Hi and how are you all today? The question says prove that integral 0 to fx dx is equal to integral 0 to a f of a minus x dx. Hence evaluate integral 0 to pi by 2 dx upon 1 plus tan x. So here in this question first we need to prove and then we need to evaluate. First of all let us start with our right hand side of this. Let us put a minus x equal to t. So we have dx is equal to minus dt right? And also when x is equal to 0 then t will be equal to a and when x is equal to a then t will be equal to 0 right? So we have integral 0 to a f of a minus x dx written as a to 0 f of t into minus dt. This further gives us minus a to 0 f of t dt. And this is by property 1 we can write this as integral 0 to a f of x dx which is same as our left hand side right? So left hand side is equal to right hand side and hence we have proved first part for this question. Now we need to evaluate this value. Now here when tan x is written as sin x upon cos x it becomes 0 to pi by 2 cos x upon sin x plus cos x dx. Let this be equal to i. Then i is equal to 0 to pi by 2 we can write it as cos pi by 2 minus x upon cos pi by 2 minus x plus sin pi by 2 minus x dx. Right we know that cos pi by 2 minus x is sin x upon cos pi by 2 minus x is again sin x plus cos x dx. Let this be the first equation this be the second equation. Now on add the first and the second equation we get i plus i is equal to integral 0 to pi by 2 cos x upon sin x plus cos x dx plus 0 to pi by 2 sin x upon sin x plus cos x. This implies 2y is equal to 0 to pi by 2 cos x plus sin x that is what combining these two upon sin x plus cos x dx. This further implies 2i is equal to 0 to pi by 2 1 dx this 2y equal to x these are the limits that we are going to use that is 2y is equal to pi by 2 minus 0 that gives us i is equal to pi by 4. Right so the value of 0 to pi by 2 dx upon 1 plus tan x is equal to pi by 4. Right so this completes our solution hope you understood it well i enjoyed it too have a nice day ahead.


Okay I'm gonna have to admit something to you. I sneak things into the movie theaters mostly because they have bad food options like very unhealthy food options so I usually bring a really big purse and sneak stuff in. If anybody sees my face at a movie theater please let me bring in the food that I have in my purse. I have been known to do that a few times myself. I'm always afraid the person taking the tickets will smell it. They're like sir why are you carrying a purse number one. I think it will be cool for me to get an insight on what their life looks like and then also for us to just have fun together maybe working out going to lunch together maybe feeding the ducks who knows. I lived on the east coast and I was looking for different opportunities. I lived in Key West Florida. Oh nice. Yes on a tropical island. I know right I was security for a private resort and private island. It was a wonderful opportunity but it's incredibly expensive down there you know and and I wanted to explore a few other things in life you know and I've never been out to the west coast so I figured I started looking at moving here and thinking about a change in career so trucking has always had a special interest for me. Yeah. Does it stem from something else like do you have anybody in your what in the world. Bad drivers. Right. My the earliest memory I have is my best friend growing up his father was a truck driver. Okay. And but from there I've always been around trucks whether it's working in a warehouse or having friends that were drivers or something of that nature. Did you ride along with him. I did. Yeah. Yeah. He had one of those old long nose peats. Big loud all that kind of good stuff but it was great. I loved riding in there. And so in my 20s after the military I started thinking about being a truck driver but life happened so. So you went military and then Key West. How long did you serve. Four years. Nice. Yes. Thank you for your service. What branch. I was in the Navy. Oh nice. Absolutely. Do they have a base down there. Key West or just like down. We do. There is a there is a base in Key West. Oh there is. Okay. Which I never actually served there. I did most of my tours in in Florida up in North Florida. Jacksonville. Yeah. That's an area. But I left the military actually moved out to Denver lived in Estes Park Colorado for a little bit. Had a gorgeous. But I got a cabin up in the mountains. Beautiful. Then Halloween night it snowed and it was more snowed I'd ever seen in my life. Right. We had like eight or nine feet. Yeah. And I was like that's it. I'm done when I saw that I'm going back to Florida. I am a beach bomb. I can't do this now. Yeah. So I moved back down to Florida and I went to Key West and lived down there for years and years. Yeah. And then eventually I ended up moving up to Virginia. With some family. Yeah. Yeah. And is it humid up there. Not too bad. In the summer it's a little bit but not too bad. Considering my life in Florida where it's 100% humidity year round. Yeah. You know the weather. Right. For some reason I thought that you were from Hawaii. I just always linked you to Hawaii because of your tattoo. I don't know. I do. I do like the Hawaiian vibe. Yeah. So I lean more towards that kind of tropical culture than I do the Caribbean culture. Isn't it funny how you can be like in your heart. You probably see yourself as like a tropical like beach bomb type of person. Absolutely. But where you are is not that at all.  Oh, completely. It's kind of interesting. It is. But I like that difference that juxtaposition of being a beach bomb living a life as a desert rat. It's so different. It is. It's completely different. But that's why I moved out here is because I've never experienced anything like this. And I like exploring new things and new opportunities. Yeah. You know. I can see that. I decided to do trucking and got to looking around and Phoenix seemed like the best opportunity for trucking schools and trucking companies. Did you initially have your eye on night? Yes and no. It never really occurred to me to work for night. That being said I'd seen night trucks on the road to me. They're the best looking trucks on the road. You know, they're the prettiest. They're the cleanest. Yeah. You know, in every sense of the word. So I've always kind of been partial to night. Yeah. But honestly, I was actually looking at Swift. Yeah. Mainly. And I came out here. Because of their training program you think? Just a bigger company and I knew the name. Yeah. Really. And other than that, I didn't know too much about them. But I came out here. I went to school and my particular trainer was a night driver. So she was always talking night up. And I said, you know what? I'll give them a try. Wait, so you didn't go to our CDL program? No, I did. You went to a school in the Valley? I did. And then you got hired on through Squire? I did. Yeah. Yeah. Am I did my my Squire training? Yeah. It was good. But Mitch Atkinson was my recruiter. Nuh-uh. Yes, he was. How long ago was this? Oh, a while back. Like four years? Probably. Yeah. And I'll be I called him up and or I put an application he called me up. Yeah. And tell me the dirt on Mitch. You see it? You see a good recruiter? He is a good recruiter. Right? He did. Yeah. I dealt with recruiters and other situations before and Mitch took care of it. Yeah. Recruiters tend to get a bad reputation from time to time. Oh, yeah. And I got to say Mitch actually did a really good job taking care of it. It gave me all the good details. But he didn't like oversell and underdeliver like it was pretty. Absolutely. It was exactly what he said. Right. But it was good. But in the overall process, he called me up, looked up my application and said, Hey, can you be here next week? We can get you in. I said, Yes, sir, I'll be there. Never looked back. Seriously. Yeah, you've held a lot of different positions. I have. Night is known for that. Whether it's driving associates or office personnel, like we switch around like crazy. Absolutely. But I think that's a great idea. In terms of people being able to get into different opportunities, see things from a different point of time. I know I had a certain point of view of the office and of trucking in general, being new to the industry and only being in the truck, and then coming in and dealing with the office and their paperwork and how they interact with drivers and all that.  Going back out on the road here again. It's a totally different perspective. Do you feel like okay, what was your when you came into the office? So your first role was DQP instructor or just helping with class. What was the biggest shock? Like what surprised you the most about coming from a driver role to an instructor type of role? I like my solitude in the truck, right?  I'm not exactly a shy person, but it wasn't something that I was really looking forward to. It's not my normal sort of thing. Do you think that's why you want to go back over the road? No. Actually, to be honest, I got into the class and I still remember my first class and the first conversations with with that group and I fell in love with it. Yeah. No, I do love that role. I love supporting our drivers and being available to them. Yeah. But the truth is I look out the window at my desk and I see all the trucks driving by. I talk to the drivers and their stories and I just miss it so much. Really? I love the travel. I love the driving. For me, a personal hobby of mine is to just hop on the road to drive. Yeah. So it's very relaxing. It is. I've always done that like even when I was in high school, when I first got my license, I would just drive around the city and listen to music and try to find, obviously we have a few mountains here in Phoenix, so try to find cool areas where you could like go up an elevation a bit and then see the the lights or see the sunset or see whatever. Oh, absolutely. I feel like being in a truck, you see more. You do. Maybe that's why I'm recognizing all these crazy drivers. A lot of it is that you are physically sitting up higher so it doesn't watch better view. Yeah. But at the same time, I think subconsciously you realize that you're in such a. What does that mean? That is our distance alert where the two bars change lanes in front of us. I didn't see that. Then we were a little too close. Did it push the brakes for you? It did. It did? It did not. I was surprised. I was expecting it to. I have a loner car right now because my car's in the shop and it pushes the brakes for you. Right. And it scares the bejesers out of you. Apparently, I followed too closely. Oh no. If only you knew a good Smith system instructor, right? Probably wouldn't be able to drive a truck if they pulled my MBR. I'm just saying. Uh-oh. Just kidding. I've only totaled the one car. We had to mention earlier that I wanted to get into trucking. Yeah. In my twenties. Yeah. And that was actually why I didn't because I had a robot habit of getting speeding tickets. I love to drive fast. Oh really? And I used to street race and things of that nature. Oh no. Did you have a lot of tickets on your record? I did. I got a ticket about every four months for speeding for several years in a row. And why the trucking company was even willing to talk to me is beyond me. They had fallen off, right? Some of them had. Sure. But I was on my way to the recruiter to sign the paperwork to go to school and got a speeding ticket. Oh my god. So I called him up. I was like, Yes, sir. I am not ready for this. I'll call you in a few years. How long did you wait? I was maybe 25 at the time and I was 35 when I got back into it for some. That's a lot of years to it. It was. I don't think most trucking companies even look back that far. But however, most safety directors would think there's a pattern here. Exactly. That is not good. So I figured I wanted several years between driving on my record so I cleaned it up. Yeah. I wanted to be a driver that truckers would be proud of. I wanted them to see me down the road and go, you know what? I like his driving. He could be one of us. Oh, that's like being accepted. Exactly. And then I became a trucker and realized how bad my driving still was. Really? And how much improvement I could make. Like how, where? Like if I hopped into your seat, what would happen? Like what would be the first thing? I mean granted you don't know my trucking ability or my driving skill set. But what's the first thing that's kind of like red flag? Like you need to work on this. Like I feel like staying between the lane lines would be hard. It can be. Yeah. Especially in construction zones where they twist and turn a lot. But there's a couple of tricks to that as far as staying to the left or to the right. But for me, my biggest issue was following the distance. My thought was, hey, there's a car up there. We've got plenty of distance. I need to speed up and get close. Right? Yeah. And or changing lanes. It never occurred to me that if I want to move in front of another vehicle that I need a greater amount of space. Or like think about how fast they're going. Exactly. A lot of that did not occur to me. So getting into trucking school and then being in a truck, it changed my perspective of that. So now I'm much more open to leaving the space between the LVM. I notice that there's a lot of space always when you're driving, which is very good, especially somebody who has rear-ended someone. I am always open to the suggestion that the vehicle in the lane on either side of me will make an emergency lane change. Yeah.  So that's always my thought behind it. Right? So you just like constantly stay further. Exactly. And even like here in the tunnel we have a curve coming up, right? And let's assume that there is no traffic here. I can't see what's on the other side of that curve. Why would I drive very quickly into it if I can't stop, right? Have you ever driven port? I'm not that poor. I think it would be cool to get home more often. I do like the dedicated. I like the big home on the weekends. I love that we have so much dedicated option now. Absolutely. It's really cool. I just read an internal email, did you see it this morning, about just kind of the freight market going into 2019 and how we're getting even more creative with just making more route options. Right. For what our drivers want. Absolutely. Like obviously that needs to be done, right? Of course. But I think a lot of trucking companies forget like how important it is to just follow suit with supply and demand. Like if somebody wants that route and wants to be home more often, make it happen bro. Absolutely. Come on now. The drivers have so many different needs and desires these days and we can't just say here's one option take it over. You need to be out a month at a time. You can't be, oh sorry no. We don't live in that world anyway. When you drove before you went into the office, what did you like to do for fun and did that change when you started working in the office? For me one of my biggest hobbies is photography. Oh I know that. You take amazing photos. Thank you very much. And I've gotten into drone photography as well. With that. Flying drones around. So I can get those good aerial shots and wide landscape shots. Do you have to have a different like drone for drone photography versus drone video footage? Same drones. You're just taking like a still of the video? Correct. Yeah. So I've got 4k cameras on my drones and they can do video or still. Did you do that a lot when you're over the road? I did. Quite a bit. I don't feel like I saw those pictures. I had a smaller cheaper drone at the time so I'm still trying to learn. So a lot of it didn't come out as well as I wanted. Taking a still of a video isn't always high res right? Unless it's like a really high res video. Usually it is. Most cameras will come out with the same quality picture. But I'm a big believer that I love driving but just as much as I want to be in the truck you need to get out of the truck to clear your head. What's your favorite hobby while you're over the road? Leave it in the comment section below. So photography what else do you do outside of the truck when you're driving? I'm a big movie buff. I love catching the latest movies. Yeah. What do you use? Just like Netflix or? I do Netflix and Amazon. If it's illegal don't tell me. No I don't. I support the film industry so I don't see his illegal sites. Bleep that up. Exactly. And I believe in supporting the local theater. Totally. So it's as crazy as concession stand prices are. I know. I will still go buy my ticket. My $10 popcorn and $10 Coke. Okay I'm gonna have to admit something to you. Uh-huh. I seek things into the movie theaters mostly because they have bad food options like very unhealthy food options. That's true. So I usually bring a really big purse and sneak stuff in. If anybody sees my face at a movie theater please let me bring in the food that I have at my purse. I have been known to do that a few times myself. I'm always afraid the person taking the tickets will smell it. They're like sir why are you carrying a purse number one? Does it get boring though when you're on like I imagine going to Tucson for example. There's not a lot to look at. There's not. However you always have like the entertainment of the what you call them personal vehicles. Is that how you would? I like that. Personal vehicles? Yes. Four-wheelers. Oh four-wheelers. The truck is playing. It does have its boring moments of course. Yeah. But in addition to photography I love music. I have a very deep passion for that. It's almost religious for me. So I can always find some good music to listen to. But just driving in general there's so much to observe and pay attention to to make sure that I'm a safe driver. Yeah. That I find I'm working too much to be bored. Yeah. With it. Like if you're bored that's probably not a good thing because you're probably not doing what you should be doing. Exactly. That's what that's when you know it's time to get out of the truck for a few minutes. Yeah. If you've liked this episode please subscribe to our channel and turn on post notifications.


What up making fun of my warm-up. I mess with this 930 though our first day we were 1230. We're all good We're all good I'm so locked in today. It feels like I'm in a dream Now he didn't see me he didn't see me it was like a transformer at the same time Yeah, yeah, yeah


One of the most common questions I get asked is, you know, how do I start day trading? So what me and my mentor about it for our viewers on YouTube is create a free mentorship course that reveals our 12 secrets that every single brand new day trader should know before they get started. But please take note that there is limited seating every single week. So please reserve your spot at myinvestingclub.co. Link is in the description. Yo, what's up, everyone? It's Harry Ross here. And today I'm just going to be doing another kind of weekly recap going over some trades for the week. And I'm also just going to, you know, I'm going to be kind of brushing over some things that I have kind of like recently been seeing like in my DMs, like one big thing has really been just like people not really knowing what stocks to avoid going long or like maybe how I look at stocks when they first pop up on my radar. So I'm going to be going over some stuff like that. And yeah, just also some general trades. So I'll just get right into it. So I just wanted to kind of just briefly brush over some long traps. I know this may be a bit repetitive because I do talk about this in some of my other videos.   Is this going to be the next big thing? Am I going to miss something? You know, and that is just complete FOMO, right? When you get in that mindset, when you get kind of just in that kind of, I don't know, almost like a sheet mentality of just I'm going to chase everything that's up. If I see green, I'm going to buy, you know, and you're not even thinking about like technicals or a daily level or just stuff like that. That can be very, very dangerous because a lot of the times in main chat, when people say XYZ is popping, it's usually A to alert for a potential short position or B, you know, it's brand new or, or, you know, maybe even C. And this is the kind of rule that I like to say is that if it's a stock that really hasn't been on my radar, but has already kind of moved a little bit, maybe it's transitioned over to the backside, we get that kind of notification. Everyone's saying, oh, XYZ, XYZ popping, bullish XYZ. You know, I usually take a step back and say, OK, let's let's kind of evaluate this for a second, right? Let's take a look at the stock and, and, you know, what is my reason really here to buy it? And a lot of the times there isn't really a great reason to buy it. A lot of times it's under VWAP. Maybe it's a VWAP test. Maybe it is it had made its run already. Some of these stocks are making incredible runs at, you know, five six in the morning. They're making incredible frontside runs at five or six in the morning when I, you know, I'm not necessarily like at my desk trading at five or six in the morning market time, right? And, and that sometimes is the real frontside on some of these tickers. I mean, it used to be like eight o'clock and seven o'clock were early. Now it seems to be that four, five and six are now they're really early moves where, you know, it's either an algo or it's some type of random pump. I don't think most people are awake. So I mean, the buy button at, you know, four, five or six in the morning. I could be wrong. Like I'm not sure. But hey, guys, my name is Toss Bradley and one of the head mentors of my investing club. If you have any questions about getting started in the trading, getting started in the MIC, MIC in general, text me at two, one, three, four, five, eight, five, nine, nine, seven. This is not a robot. It is me directly on the other end of my business line. And we'll get you in the club. We also have special promotions going on that I can get to you depending on your trading needs. Hit me up. Back to the video. Sometimes we'll get these stocks where they'll have those incredible runs in the morning. They, they transition to backside and by the time, you know, it's, it's seven o'clock market time or eight o'clock market time. People have kind of forgotten about them. And, you know, once in a while, we'll get someone in chat that will alert and say, uh, you know, oh, this is pushing. This is pushing. And it's already really on the backside. I kind of say to myself, okay, is this something that I really need to be involved in? And I, I take a step back from it, right? And, you know, that's something that, that you can do is say, okay, well, this ticker is on the backside. You know, there's a lot of resistance we need to get by. There's a lot of fighting involved. I'm going to take a step back and kind of leave these be. And that's something that you can do, right? So a lot of long traps do come when the stock is on the backside. It's so funny because when a stock's on the front side, everyone is, is, is never in a rush to buy it. They see a stock on the front side and they're like, I don't know. I don't know. You know, they watch the stock for 15, 20 minutes. Maybe they have a bit of FOMO. They see that first dip. They jump right in. This is going to be the one. This is going to be the one. And then they end up kind of taking a loss on it for kind of getting in a bit too early, right? And when we get that kind of first pullback recently, you know, it hasn't been working super well, or maybe it's a small pullback. But I mean, and I'll go into like one or two examples of this of three stocks that I kind of avoided today. But I mean, for me, like I just really haven't seen that type of stuff working super, super well. Another long trap that I've been seeing is the lower volume. A lot of the times we'll get these kind of lower volume stocks that seem to kind of start creeping their way back up. They're not really the hot chick. People think, oh, maybe this could be the next one. Maybe this could be the next one and they end up kind of stuffing into a resistance level or just purely fading. And people are wondering why they've lost on it. Well, you probably lost on it because it is kind of a lower volume stock, right? It's a lower volume non-hot chick stock. So it's not something that you should really be, you know, too interested in. It's not something that you should be too involved in. It's not something that you should even really be giving a second thought. You know, I get a lot of DMs all the time. Harry, how come I lost on this ticker? Can you tell me? And I just say, you know, well, number one is that was that the hot chick this morning? And they're going to say, well, no, it wasn't. Then why are you trading it? Right? I made these little cheat sheets. Eventually, I'll probably end up making a textbook just for me trying to like cure FOMO. And of course, they're always for free for everyone. You know, of just me trying to kind of cure FOMO and I'm just kind of bored and I'll take a concept and try and make like a diagram into it. And if people like it, then, you know, it's good. It's yours to keep, right? If it can help you out, then that's awesome, right? But, you know, I made a diagram where it said, and I believe I talked about this in a prior video, maybe two videos ago or my last video where, you know, I bring up the kind of cheat sheet and it says, is this stock the hot chick? If it's not the hot chick stock, don't even bother with it, leave it alone. Right away, don't even bother with it, leave it alone. Like if Alex or Vau or me or anyone else is not saying hot chick on the stock and you just get a random idea that you're like, oh, maybe this one could be the one. Maybe this one could be the one. No, avoid that. Avoid that at all costs, leave it alone. Okay, don't don't touch it. If you're thinking maybe this one could be the one or the classic, maybe they'll rip it. Maybe they'll rip it this time. Who is they, right? Austin had a great webinar. I believe it was his last one. Who is they, right? You know, you can't count on them or they.  Got to be doing good volume, you know, lower flow, maybe some flow rotation. That's better, but if it is a non-hot chick stock, then that's not something I'm looking at. Caputo, no, not looking at it. Another long trap is when something is very under view app. This usually falls in the backside category as well. That's all of our most recent videos right over here.


My name is Brian Wallace. Some of you might know me as Botnet Hunter from Twitter. And today what we're going to be talking about is machine learning and malware classification and its uses and so on. And now I'm going to pass the mic along for everyone to introduce this, introduce themselves on the panel. Hi there, my name is Andrew Davis. I'm a staff data scientist at Silents. My main day-to-day job is training our PE model, so I know a little bit about a feature extraction and different methods like that for training PE models, disassembly, static feature extraction, starting to work a bit with dynamic feature extraction. And yeah, PE is kind of my bread and butter. I'm RetroRang. I'm a principal data scientist at Sophos. I also work a lot on PE but also on other formats including document and HTML, particularly malicious JavaScript. My name is Hyram Anderson. I'm the technical director of Data Science at In-Game. And I work with a great team. We have also primarily PE was our first machine learning model but also we do macros and Mako. Hey everyone, I'm Matt Maisel. I'm the manager of Security Data Science at Silents. I work closely with both Andrew and Brian. And yeah, I guess my kind of interests are more in, again, the nearest neighborhood search if you attended the last talk, clustering, weak supervision, active learning and basically applying those different methods to help basically perform malware classification or help with the pipeline to do malware classification at scale. And if I may, I would like to just briefly introduce Amanda Rousseau who will be joining us momentarily. She's fleeing the paparazzi and will be here when she arrives.  So I'll provide an interesting perspective there. Thank you. So we're going to start out with kind of an easy question for all of our panelists. What do you guys believe is the current state of the art for machine learning and malware classification? Who wants to? You open controversy. Oh boy. I guess I think the current state of the art for malware classification is basically applying deep neural networks.  And then obviously once you have a great model, you actually have to put it in production somewhere. So whether it's on an agent or in the cloud, a lot of the challenges usually come after you make the model. So yeah, I'd say deep neural networks. Again, my kind of expertise isn't necessarily in the classification algorithms. So I'll probably get overturned here. But yeah, so let's kind of start off with that. Just a note. We're not talking purely about static detection. We're also talking about dynamic and any sort of automated machine learning based malware detection method. Yeah. So at in-game, we primarily deal with static detection. There are I think at least two other types. There's dynamic. There's also contextual machine learning. So things when you see a large spike in traffic, right? To a vendor with a lot of hosts that could indicate a new attack where you haven't actually analyzed the file. You only see the number of hatches flying by, right? So in terms of static machine learning, I will respectfully disagree with my panelists. But I think that the way you define state-of-the-art is a Pareto curve. And there's an optimum along that curve depending on what you want to achieve. And that depends on things like obviously false positive, false negative trade-off, but also think about model size. Does this need to live on the endpoint or does it need to live in the cloud? Or think about time required for detection. So in cases where milliseconds matter, like detecting ransomware in a dynamic case, it's often really advantageous to have a speedy, lightweight model that within a few, in sub millisecond time, can determine if that's ransomware. So my belief right now for static, the determination I'd like to make a clear cut that in my research still, there's a difference between ends-to-ends deep learning performance and parse a file first and apply a model performance. That is actually highly related to the next question. And I will move along then. Yeah, so what are the different approaches for feature extraction and how do we represent malware to a model? That is, I imagine something that's new to much of the audience. I guess I've got the mic. Yeah, so I think a lot of the stuff, as far as I'm aware, that's actually in production tends to be static artifacts. And so you have two different ways that you can represent it. You can either use some sort of parsing approach where you do things like you pull out section names or the entropy of individual sections, but it relies on you being able to dig in and analyze the file as a PE file. And then you also have features that don't require any parsing. So you can just get like the entropy of every consecutive 256 bytes of the file or something like that and treat that as a sequence. And you can also, there's research that's been done in convolutional and recurrent neural networks where you just feed the file in a byte at a time or you feed in chunks of the file and it just operates directly on the raw bytes of that. And so I think all of them have their pluses and minuses. There's trade-offs in terms of how much domain knowledge you need to put into it and whether your parser will actually choke on some files and not others and how flexible the representation is. But that's probably the key challenge in getting an effective malware model out is figuring out what the right balance between these sort of very domain-specific expert knowledge required parsing features and the more flexible, less structured, you know, I'm just going to ingest the whole file and it doesn't actually really matter that it's a P file, I'm just treating it as a bag of bytes. So I have a question for the panel real quick. Do you guys believe there is a single approach, like a single model that could be applied to detecting malware or is it a requirement to have multiple different approaches being used in conjunction? Do you mean different file types or what do you mean? File types, dynamic, contextual? Um, no. I mean, you're going to have different problems like Hiram said, right? You're going to have different places where you want to deploy it, you'll have different requirements for latency, for speed, for size of the model and every one of those decisions is going to lead you to a different kind of model. Yeah, so I would definitely agree there's probably not a single all-encompassing model that would work well across all different types of malware. Um, one of the things that I wanted to mention about the previous question about feature extraction and feature engineering is that feature extraction and feature engineering is vitally important to make sure that your model isn't abusable. If you're extracting features that don't really make sense, your model might cue in on things that it shouldn't be queuing in on. Um, and that's not going to be a very good model, it's not going to be a robust model and adversary could find those weak points and exploit them. Um, which kind of brings me around to why there probably isn't an all-encompassing model that would work well on all different kinds of malware because the things that you would use to do malicious things with P.E. are going to be different from the things that you would do to do malicious stuff with health or Mako or any other file format or JavaScript even. So having a single model that just cues in on, you know, yeah, TLDR, no, single model. I will just note there are corporations who do use a sort of single model for all file types and have claims about that. So I would, you know, it's something that wouldn't be great. I should hope they're using transfer learning. Yeah, wouldn't be great. I'd say the only thing that I have to add would be like, you know, obviously each model would be specific to the modality but considering like multimodal models where we're looking at feature spaces from static and dynamic and identity, you know, again depending on how you source, how you're sourcing that data, how you're doing the feature extraction I think could change things but each model could be trained independently and then again, you know, we can ensemble or build, you know, like a majority vote. You know, again, simple ways of basically combining the outputs of different models that are, you know, built for a specific task I guess would be my two cents to that. So onto the next kind of set of questions. What do you guys feel are the biggest challenges in like the field of detecting malware with machine learning? Well, I'll start. I think, again, you can break this down into the different types but in static detection, I think an awful lot of engines still have trouble with packed samples, right? Because packers change, it's hard to track them. The entropy and sections can vary depending on the packing technique used. And at the end of the day, you know, not all static engines actually attempt to unpack before inspecting the contents. They actually use instead of sort of, you know, instead of looking inside the sample and trying to determine a string or signature that would indicate maliciousness, instead they look at artifacts that, you know, the smoking gun, you know, something in here is probably malicious because of the imports and all those things that can't be packed. But that still represents, I think, a weak point for some type of static approaches. Do you want to introduce yourself, please? Yeah, I was actually hanging out with malware tech. Trying to get food. But yeah, my name is Amanda Rousseau. People also know me as Mauer Unicorn. Can you see me back there? I work at Endgame doing malware research. I help a lot of the data scientists kind of tune the machine learning models that we use at Endgame. And we try to look at different types of malware and kind of see, you know, where do we need to focus our feature set on, as well as, you know, determining manual verification if something is malicious or benign. So I think we're still on the challenges, right? Yes. Challenges? Please continue the challenges. Yeah, I think the, so packing an encryption is a major headache. I think the other challenge that's really kind of a big one is just getting a good labeled set for doing supervised learning. So, you know, you've got a lot of repos of stuff that's, you know, allegedly malware or mostly malware.  But a lot of the stuff in there is kind of, the labels are kind of garbage, right? And you've got a lot of disagreement between vendors about whether some samples are malware or not. And so being able to get a good set of ground truth labels that you trust, that you can use to then train these models in a fully supervised fashion is kind of a constant headache. And so finding ways to refine those labels and make them more trustworthy is something that we actually spend a lot of time on. So that actually leads well. Oh, sorry. And to elaborate on that a bit, I think one of the main challenges that I see is that if you're dealing with certain kinds of file formats where you don't have a lot of labeled data, like let's take Mako, for example, you might scan VT for labels or something like that and you might come back with something like 1,000 or a couple tens of thousands of malicious Mako executables. And when it comes to training models that will generalize well, how do you learn anything from 10,000 samples, right? When you compare Mako to PE, for example, you might be able to get a labeled data set of several hundred million malicious PE executables. But when it comes to file formats where sort of like the way to abuse them hasn't been fully exercised like it has for PE, you know, people have been writing malware for PE for decades now. It's a really difficult problem to deal with. So like he said, file format is a major issue because you don't have just file format, you have Mako, Elf, whatever. You also have compiler type. So there's a lot of bootstrapping code in the beginning of a binary that can change your feature set. Say you're focused on the beginning of the binary and you're trying to design features around the malicious part of the code, but you're looking at the bootstrapping code of the compiler. So when you start to cluster PE executables based on just the PE alone, you also need to cluster them based on compiler, a language that they were written in, because all of the calling conventions, even in the malware binary itself, are all different depending on the compiler and what processor it's meant to be. Same with 32-bit versus 64-bit. You're going to have different training sets for those. So you have to make sure that you have those samples in your training set that are labeled properly. I'll just add one last thing to this question. Not necessarily from the perspective of modeling itself, but from building really engineering sustainable model pipelines to support rapid experiments, you know, again, deploying models, getting feedback quickly, being able to make use of feedback that doesn't come through normal channels as well, too. That's a really hard problem, I think, especially when we're considering some of the data set sizes, maybe not necessarily in the class of the imbalanced data sets, but for PE, moving that all around can be challenging and again, quickly building new models, experimenting with different instances of them and evaluating them and then getting evaluation and getting feedback from the field can be a hard engineering problem. So we can move on to the next question now, which I think is going to be kind of interesting. Well, more interesting. So what should we do as an industry of, you know, security folk about things that are only malware in the malicious hands like PSXAC and so forth? If anyone wants to jump in on that. Yeah, I'm not all that. So I think I'm a proponent that machine learning is not panacea, it's not a cure-all. A model should be designed with a specific focus and a question and it can do that well. And if you kind of try to fuzzy your objective, then you'll get kind of fuzzy results. So with that in mind, I think the sort of the tools packages sometimes can be addressed better without machine learning. So looking at common rules of parent-child relationships that should not happen. You can't discover an exploit much more easily than maybe a machine learning package could, for example. So I think there's a lot of room for traditional security concepts to sort of wrap what machine learning provides in a more laser-focused setting. I think just not the binary itself, but it also depends on the context. So one of the things that we focus on is adding another, I guess, feature to the set there is determining how the malware is delivered because if you're using a tool and it was delivered a part of package, whether they're malware packaged inside of a zip file, for instance, in that context, it's going to be probably used maliciously than rather an admin using the same tool in the wrong way. So there's more outside factors to just the binary itself to determine if something is malicious or bad. Okay, so great answers, everyone. So like a lot of machine learning engines applying to malware classification generally tell whether a sample is malicious or benign. How do we feel as an industry or how could we approach naming malware through machine learning or is it really a problem we need to address? Well, you could build a classifier around all the VT detection labels and basically just produce labels from that or generate labels, I should say. But I think there's a lot more interesting kind of machine learning tasks here beyond just binary classification. So multi-label classification or multi-class classification could be applied here. I guess this kind of maybe goes in the realm. So I just to clarify, binary classification, he means one or zero, not like... Benign or malicious. Yeah, but benign or malicious, not like raw bytes. Yeah, thank you for that clarification. I think other areas too, especially because again, I grew up in a sock working as an incident responder so I loved having tools that enabled me to do my hunting better or do my analysis better. So applying things like nearest neighbor search or clustering for customers and even internally, I think it's really helped us out. So yeah, I guess I think there's more beyond just or again, beyond binary classification on things being malicious or benign that could definitely help out. And maybe this gets into model explanations as well too, but I don't know if that's a question later but I think that's also a very interesting area too, model interpretability. Yeah, on that front, that's one of the reasons why at Sophos we're so deep in on deep neural networks as opposed to some other more structured classifiers simply because you can put a lot more flexibility into them and so you can do things like give me something that will not just say, is this malicious or benign, but is this malicious and if it's malicious, is it malicious because it's Pua or malicious because it's a virus or malicious because it's ransomware and you can even put things like family labels into it. So you can build a whole lot more flexibility in how you want to slice up your space of your malicious and your benign samples and sort of enrich your output in that sense. And then also, gplug, blackout talk, we have found that using sort of the internal representations from these deep learning models actually is a really useful analytic tool to take a look at sort of how these different samples can be grouped together in space and maybe suggest other clusterings that might relate more to functionality rather than to authorship similarity and things like that. So I think there's definitely, and I think we're just sort of seeing the beginning of this, there's definitely a large role for these machine learning models not just as tools of classification but also useful analytic tools that can be sort of handed over to people that do more conventional malware analysis to them in this sort of virtuous cycle. So I think as far as auto classification, taking a machine learning model and having it take a binary and try and predict what kind of malware a family belongs to is a pretty good idea and a lot of people do it really well. However, I think we will always need malware analysts in the loop. We're always going to need humans to validate these results. We can't just be automatically classifying things and be asleep at the wheel. So I'm not super sure if it would be a great idea to have machine learning models that do things like automatically come up with new family names and things like that. For one thing, it may come up with something that's not entirely meaningful in the name because malware family names, there's often like some, you know, maybe signatures being like all over the place? Never. Yeah. But yeah, just having a human in the loop to give a specific malware family name a meaningful name is, you know, that's always going to be important. From the malware analyst perspective, it's the data science job to help us bubble up the important things for us to resolve, right? So, you know, a lot of traditionally the malware samples were identified by someone giving it a cool name and saying a children something, you know, wanna cry or something like that. But really, we, you know, if we kind of went back to the whole biology part of it, we classify that it actually does this certain behavior or has a certain property, rather than just giving it a random name and calling it a certain class, that would help us a lot better because we would need to figure out how to get rid of the malware itself, but the only way is if we knew what type of behavior it did so we can remove it. And I think that's one of the major problems that, you know, data science tries to resolve is like there are heuristics based on behavior properties that could be more helpful than just a generic family name that someone threw a dart on the wall and decided to name it. I'm just gonna lead into the next part because we're a little bit over because we started late. What do you guys feel is the future of malware classification without burning intellectual property? Does no one want to touch that? So I think from the sort of machine learning perspective, the amount of data that's coming in day over day is growing really fast so there's a lot of challenges for us to overcome, just unlike the engineering and the pipeline end of things, but also being able to sort of put analysts more tightly into the loop and sort of engage that feedback loop and maybe bubble up stuff that's suspicious but hasn't been assigned like a family name or something and hand that over and get a final verdict that's suspicious or is it benign? So being able to get more and sort of focus more on an active learning type problem where you're putting humans into the loop and you're learning how to sort of spend analyst hours most effectively to supplement and improve your machine learning, I think is a really promising direction for the future. I'll just add that I think of everybody I think represented on the panel, we rely maybe to an embarrassing extent on traditional AV to supplement our labels. I agree. It's really an important thing but they also rely on each other. But these labels don't come for free. We put in human effort but there's also automated effort in there. So one thing to think about in the future is if everybody moves to machine learning then from whence the free labels so there's a conundrum here that reliance on the human is going to become more important or I think that a really hot research area is not in supervised learning of machine learning models but in unsupervised and semi-supervised machine learning models where the reliance on labels diminishes I have a strong I'm strongly in the opinion of using active learning I'm a big fan of it. I guess just kind of go on top of that I would say there's a really interesting project called Snorkel that's a framework for doing weak supervision so specifically in the case where there's labels of all these different types of malware and maybe we're getting like heuristics or signatures from analysts weak supervision the task is basically to try to combine all of those labels in a way that overall improves another model later down the road and this project Snorkel I think it's Hazy Research Group I can't remember the author's name right now but they have a great tool it's kind of more built around weak supervision so combining all these different labels from different kind of mechanical turks specifically for image classification that could be potentially extended to help with some of the problems of taking really noisy labels and also taking account of external databases of signatures or heuristics that might be useful for influencing the model so I'm sorry we have to stop now we're over time but thank you for all the panelists great answers to all the questions super happy to have you all thank you everyone for coming


Thank you. I mentioned that collapse that project I'm afraid and the in the So I'm not talking about the eurozone instead What I would like to do is I have 20 minutes and I would like to explain I mean people will see I look at me as a pessimist. I'm actually not that's actually not a true a true statement I'm reasonably open about About all the all the prospects what I see there are I would think there's sort of three strands which which which I see Ultimately tell me that this thing is unsustainable It doesn't mean it will collapse. It means that something will have to change can collapse But that you know all certain conditions can change to make it work But there are three things that are that I find ultimately unsustainable or that in their combination Produce an unsustainable mix. Let me start off with the first one, which is banking the eurozone has seen Or Europe eurozone banks have seen a number of successive crises each of them would have been a very big a very big Issue for them and a problem for its balance sheets. The first one was the US mortgage crisis, which wasn't even a domestic one But obviously during that period there was also bad that accumulated through bad through bad lending In the housing sector like as happened here in Ireland and in Spain So there were problems arising from that period. We've then had You know the beginnings of the Greek crisis This has resulted in in the restructuring of Greek debt that was certainly a a factor of problems for the for the banks In cases like Germany with with decade a decade of current large current account surpluses that were invested abroad Or shall we say capital account deficits that Germany had the Germany had to You know digest those You know, we don't know exactly where all this where all these investments went But I would assume that a large amount we know it from some of the banks were funded or were invested in in securities with a very dubious dubious pedigree and There are large hidden hidden hidden losses in those balance sheets and in the German banks We know that the French banks are in some in some difficulty more than what has generally been Been been acknowledged. So you have this combination Of crisis we have Cyprus. We have obviously a recession Normally any recession is a problem for for banking saying these are not just any little This was a double dip recession with the 2009 recession followed by yet another one and one in Spain And that depends very much on the outlook, but it doesn't look, you know, it's gonna end that soon It will it will last for this entire year. So this cumulation It's a cumulation of of shocks and losses will have produced Losses on balance sheet that would be that would not all be visible at this moment. You can make your estimates We don't know what it is the ECB will conduct what it calls a asset quality review in the in the first quarter second quarter of next year this asset quality review is meant to Honor some of look at these balance sheets in some greater detail But if you look globally the eurozone has 25 a balance sheet total eurozone banks of about 25 Trillion you take out the central banks that leaves you with 24 trillion Get very rough take or leave a trillion. That doesn't really matter ultimately If you're dealing at that scale if 5% of that is under water, which isn't in all that extreme estimate Then you come up to about a trillion a Trillion in hidden losses now that doesn't mean that you need a capital of a trillion because some of those losses could be funded by Existing capital, but it would probably given that the European banks are in general not over Capitalized and with two generous buffers, you know, it was a fairly significant part of that Would have to become we're raised in your capital now 5% is just the wild gas. It's a wild but conservative gas You know if you've seen as an exercise in Slovenia Where the central bank has actually looked at the banking system and they came up with a number of 19% of The assets of Slovenia being underwater now that may not be indicative of the average of the eurozone I would not you know, we cannot extrapolate, but it can easily be that if you are in the country where Where things went wrong in that period things could you know, there could be quite a The the the assets that are underwater could be quite could be quite sizable So we're looking at at a very large recapitalization need for the eurozone banking system That I don't see that the eurozone is not going to raise anytime soon They're presenting a banking unit and I will talk about the banking union in a moment but the the There is no realization among the countries this painted an exercise of an asset quality review They invited outside consultants that came up with a number ultimately that led to a recapitalization of 40 Billion the Spanish banking sector, I would have estimated the sum at least five times as much But it seems to be the political the way this works politically is that the governments don't want to recognize these losses because Because they want to maintain that they have a solid is maybe out of out of pride or maybe even out of you know Recognizing a 200 billion loss would have reverberations on the government if Spain had accept accepted that its banking system Were broke. Well, Spain might might already now be a full a candidate to be for a European rescue program because it would not be able to fund itself So, you know, we should not trust governments in general to to be honest about these exercises And in the way the eurozone works and the way these stress tests have worked this works through national regulators through national supervised This is not a truly independent process so My first conclusion is that we have a banking sector that is largely underwater I don't see it's it's likely to be fixed because the national interest will prevail over the over the common interest in fixing this banking sector And also in the realization that we don't have the institutions in place to fix the banking sector That's we haven't we haven't we haven't basically created there, you know, we don't have the trillion basically This is something which needs to be provided for and isn't being provided for The second reason for my pessimism is the you know, it's the macroeconomic policies In particular the way we have Applied austerity Now, what some people say austerity may be over. It isn't really over what we're seeing Italy is a good example It has applied severely significant austerity in 2012 and 2013 But now the government comes in and says austerity is over. There's a tax They will they will take back but they will increase the other another tax just compensate exactly compensate whatever is gained by But not rare by by by by suspending one tax Because the goal the ultimate goal of a of a nominal deficit to GDP target in Italy's case 2.9% is unchanged So, you know, if you call it austerity three months ago, it's the same policy.  There are different implications in the long run. There may be fairness implications But if you want to assess the impact of austerity on on growth It's it's it's not going to be the big difference if you take if you take the money away from people It doesn't really matter from whom you take it away The the overall macroeconomic impact is the same if you look at the economy of the eurozone It's often easier to look at the eurozone as a single economy If you look at it as sort of a series of states that are bound by some exchange rate regime It becomes very complicated but if you look at the You know the economic literature is fairly clear about about the impact of austerity in large closed economies The eurozone is a large closed economy with characteristic that's similar to that of the United States And you know, since we all apply your austerity is not applied at one country level and not anywhere else And since everybody has the same policy because of the fiscal pack because of the fiscal rules everything we do is symmetric Even Germany implies a degree of austerity at the moment So that combinae this combination of policies means that the so-called fiscal multiply in What I have to add in the presence of a zero interest rate where we are in a liquidity trap that that the presence of a Of a of an austerity policy means that it had the impact on growth is very significant Technically the multiplier is greater than one That means for each for each you know percent of austerity you lose that much in growth Because you take the money you take out of the economy is not compensated for by by other policies normally Interest for in response the private sector could could could consume more or invest more So they the effect would be somewhat compensated. That is not the case at the moment So if you apply austerity in a situation like that You get you get a very significant impact of growth. That's what the economic literature would tell you and it and it was Denied in the eurozone that this would would happen, but it happened and exactly you know We haven't we have seen in the last in the last in the last year a an economic response That was entirely predicted and predictable that austerity would have that effect And while we are now loosening it a little bit because in 2014 there won't be any net austerity Applied at the eurozone level though. We're not taking it back. It's just a level and and a level effect So we're gonna stick to this there will be additional austerity in the years 2015 2016 when the new fiscal pack that everyone had Signed kicks in because the new fiscal pack compels countries not just to keep their deficits low, but actually to repay debt If they're debt to GDP levels are over 60 percent, which is the case in most countries so that a percentage of that excessive debt a 20th of that excessive debt has to be repaid every year basically meaning that Countries would have to run excess fiscal surpluses simply to repay that debt now that People may hope that this this might be suspended or reinterpreted But that's what the fiscal pack says and it would require a you know It would require a fairly tight fiscal policy for the indefinite future if we I'm skeptical what it what it tells me that that even if I'm not sort of Even if I don't believe that the look even if we believe we get out of the liquidity trap And if we believe that things normalize in the global economy It means that the government will remain a restrictive influence on growth You know, it will not be a positive that that's a that's a forecast. I'm fairly certain certain of making If you combine that with my first observation that we have a fairly restrictive environment for growth With a dysfunctional banking system that is unlikely to provide credit because banks that are underwater are not going to expand the asset base They are restricting the asset base. We're seeing credit crunches in various parts of the eurozone In place that means we're going to look at a decade very similar in some respects to that of Japan in the 1990s of low growth With sort of as they call it the zombie banks is a large banks that are not that are That are there but they can't really act they can't really fulfill the economic functions of a healthy banking sex sector, but they're not They're not being wound down because governments are afraid of doing so because they're vested interest by politicians or or other other concerns About the consequences of that such a policy has so that scenario is already puts us sort of in a low growth Equilibrium now what could potentially solve the situation would be a genuine banking union and now we're coming to my third My third category of issues why I'm skeptical and I was briefly optimistic in the summer of last year when the European Council agreed the principle of a banking union a fiscal union and sort of a long time scale and I said okay It might not be fast enough, but at least they're going in the right direction But what we're seeing today is the banking union is not it is still called a banking union, but it doesn't fulfill The economic functions of the banking You know have the first agreement was to shift the supervisor for the large banks from the member states to the center That is an important step, but it doesn't change just the fact that someone else is supervises the banks Does not in the you know does not change any of the problem that we that we just identified the second Step that was taken was a harmonization of resolution rules. That's very important because if you step into another country's but you know Assume the ECB or whoever is going to be then the new resolution authority came to Ireland closed down a bank Obviously that had to be done under Irish laws No, there are insolvency laws their employment laws that tons of laws that affected So we need to we need to harmonize those laws in order for this sort of cross-country resolution to happen The third step would have to be a resolution authority We have to create an authority that actually does this that actually goes in to a bank on a Friday afternoon Merges it with another bank closes down does does something, you know basically to you know Something that isn't normally done in Europe Which is like closing and closing down a bank that isn't profitable if we believe that's going to happen that needs to be a very strong Authority that is backed by law that is you know It's going to be interesting to see how they're going to pin this under under the current legal system The main debate in Brussels is about whether the European Commission should do this or whether there should be another authority It seems to me that Germany that's my the information wants to prevent Absolutely that the Commission gets involved in this so there's going to be a typical Brussels into institutional fight that we're gonna that we're going to see in the next few weeks and which kind of deflects our attention from the Real issue because it doesn't really matter who does it the question is it that it needs to get done We need to we need to resolve the banking sector if we feel there is a billion a trillion of unresolved Losses in the system. It needs the job needs to be done And obviously there needs to be a fund to do it and the moment the fund that the Finance ministers are discussing is has an order of 50 to 70 billion Probably at the even at the lower end of that range And that is not going to be enough. That's not going to be enough to you know to deal with the fundamental Issues and because the fund is lower than the needs what I suspect will happen is that the needs will not be fully recognized This is what we've seen in Spain as a there was clearly a Banking system that's underwater. We see the bad news coming out instead of instead of trickle terms at the moment We see every day that's some some bad news about banks some unresolved issues And now the government admits that the recapitalization has to be a little higher You know and that was already you know an exercise that was you know this exercise They they had an independent quality review They looked at all the balance sheet that came up with a number then they did all sorts of manipulations and then came up with a number of 40 billion in in you in US I expect something similar to happen on the eurozone They will probably come up with a number with a number of hundred billion or 200 billion in terms of new capital That to be shared between the government and the ESM some some kind of coordination and bail in through shareholders, but it won't it won't exceed that level so you know The shareholders bondholders depositors will get bailed in in some cases Governments will co-fund at the ESM will probably spend its 50 to 70 billion Budget on it. So we're probably looking at a at something in the low three figures and that's not gonna That's not gonna be it's not gonna be sufficient So this banking union is not gonna resolve the eurozone banking crisis And then your way you were in a situation that can potentially last very long We can be in a situation that you know that can last a decade at the end of which it the eurozone can continue to live And it doesn't mean it doesn't even Forcibly say it's gonna break down. It's dysfunctional But it doesn't mean it's gonna break down because a breakdown would require would assume that whoever leaves it Would perceive it to be in a better position by leaving it. I was not necessarily to the case We've seen greed even the Greeks who who you know who I cannot see their future in the eurozone and Even even after my even starting today having gone through what they did I still see it's not it's not it is not working But even Greece is not gonna leave even not even the government there with all its unpopular measures It still has a majority in the in the opinion polls So, you know, it's gonna take quite a lot for country to conclude that it it's better off Outside the eurozone with all the political risks now because there's always the possibility that you might have to leave the EU Depends on the you know the legal interpretation of the day whether that is necessary or not But there's certainly a risk about the countries and then unless it is a big country You know, I would assume most small countries would be kind of intimidated to even try this experiment So this thing could could last long but the worst outcome is not necessarily a break of the worst outcome Could be a survival under sort of a permanent crisis You know if a station of social unrest high unemployment You know leading to a point in some kind in the future where Where there may be sort of a violent social eruption an alternative scenario would be a Changing policy because well possible. I can't exclude that Germany at one point and other northern countries say This isn't working for us. We need to really change it and you know, let's do this We denied the nest we denied the need for a euro bond But now we've had you know the crisis now in year number 15 It's probably time to realize that it probably our crisis resolution polls. They haven't been all that successful Let's do what we should have done 15 years ago and go for it. I can't exclude it I think it's unlikely given the way the debate has been going in in the northern European countries But who are kind of conflicted because they want the euros to survive There is no majority for break up of the euro if you look at the opinion polls They really want it but they don't want to do the things that are necessary for it to survive So it's an interesting how they resolve their own their own internal conflict And which is also part to do with the with their own narrative crisis narratives now I mean if you talk to the average Germany The people would say that the crisis is because the governments have been irresponsible Which doesn't really explain what happened in Spain doesn't explain what happened in Ireland It doesn't really explain much even Italy cannot be explained by that Greece could be explained by that But that's you know, so the crisis narratives are very much part of the way How these sort of this contradictory set of views has been Has been has been has been formed so I'm not making predictions about the eurozone, but I'm just saying it's unsustainable and You know as a famous American economist or economic advisor one said what's unsustainable will stop one day It's just we don't know what will stop what element will stop and I'll stop now. Thank you


Hi everybody, Sean with jaspyscasebreaks.com and jaspys.com where you can get personal breaks from us doing some late night early morning personal breaks. This one we're going to be doing a 2017-18 Padini Prism cello pack break. Two packs this time for Fayaz. He's already picked out the packs for himself. Here they are. So we'll get ripping and see what we've got. Yeah, exactly. Obviously looking for Jason Tatum in this. Tatum, silver, color, all that. All the above will be good. Good luck, banger. Yogi Farrell. The song White Side. Reggie Bullock and Corey Joseph. Starting off with a coach card. Tyron Liu. Sean Kilpatrick. Robert Covington Silver and Carmelo Anthony. Yeah, somebody said something about it. I didn't feel it, but I thought it was in downtown LA. 4.5 on the Richter scale. Marcus Smart. Earl Watson. Joe Johnson. And Nicholas Batum. We'll do the regular packs on this side and then we'll do the silver, I mean the extra pack. Is in Pacoima. Maurice Harkless. Mike Mascala. Dwight Powell. Silver. And Nicola Moritit. Jeff Teague. Wilson Chandler. Wes Unsold. And Chandler Parsons. That's possible, Jesse. I have the sugars, that's for sure. Definitely had the little tingles going on in the skin. Dwayne Casey. Quinn Snyder. Steve Kerr. Coach Silver. Not what you're looking for. And Paul George. Let's hope that he shows up in these, the extra pack for you. You got Al Horford on the front. Torian Prince. And Michael Kidd Gilchrist. Not the names we're looking for. I know, banger. I think 17 was the last year that they did coach cards, luckily. And money. Alfred Payton. Emmanuel Moudier. And Deontamurray. So no Tatum or Mitchell in that, but thanks for giving it a shot, Faiz. That was a personal break for Faiz. 2017-18, Panini Prism, basketball, cello pack breaks. I'm Sean with jaspyscasebreaks.com, jaspys.com for personal breaks, and we'll see you guys next time.


Russia loses up to 30,000 killed and wounded near Bakhmut. Between 20,000 and 30,000 Wagnerites and regular Russian forces have been killed and wounded in the battles for the city of Bakhmut since May 2022. Ian Stubbs, senior military advisor of the UK delegation to the OSCE during the meeting of the Forum for Security Cooperation in Vienna announced it. Over the past week, we have seen intensive combat as Russia continues its grinding offensive in Donbas. Russia is suffering extremely heavy casualty rates. Since May last year, between 20,000 to 30,000 Wagner and regular Russian forces have been killed and wounded in the area around Bakhmut alone, a huge loss of human life for a total territorial advance of approximately just 25 kilometers, he said. According to the British diplomat, it means that is over 800 Russian personnel killed or wounded for each kilometer gained, the vast majority of them Wagner fighters. In the face of these losses, Wagner group owner Yegevny Prigozhin is finding it increasingly difficult to replenish their forces due to what he has termed the meat grinder in eastern Ukraine. Separately, Stubbs indicated that judging by everything, Russia is running out of its missile reserves. This is evidenced by the increasing intervals with which Russia strikes Ukraine's critical infrastructure. According to him, the issue of providing the Russian troops with equipment is just as urgent. Russia suffered huge losses of heavy armored vehicles, which forced it to deploy 60-year-old T-62 main battle tanks to the front. Since the summer of 2022, approximately 800 T-62 obsolete tanks have been removed from storage. More recently, Russian BTR 50 armored personnel carriers were also deployed in Ukraine, rare vehicles that were first adopted by the Russian Army in 1954.


What's up everybody Jason Rajasby's case breaks calm 2021 panini XR football seven box half case break picking teams number one Just sold out and I got two autographs one really card one insert four parallels and one-on-one autograph per case So looks like you at least get one of those So there you go guys, so here's everybody that has teamed straight up So thank you guys here. We only had to put up a little R&B for like the last seven I believe And then the rest of the team that didn't sell which was Jacksonville Tampa Bay, Kansas City, Arizona Green Bay, Minnesota Indianapolis and Vegas We're sold random number of lock style right there to these customers So good luck to everybody there. And again, this is a XR football case This is a half case break to only seven boxes. So the second half of course will be used for The next pick your team, which is also sold out Dude, Brody When I had a man, I had a rough cough that literally wouldn't stop all day and night and even when I was Clear to cope it after two weeks I Had that similar cough Throughout the next like two months. It really took a long time for that shit to go away And that's what my doctor that said to that the cough sometimes if you get a lingering cough It's just gonna it's just like it's gonna happen for months, but it'll eventually go away At some point I was just like coughing but not coughing anything, but I just like, you know All right, so one two three four five six But yeah, I didn't lose my taste buds either But not that I was hungry anyways, I was like 30 pounds one two three on the left So these right here would be for the next pick your team and I'll put a little line through them. Let's see some XR XR is actually really become a fan favorite. It's really not a bad price point box And people do tend to like hits Little Najee Harris to start us off Calvin Rudley insert Cousins we have a famous Janus very nice little color match right there Out of 75 for the Saints Levi to 49 for the Lions. That's actually part of the random number block. No miles actually got that straight up You got extra extra extra extra Raiders 59 out of 99 Raiders are part of the R&B spot. I'm gonna ride a hero extra extra And a Gary Brightwell to start us off to 49 he goes for the Giants and Josh Got the first hit for sure man. Well, the good thing that is that you're Pretty much at like a week. So You know, you'll hopefully start feeling better soon But you know, you pretty much got the first, you know, five six days off. So Of the symptoms at least Patrick Mahomes, there you go. That's a nice color match 140 to 249 That's a nice Mahomes right there Travis ETN for the Jaguars That'll be randomized or put in the R&B. Sorry one 88 Robb with that Pat Friarmouth To 75 a little relic for the Pittsburgh Steelers. We have a redemption Andy and Mari Rogers base base and actually the chiefs is part of the R&B 140 It's about zero. That's going to Raymond. So so far. We've actually got some hits for the Random number block just base cards, but again, there's Patrick Mullins about actually sell for more than some autographs So actually that's Patrick Mullins is actually really not a bad hit So far these three right here and then ETN eight zero and nine Show me We got here rookie XL swatch autographs red card number for Kyle pits Let's go Brody back to any of your Kyle pits redemptions There you go for the ATL a little sick, but Hit still keep coming through Very nice first box in the book boom Next one Trevor Lawrence that is not numbered so that'll be randomized to everybody in the group of the R&B That's probably a nice little trouble aren't you out there? Maybe 20 bucks 25 bucks. Maybe something like that So Michelle Mike Evans, Jair Alexander to 249 that's gonna be for Green Bay and That's part of the R&B as well. That is 102 It's about to that's going to Patrick Gregor was so For the bills Oliver, we have a extractor material could areas Tony That is for the GMN and Josh Anthony Schwartz to 199 for the Cleveland Browns Patrick Davis Little Devontae Smith for my Eagles Chris Maxwell. We have Travis Kelsey. That's gonna be a non-numbered base right there Marquis Brown Baltimore Ravens Calvin Ridley that is number 799 and a Frank Darby another one for the Falcons back-to-back for the Falcons And we had extreme rookies 37 out of 49 the Kansas City Chiefs spot 7 that is going to Joe Howard R&B style there you go and we have a William Perry for the Bears to 49 Acclimated autographs bears and a John Jay box two out of seven in the books Next one two to two Justin Fields for the bear. That's a very nice one right there. Yeah, Jaylin or Xavier and Howard Tyler Boyd We have a Julio Jones for the Tennessee time That's 20 or 18 out of 49 and then for the Washington football team John Bates Number to 249 Cornell-Polle a little relic there. That's 25 out of 75. So that'll be going to swap five and Josh R&B Josh Palmer to 25 little Jersey autograph for the Chargers going to Jeremy H Here we go. Next one. We have a Bentham in St. Juiced. We have Miles Jack Julio Miles Jack will be over there. 49ers George Kittle to 49 49ers there and a nice Trey Lance That is 94 out of 99 Extra extra, Aaron Donald Back to Davison. Whoa Uno of Uno, a printing plate patch autograph of Amir, Smith, Marcetti Minnesota Viking that's part of the R&B big dog Rob. There you go Little Uno of Uno Very nice. Pretty much halfway there guys. That was box three Halfway through box four will be the midway point. So Still plenty of hits out there. No need to panic. Play to the whistle. Play to the whistle Smith-Marcetti Big Ben Braden Cooks, Josh Allen for the Bills Oliver to 99 and Pena Sue Will 49 It's been outstanding. Dwayne S. Ridge to 49 for the Seahawks Chris Maxwell and Davis Mills little patch autograph Houston, Texas and a Jerry Kyle Trask for the Bucks Derek Henry Joey Bosa Brian Burns for Carolina 289 We have Owa To 1.99 and vintage moments to 1.49 for the Dolphins Deported that is Dan the man marina. We have for my Eagles Canada Gainwell luminous endorsements 18 out of 25 Little orange color match as well Fly this fly Chris Maxwell. Maxwell guys Andrea Cisco Jaguars Stefan digs the under swift Tredavious whites to 2.49 You have a mantra same brown to 1.99 a mantra x-ray That is numbered 18 out of 49 Detroit miles with that one and core now. Oh, wow little triple relic and autograph to 75 And that is 26 spot six going to add a couple in Jaylen water rookie. It's nice for that for the Dolphins TB 12 can't go wrong with a little base. That's probably gonna sell for Just as much as a cheaper autograph. Probably if not more Remember that'll be randomized as well Toby kill. Yeah, Brian Burns Yeah, for the Eagles kind of game. Well, you have vintage moments Barry Sanders numbered 42 out of 1.49 and Patrick Sartain Very good DB for the Broncos 8 out of 99 Deborah Broncos went here. All right, the last two here guys. Good luck. He's right there Eric Stokes for Green Bay Jaylen Hertz Rogers Jarvis Landry to 2.49 Davis Mills to 1.99 and Trevor Lawrence Little x-ray 46 out of 49 The piece of the jersey spot six went out of cuppermen And a Javonte Williams 2 out of our star 7 out of 25 for Denver Three-color patch as well Denver that's going to Harry Jaylen Darden Rob Ramkowski, David Montgomery got a little Kirk Cousins To 99 It's from Minnesota 38 and then 143 out of 249 Wangu So those are numbered there for Minnesota back-to-back R&Bs And very nice not much Tom Brady can get out of here, but we did get a Vintage moments Tom Brady and that is a Patriots edition And that is 38 out of 49 Patriots that's going to John Which is a really nice here right there And what do we have here? Celebrations autograph Richard Sherman for the 49ers Alfonso, there you go. It is Not numbered but a very nice thing Like that insert. Alrighty guys Last one here Remember the second half is already sold out. We'll be running that back right after this Josh Palmer Let's actually keep this last usually that's the patch autographs and stuff I don't think there can be two patch autographs, but still Mac Daddy Jones It is now Ryan. It is now Good luck, man Zeke Tyron Matthew Scary Terry McLauren To 249 We have a Aaron Robinson to 249 And 83 out of 99 Brett Fabre Little far vintage moments Vince Young Wow, I wasn't expecting that guy Because first like couple years in Tennessee the rookie of the year. He had some great great plays early in his career Two out of 10 Tennessee Titans going to Brooks. Good luck guys Darnold Winston Ryan Tannehill Travis ETN 188 out of 199 The Jaguars 88 going to Rob spot eight Last two hits here guys. Good luck We have a x-ray 40 out of 49. That is Justin Fields We do have a Jaguar guys Coming up so it's gonna be for the right of normal lock last hit Last hit is a Travis ETN That is a jersey autograph and that is serial number 36 spot six Adam coverman That damn upside down nine Ryan. Alrighty guys and boom boom. That was the break so So my knowledge these were all the unnumbered cards for the random number blocks Right there a couple nice quarterbacks right there So these is actually probably not too bad You got a rookie quarterback here called Trask So these will all be randomized to one customer in one lot As a little added bonus to the random number block and again, we got some nice hits so far I think the second half will have some really really big rookies But nice to be seen young right there Richard Sherman was nice John T. Williams three color patch Patrick 15 again, again, well Davis Mills Josh Palmer We have Willem Perry Anthony Schwartz Kyle Pitts was a nicer redemption early on Brightwell And then for the random number block, this is one of the hits that they got here numbered wise at least Some number block actually did pretty well a lot of nice number cards Only a couple of hits as in the autographs like the Travis ETN, Trevor Lawrence Relic, Norma Pawell One of one was really nice Cornell Pawell And there you go. So these will all be there for the random number blocks. Let's quickly Switch scenes and let's uh, randomize that non numbered cards in one lot really quick Dice roll Six and into two eight times one two three four five six seven eight Boom Eight times six into two. Congrats, Josh You're gonna get all the unnumbered cards including that bass, Trevor Lawrence, Brady and Patrick Mahon Which is not too shabby, a little extra right there Appreciate it guys. Number two sold out. We're running it back straight up


Let's take a look at card number 27, card number 27, the French connection, the French connection. Who is this guy? What is the French connection? Who? Let's see if we can get this thing focused. Who is this guy? Mesmerizing, eh? Mesmerizing artwork. Jean Soutri. Jean Jean Soutri. Jean Soutri. Let's check this out. What do we got? After Canada's death, same text. Canada, Mexico or to Canada, okay. Wenjak Ruby, cool. And then William Harvey, we got at the bottom. Is Jean, yeah? Oh, a little bit of text difference there. Something, Jean. Oh, it changes a little bit. We're going to read the revised version, just because some wording might be more important. So this is the original version released in 1990. This is the revised version released after all the Stones movie from 1991. This was released in 1992. So let's read card number 27, Jean Soutri. After Canada's death, French intelligence asked the FBI to help locate Jean Soutri, a French secret army organization, OAS, terrorist previously jailed for attempting to kill French president Charles de Gaulle. According to a CIA document dated April 1st, 1964, which surfaced in 1977, the French claim Soutri was in Dallas on November 22nd, 1963, and was expelled by U.S. authorities 18 hours later. Concerned with security to the Gaulle's upcoming Mexican visit, they wanted to know whether he had been sent to Mexico or to Canada. When Jack Ruby was jailed for killing Lee Oswald, his lawyer asked them if he knew anyone who could damage his defense. Ruby mentioned Thomas L. Davis III, with whom he had run guns and jeeps to Cuba. In 1963, Davis, while on prohibition for bank robbery, obtained the U.S. passport. By December, he was in Tangier's jail, charged with running guns to the OAS. According to the FBI, Moroccan authorities intercepted a letter from Davis that referred to Lee Oswald and the assassination. Davis was apparently released from jail through the efforts of a mysterious CIA agent codenamed Q.J. Wing, W.I.N. described as a foreign national with mafia connections who was recruited for the Z.R. Rifle Team, a CIA assassination unit run by ex-FBI agent and Cuban ex-op handler William Harvey. Something Jean Sutri was Q.J. W.I.N. when, in part because OAS terrorists were involved in heroin trafficking and in 1963, the main American distributor of French heroin was the lucky Luciano Syndicate, run by Meyer Lenski and Tampa mafia boss Santos Trifacante Jr., formerly of Havana, who was William Harvey's partner in the CIA mafia plot to murder Fidel Castro. Wow. So many connections. Crazy. Crazy. The French connection. Always a cigarette in their hands.


From Hollywood it's time now for Johnny dollar Mrs. Galen, I think mr. Welch told you I'd be around to see you Oh, yes, you're the special investigator the insurance company sent out. That's right. Mind if I come in All right, mr. Dollar. Thanks And through here Your company didn't waste any time did they sending you out here? I mean no no more than you did and filing your claim I have a right to it with Eddie gone now. I need the money I see sit down. Thanks How many keys are there to that door keys? What do you mean your front door? How many keys do you have? Just one Of course Eddie had one. Why what difference does it make just about enough difference to hang somebody? cigarette, Mrs. Galen Tonight and every weekday night Bob Bailey in the transcribed adventures of the man with the action-packed Expense account America's fabulous freelance insurance investigator does truly Johnny dollar From special investigator Johnny dollar location, Los Angeles to the home office Trinity Mutual Insurance Company limited Hartford, Connecticut Assignment the Kailin matter expense account continued Quite a dramatic statement. Mr. Dollar. Are you prepared to name that somebody who may get hanged not at the moment Could it be that you don't have a name? That's possible, of course that you're just fishing so to speak bluffing Now why would I do that with you? I don't know frankly, but you must have come here for some reason Yes, I wanted to ask you a few questions and you'd be smart to answer them under the circumstances What circumstances the only one I know anything about is the tragic one of losing my husband only three days ago You have my sympathy, Mrs. Kailin. Sergeant Manosa questioned me for hours. There's nothing more to answer Will you go now, please? All right, if you say so Your unwillingness to cooperate will undoubtedly prejudice your claim for the insurance.  Finding some excuse for not paying off the policy. Wait a minute, Mrs. Kailin I'm not crooked and neither is the company if a claim is legitimate. They pay it always I'm sick of being under suspicion of being accused. I'm not accusing you of anything All I'm after is some information and if you refuse to give it Good night, Mrs. Kailin No, wait Wait, Mr. Dollar. Yes, don't go Come back, please. I'm sorry Been under such a strain on edge forgive me. That's all right forget it I didn't mean what I said, but I've answered so many questions And to go through all of it again. Well, it seems so pointless. Yes, I understand But I've found that people say things to me sometimes that they forget to say to the police They're more relaxed, I guess don't feel they're on the spot so much. That's true, but I thought it was just me Oh, you're not alone. I Remembered something like that after I talked to Sergeant Manosa He wanted to know where Eddie hung out mostly bars and so on I don't think of two. What are the names of the bars, Mrs. Kailin? Are the the Eloines on Beverly Boulevard and the brass monkey in down the strip What difference does it make Eddie wasn't killed in a bar? No, but he probably met people there talk to them You see it's a matter now of trying to reconstruct his life step by step right up to the moment he died You'd be surprised how much bartender see in here and remember I suppose they do All right, Mr. Dollar I'll be glad to answer any questions you want to ask good one thing though. I Wasn't expecting visitors of course and I wonder if I could have just five minutes to change and freshen up a little Well, that's unnecessary. I won't be here long, but I'd feel better really do you mind? No, of course not go ahead. I'll be right back Pour yourself a drink Johnny I Had the drink and waited and got ready to brace myself I've been through this before Attack plan number two a common garden variety when you can't beat him join him And when the joiner is a lovely woman the maneuver usually starts with some paraphrase of Slip into something more comfortable. Why don't you have a drink and a sudden switch to first names? and it always ends up with you and I against the world and Couldn't you forget just one little mistake? The little mistake being something like arsenic and a husband's coffee Yeah, an old familiar pattern and a first resort just as often as a last She was gone 20 minutes not five, but it was time well spent Carefully casual touch with a hair make up skillfully softened perfume And one of those frothy nylon jobs designed for that special evening in You will call charge Like another drink Johnny Thanks. I still have some I think I could use one. Would you mind sure? What do you have scotch and soda, please? Thanks for being so patient I Feel better now more Comfortable something like that easy on the soda, right? There you are. Mrs. Killen. Thanks. Would you do something else for me? Oh, I'd be happy to but I don't know your first name Touche All right, what are your questions? How do you think it happened? I Don't know Not some enemy because Eddie didn't have any just friends Too many friends. Who are some of them? There's only one who really fits the definition who who's really lasted his name is Pete Steimer Pete Steimer, where can I find him? You can't or at least the police haven't been able to nobody's seen him since that night He's had nightclubs off and on and in between he makes books What about those other friends the ones who don't last? They drift in drift out depending mostly on whether he had any money at the moment, of course there were women Showgirls mostly dances strippers so on know any of them Hardly ever hear any of their names. Oh, he's made a point not to otherwise I'd have killed him long ago Did you kill a Mrs. Killen? No, did you love him? That's a good question. I Think I'll have to pass it though.  You didn't run Can I have another drink?  Maybe you had a fight I Ran out and told him I wasn't coming back And only three days later over the radio I Heard where he'd been found dead Burned up in his car. There you go. I Guess they call it shock. I Still can't really believe it even though I know it's true. Well, I guess you shouldn't know I understand You're the one who identified the body. I identified a wallet Burden black the wrist watch a ring all of them things I bought for him They told me there wasn't anything that Could be called a body. Yeah, well, I'm sorry mrs. Kailin. I know this is painful. Sorry Like I said, I can't believe it Not really Do you have any other reason for not believing Eddie is really dead? I mean besides just a feeling No No, of course not. What do you mean? What do you mean? Well, I was just a question. That's all forget it Let's get back for a moment to another question.  Well, the same as the police. I guess they said Eddie won a lot of money that night from some gambler named Toppo Lienley, you don't know this Toppo Lienley, huh? No, but I suppose that's why he was killed the money wasn't found. So I guess it was robbery Did you know about the money? It all happened while I was up at arrowhead and anyway Eddie ever had any money.  Maybe I did love you mr. Dollar. Is there anything else? No, no, I guess not at least not tonight and you look a little beat Yes, I'm afraid I am You'd go around trying to keep up a front But it's been rough. Yeah, I imagine that business a while ago fixing myself up a little This robe I Just had to do it There are times when a woman has to feel like a woman in order to feel anything Even sane I Guess you wouldn't understand though And I'm afraid I gave the wrong impression No, I think I do understand now And I also think I owe you an apology for what for walking in here with a preconceived opinion for being rude being wrong I'm sorry forgive forgiven forgotten and And Come back again, please Regardless, I might on one condition. Yes, your first name. Would you mind? It's Lila Thanks, Lila Good night. Good night. I Caught a flash of movement from the corner of my eye and whirled around just in time to see somebody slip off the corner The terrace and edging of the shadows of the shrubbery. I stepped off the porch and moved toward the dark hedge of banana and scrub palm I was watching for a sudden attack, but nothing happened Then I heard a slight sound on the next terrace level up the slope a rustle of bushes an accidental scrape of a shoe on the cement walk And I slipped along the walk. I stopped at the head of the steps and listened Nothing The only way out of the patio to reach the street was to come past me I started searching Even though I was on guard when the attack came it caught me off balance All I could see was a dark shape in the glint of metal in an upraised fist I grabbed the arm and twisted and drove my left into his stomach and again He rode his knees and raised his right hand and again, I saw the glint of metal I jumped warm grabbed his hand twisted it back and at the same time I swung my foot and kicked him out of the jaw Yeah, I'm all right Call Sergeant Rainosa. Would you Lila? I turned him over in his back and struck a match to get a look at him He was a big man stocky bull neck blonde haired. I slid my hand inside his coat and fished out his wallet and opened it His name was Toppo Lienly Here is our star to tell you about tomorrow's intriguing episode of this week's story tomorrow We meet a latin doll from Santa Monica an erudite bartender and a terpsichorean Ecstasiest and they're all in the cast join us. Won't you yours truly Johnny dollar? Yours truly Johnny dollar starring Bob Bailey is transcribed in Hollywood written by Les Crutchfield It is produced and directed by Jack Johnstone Be sure to join us tomorrow night same time and station for the next exciting episode of yours truly Johnny dollar Roy Rowan speaking