm retired after 30 years of working with the city, with the lifeguard system, and right now, do whatever I want, come and talk with you, do a little bit of ocean safety stuff, but happily retired. Happily retired, honestly, I always thought you were happily working, too, so that's a credit. You were the, honestly, you're an inspiration to me in a number of ways, so I might as well tell you about a couple of them. One was, I know that you generally went for a swim in the middle of your work day, and that's pretty cool. I don't know how often you pulled that off, but I know it happened. And I think that's important, because part of our health is making sure our bodies are engaged. Absolutely. The other way that you are an inspiration to me is that you've focused on how to keep people healthy, not on the drama of the intervention in ocean safety, that I think it was called lifeguarding when you started, likely. It was always the rescue. And we do too much of the rescue in medicine, whether it's pre-hospital, an emergency department, the dramatic therapy. Almost always those things mean something, well, they always mean something's gone wrong, and they usually mean we failed in some way to anticipate a bad event and didn't intervene. I think that whole concept of reaction versus prevention is so true, and you and I have spoken about that many times. The prevention stuff isn't real dramatic. It's not real glitzy. It's not like, oh, they made a rescue in a 20-foot surf at Waimea. It's something that's ongoing that has to be a part of what we do as lifeguards and as safety people. I agree. And the challenge is, there are many challenges. What works in prevention, what doesn't, hypotheses are fine, anecdotes are fine, but they aren't science. And they shouldn't shape policy. But in addition, you touched on something else. Everybody loves drama. People pay for drama. The actual saving a life or preserving health or making a more healthy place to live, that's often unexciting and it's work. That's what you folks, walk us through sort of the evolution of what is now ocean safety? I think that when I first started, which was a number of years ago, 1981, people said you should go to Australia and LA County to find out what's really going on in life-saving. So I went and saw some really good things. I came back to Hawaii and said look, there are things that are going to work in LA that aren't going to work here in Hawaii. So we took some of the concepts and some of the things that we learned and applied them here with that perspective. You weren't going to stop people from surfing. You weren't going to stop guys from going and laying net and diving for fish. I mean, that's part of their lifestyle. So I think that's something we accepted. We were very impressed with Australia's surf life-saving. They're very dramatic. They have these studs that do all this wonderful stuff. And from LA County, we learned about organization because LA County, they're probably the highest paid public servants anywhere in the country. They make a lot of money. But it's not because they're cool or they're ocean guys. They worked at it intelligently, systematically. They have a pretty enlightened coastal community that they worked politically and got to where they are. So they are, in my view, the example of what a public safety agency should strive towards. So we worked at that. And when we first started, Craig, well, you were around. It's true. I think our career spans pretty much the same decades. There were the surfer guys. There were the ocean guys. There were the studs. No one, not really any formal training, you're going to be the lifeguard at Hanama Bay. And at one point, there were two lifeguards at Hanama Bay. Now there are like 12. So it's evolved from a reactionary sit-in-the-tower wait for something to happen, go make your dramatic rescue, do CPR, do mouth-to-mouth, to more of a prevention-oriented organization. It's been a pleasure to watch it. Because pretty clearly, if you're doing CPR, it's not likely to end well. As an aside, I like the TV shows on medicine that portray actual adverse outcomes, failures in diagnostic acumen, because we're all human. And one beef I have with most of those shows is that the CPR success rate is on the order of 80%. So the public expectation is, oh, they're doing CPR. It's going to be fine. No, almost never is it fine. So that's been a pleasure to watch. I know you also innovated some sort of Hawaii-specific, or should I say, innovated in Hawaii, some things that worked well here, and I think have been adopted largely across much of the ocean community. I think the two areas where Hawaii has really taken leadership in life-saving, one is rescues in the big surf, because this is, you know, this is Mecca. This is Waimea at 30 feet. People come from around the world to challenge that environment, to surf it. So the work that the North Shore Life Guards have done, and the West Side Life Guards have done, really been pioneer work. How do you do a rescue at Waimea when it's closed out at 30 feet?  You know, when you get out there, it's too gnarly to come in, so you wait for the chopper, and it's drama and trauma. And it's slow. Yeah.  So one of the, you know, the other area where we definitely did the original work was the use of personal watercraft, the jet skis. And originally they were looked at as dirt bikes on the water. They're offensive. Nobody wanted to play with them. And there were a couple of lifeguards that saw the potential. Brian Kailan, it was one of them who, during a surf contest, got wiped out, and a guy came up with the jet ski and put him on it, and the light went on. He goes, wow, this is something we could use. They developed the use of the ski. They put a sled on the back, started as a boogie board, and now it's evolved into an actual rescue platform. And it's just, it really has revolutionized life-saving, surf life-saving. And that was done here, not in Australia. It was done here. I bike down the east coast of Australia, and I love the aspect of the surf life clubs to popularize the, how to do water activities and the fitness and culture associated with them. I prefer your approach to keeping people from getting hurt. And on a personal, I have a friend, a windsurfing friend, who, if there was a jet ski in the presence out at Phantom, so years ago, he'd be alive today. So, you know, it's, it's personal for me as well as just as an ER doc. Familiar with the case, and you know, a lot of those situations without the ski, people, the outcomes would have been a lot worse. Yeah. I mean, he was a guy, definitely could have been gotten by a ski. There wasn't one, and he died, as we know. The other thing about the ski, or I think one of the important things about the ski, is it's another tool. But you know, it's another weapon in the quiver, if you will, which has really helped the lifeguards in their rescue response. And it takes its own training. You know, guys don't just hop on the ski and go. Oh no. It's pretty rigorous training, actually. The last Eddie, there were, I don't know, how many skis, but a huge set came through, and there were five, I believe, all going like crazy for sure on the same wave, because they were caught inside. So these guys were really good. That was classic. That was awesome. And you know, that has really, it caught the attention of a lot of people. I showed that video piece at a World Conference on Drowning Prevention a couple months ago. And you know, those are the, once again, the drama, the glitzy stuff that people see that you can use to draw attention to your basic safety and health messages. Absolutely. And to me, it was just also a demonstration of tremendous skill. Absolutely. Let's talk. There's always a hazard of getting in the ocean. Maybe we could get the leading causes of fatal injury slide up. I'm a water guy. If and when I go, it could easily be in the ocean, although I'll try to avoid going prematurely. Why don't you talk about sort of the relative risks of the various events in the ocean and patterns you're seeing. There's been a possible blip this spring. Small numbers and a long set, so it's hard to know. You know, one of the things that we've tried to do is look at the data, you know, a little science if you will, because if you have the data and the information, then you can make some intelligent decisions about what you're going to do, how you're going to deploy your resources because you only have so many jet skis and so many lifeguards. If you look at the data, the data really shows that in Hawaii, drowning is the fifth leading cause of unintentional injury, death. But by far the leading cause of fatal injury for visitors. What that tells us is, okay, are the visitors, how are they more susceptible to this? Are they less educated? Are they inexperienced? Do they come to Hawaii with heart or lung conditions? All of those things have to be factored into what you see and what you can do to prevent it. Because, you know, we used to think, the tourists, they don't know what's going on, watch this guy, he's going to get caught in the river. I think we've shifted that perspective from, okay, we need to know what's going on, and we need to educate people about risk, about putting your foot in the ocean involves some risk, you know, and that's been a real challenge for us. Yeah, and honestly, you've done a big job. When I started years ago, one of the places we staffed is Castle, another one is Wahiwa, they both get ocean-related injuries, and I'm sure it's still happening, but the rate of shoulder dislocation, cervical spine injuries from makapu and sandies has plummeted, and I'm sure it's because I know I've watched your folks do it. Sir, I wonder if you should read again. Do you realize those kids are really good at this, but you might not be? Yeah. I've seen it happen, and it makes a big impact. The next slide shows drownings in Hawaii by tourists versus residents, and also what they were doing. I think it's pretty interesting. It's very interesting because I think one of the things that we kind of take for granted is that people, visitors, especially come to Hawaii, why do they come? They come for the beach. I mean, 90% of them, I dare say, would be going into the ocean, not just once, but a couple of times during their stay. The data shows that the leading cause or the leading activity involved in non-resident drowning is snorkeling. So what's going on? And that's what we're trying to find out. Exactly. So in the second half, as soon as we're back, we'll talk about snorkeling. This is Craig Thomas, much more on medicine with my guest Ralph Goto. See you in a minute. I'm Ethan Allen, host of Likeable Science on Think Tech Hawaii. Every Friday afternoon at 2 PM, I hope you'll join me for Likeable Science, where we'll dig into science, dig into the meat of science, dig into the joy and delight of science. We'll discover why science is indeed fun, why science is interesting, why people should care about science, and care about the research that's being done out there. It's all great. It's all entertaining. It's all educational. So I hope you'll join me for Likeable Science. Welcome back. This is your host, Craig Thomas. I'm much more on medicine with my guest, Ralph Goto, who I've known for at least 30 years in our sort of parallel careers and trying to hopefully improve health. And when things go sideways, do what we can to fix it. Was it 30 years ago, we did the jellyfish manual? It was more like 20, more than 20. And it's actually interesting you say that, because in fact, hold that thought for a moment. I want to talk slightly more about snorkeling, but the jellyfish thing was fascinating. And I think we should talk about it, because it demonstrates the difference between hypothesis and science. Absolutely. So before the break, we were talking about how people get in trouble in the ocean. And we were talking about the fact that visitors seem to have a real challenge and have for many years with snorkeling. A little later, we're going to talk about a workshop to investigate sort of current states of knowledge and possible areas of research. And also see if the trend is changing. So this is applying science. The years ago, Ralph and I collaborated with Susan Scott, my wife, and the Ocean Watch columnist who put in a plug, on what works or not when you get stung by either a box jellyfish or a Portuguese man of war. And with the assistance of a couple of your guys, particularly Landy, worked his butt off on this, we did some studies. And we, among other things, used the product that was, I think, was that important from Australia? I don't think so. I don't think so. There was some miracle product that was being used by the gallon at the time. But there was also meat tenderizer. There was saltwater. There was freshwater. And this was all done in a blinded, controlled fashion. We also looked at heat and cold. But the more important data was the solutions. And to me, the really interesting, there were two fascinating things about the study. The first was, there were a number of people, both lifeguards, but also people on the beach, entirely convinced that this was unethical, because you were potentially putting a placebo on somebody. And we were. But it turned out that the placebo worked every bit as well as everything else, including the expensive commercial product. And it changed practice. That stuff disappeared. It's a great story and a great example. It really was the first time we, as a lifeguard operation, got involved in some science, some data, some research. And I think it was, for us, it was very enlightening how we had to do that double blind study, getting people's permission to do this and getting acceptance to do it. But I think the parallel is stuff was going on. Everyone had a theory. Everyone had their answer or their solution. And we actually were able to test those hypotheses and come up with some answers, which is really what we're trying to do in a lot of areas. Exactly. And it ended up in changing practice. And by the way, Ralph, our papers were recently cited in the Annals of Emergency Medicine as part of their addition on treatment of environmental injuries. And it's still current. So that's great. We actually, I'm pleased. Studies don't always stand a test of time. So let's talk a little bit about what do we think's happening with these tourists, if anything. And it's local people too. Incidentally, before we actually focus on tourists, I'd like to talk very briefly about freedivers. I like freedivers. I am fortunately a chicken freediver. And as I've learned more, I've become more and more chicken because, first of all, almost all the good stuff's not all that deep anyway. But second of all, well, talk about it, shallow water blackout and those things. The focus and the attention that we've put on, these snorkeling incidents, if you will, results in a lot of, once again, theories. Everyone has their point of view. Some say it's shallow water blackouts. Some say it's O2 deprivation. Some say it's pre-existing medical conditions. There are a lot of theories that people are holding and subscribing to. The freediving issue is a little different, I think, because most of the fatalities that we're seeing happen on the surface. They're not going down and getting stuck in a hole. No, no.  And believe me, local people get in trouble, too, by overextending their abilities or trying to stay down too long. But the majority of the ones that we've been seeing, especially in the past couple of months, are primarily not beginners, but not super experienced people. They're in the ocean. They're on the surface. And that's what we're trying to figure out. What's going on with these people? What's happening? We used to think, well, look at this guy. He's at Hanama, and he wasn't paying attention at the video. And he gets a mouthful of water, and he panics, and he drowns. Well, there's something a little more than that, I think. And that's what we're trying to figure out, is what happens right before that sequence of events. Do you think there's been a change? And I'm not talking about this spring blip. And maybe we should get Dan Golanus, who I know is going to be presenting it to your workshop that's coming up, to look at this. But do you think there's been a change in incidents of snorkeling death? It's a little tricky, because the number of snorkelers, tourist snorkelers, has dramatically increased over the years. Yeah, there's a couple ideas that we could put out there. If you read the paper, which I know you do, Greg. Actually, I do. It's my job as assigned at home. It's 9.5 million visitor arrivals, looking at 10, which HCA says, that's great. They're filling the rooms. Well, what are they doing when they get here? They're going to the beach, most of them are going to the beach. And it's an access issue as well, I think. For instance, did you go to the Great Barrier Reef?  I've done both. When you go to the Great Barrier Reef, I think you have to go on a boat, or you can't just kick your way out there, right? If you come to Hawaii. Well, I don't know. It's 25, 30 miles, so are you good at kicking the road? So you have to be short. The bottom line is you're supervised of some sort. Maybe it's a boat captain drops you off, blah, blah, blah.   Absolutely. So there's many more people doing it, and many more unsupervised people doing it. And there's some challenging environments. Most of the places people snorkel in the Great Barrier Reef, which is an astonishing thing, but most of the places you actually snorkel or died are places that are sort of pre-vetted. And that makes a big difference. And you know what, and we did, we polled my colleagues Miami Beach, what's happening, Florida Keys, what's happening in the Bahamas. I talked to my friend on the Gold Coast about the Great Barrier Reef, and there are clusters of these things going on around the world. But this is ground zero. We're here, I mean, this is what's happening. It's snorkeling by far is happening here, and I think that gives us an opportunity to really look at it and try to figure out what's going on.  You then need to decide how to test it, and you need to test it in a way that's controlled for as many variables as possible, ideally blinded, although that's not always easy to do, because if you don't do that, that's all it is, is a hypothesis. And medicine is full of many more wrong hypotheses, proven wrong by just like the jellyfish trial, than right ones. And I know that's your focus. And the other thing to be careful about is the sort of what we call surrogate marker problem. So there's the blind adoption of a hypothesis, you don't want to do that. And then there's surrogate markers, which might be some characteristic of a piece of equipment or some measurement of carbon dioxide, let's say. I'm not saying those things aren't important, but they aren't actually proof of the answer. One of the things that we've discussed is we need to find out more information about what's going on with the patients or the victims of fatal drownings or fatal drownings. You can't interview them with all due respect, because you can't interview them. But you can interview. We might have a blind enjoyed you over the years. But you can interview the survivors. You can interview the guys that we say that we rescue and say, hey, what happened? What would happen? Look at their equipment. That's one part of it. Interview them to find out what activities they were doing before they got in the water, their general health status, and things that may have contributed to it. Because like you say, it's theory. And until we can really get more reliable data, if you will, we're shooting into the wind.  I mean, we need to tell people, hey, this is what we think is going on. And this is what you should be aware of. Yes. And if we hadn't developed hypotheses and then tested them, we'd still be doing blood lighting or leeches I could go on. We're about to wrap up. But I think it would be great if you could give a little description of this upcoming workshop and invite people to come. Great. Next Wednesday, the 28th of March, we're having a workshop. We're calling it the Snorkel Safety Workshop at the Hilton Hawaiian Village. And it's open to the public. There is a slight fee to pay for lunch. In the afternoon, well, in the morning, we have a series of presenters, excellent presenters, physicians that are in the field, emergency room physician, the city and county medical examiner to talk about what he's found. Dan Galanis, the epidemiologist from the state, will present the scope and where it's going and what's happening. And in the afternoon sessions, we're going to get people in the water to look good. Perfect. Put the equipment on, test it out, and then have discussions about, OK, what's going on? What do we think? And hopefully begin to come up with some strategies and some messages. You know, that's just the way it should go. I'll look forward to seeing you there. Great. Thanks. Thank you. So this is Craig Thomas, your host on Much More Medicine with Ralph Godo. We'll look forward to seeing you next Wednesday down at the workshop.