What's up y'all? It's Adana. So I recently did a video not too long ago about do I sleep on a 24-hour shift and I just kind of showed you a quick vlog of like a day in the life of a 24-hour shift like on called trauma PA. And so I know that it's a little bit hard to kind of grasp the concepts of everything but the question was asked like how do my hours really work? And so that is what I'm going to be answering for you today. Okay so I had this question asked by one of you all and so again if you haven't already done so subscribe, leave your comments, like my videos because it really really helps out my YouTube algorithm and so I will really appreciate it if you can do that. But Adriana Bevelaqua, I hope I said that right, she said you mentioned patients come may come in when you're about to get off your shift. How does that count towards your hours? Do you work less on the next shift? And so you know I said that we are hourly, I work 72 hours essentially in a 14-day period which equates to 324s. That's what we're obligated to work. Obviously we can work more. We don't get your traditional overtime so I don't get paid like time and a half or double time.  And so when it comes to if there is a patient that is coming in while I'm about to come off because it never fails like literally you are it's maybe seven o'clock in the morning. Sign out for the patients from like the night before that we may have been seeing or all the patients that on the floor that we were dealing with we would go to sign out and sign those patients out to the oncoming team at 7.30. So up until 7.30 like you're still essentially like the PA right you're the one that's still managing any new traumas that comes in. Because you know you can't expect people to take the shift that they're now coming in on like it's not it's not that it's expected even though they still do it okay so I just want to make that clear like we have a great team of trauma PA so they help out that we work really well together but I just want to let you know that it's not necessarily like they have to be the ones that are taking this trauma. So if a trauma is called at 7.75 and I was in the trauma bay or it's my turn to get the next trauma late I have to run downstairs and start running this trauma. Now like I said the oncoming team will absolutely come in and help out because they're gonna be managing the trauma throughout the rest of the day once I go home. But no like typically it starts off with me. Does that mean that I work less on the next shift? No I'm there for 24 hours at a minimum okay at minimum I'm there for 24 hours. So if I work you know 27 hours on one shift it doesn't mean that now I deduct that from my oncoming shift. I still work my full 24-hour shift on the next shift that I will have and if I so happen to get off later or on time then so be it you know I'll get paid for the time that I work but it's it doesn't work that way in terms of like it's stickler for you only work 72 hours and that's it because you never know what can happen on a trauma call shift okay you people do things like some people do stupid things some people just have accidents and because of that you you have to be on call and you have to be ready and available so thank you so much for asking me this question but yeah no I don't get a shortened time and honestly I don't need it because again I'm only working three times in a 14-day pay period like that's amazing you know and I love that so I'm able to just kind of relax I'll take if I have to work 28 hours one day and then I still get a full five days off I'm good to go okay so I love it so thank you so much I'm trying for asking me that question again leaving your comments and questions in the comment section below please you guys like this video YouTube algorithm will love you for it so will I follow me on Instagram edit on the PA go ahead and subscribe to this channel and follow me on Instagram I get that see university as well I will talk to you guys next time


So the Backblaze hard drive stats for 2017 are now available, which is exciting. Sorry if I sound a little different. I have a little bit of a cold. So I love that Backblaze does this. Backblaze is a company that has built a storage system, you know, online cloud storage, if you want to call it. And they've built this on a very different platform as opposed to just building your usual enterprise by, you know, Dell EMC or whatever you want to buy for your storage or my favorite FreeNAS and TrueNAS. They built it with consumer equipment and have built an interesting company. So you can read all about that there. And they have a lot of statistics they've shared. And I really love companies that share a lot of their stats, especially when they have so much at scale. Google released a little bit of drive information a while ago. And I don't know if that was the inspiration for this. I don't remember how this all started, but they've been doing this for a long time, which is really awesome. So they've been doing this since 2013, and they give you their smart status. And they're currently, as of 2017, there are about 88 million entries totaling 23 giga data. You can download this from our website if you want to do your own research. But for starters, here's what we find out. Now, this is something else I really like. They don't just give you the stats, they give you if you want all the stats that you can download and create your own charts and statistics out of this. So if you want to look at the data in a different way, go ahead. And I'll leave a link to this, of course. So these are all the higher drive reliability statistics. One of the things they do is unless they have a higher quantity drive, and they do do some qualifiers in here of you can't make assumptions because if they only had a small sample size and one of that drive fails, you're going to let Oh, no, that's a high percentage. So I'm really going to focus myself on drives that have a larger quantity install, because I think that gives you better overall. So this is the 2017 fourth quarter list and Seagate, I mean, this is something we've seen computers come in and have bad Seagate hard drives and, you know, it's easy to get jaded and say Seagate's are bad, but you also don't have that other side of statistics. When you think about statistics, you're like, well, I've seen a lot come in. Well, Seagate was the most sold no matter what, even if they had the lowest failure, it would be the most come in. But this is where things like the hard drive reports in back plays really give you good idea because you can go, okay, out of 7,220 drives, 17 failures resulting in a 2% failure rate with a cumulative drive days of 308,864. And these are like cumulative times that the drives have been up and running. And that's a pretty high percentage for those that it's a good sample size of 7,000 drives. Here's 9,886 drives with 1.3%. And we're seeing this kind of consistent here. So out of 14,000 drives, 1.2%. So these are still pretty high statistics. This is where I say there's a problem with the sample size.  I mean, there's always other statistics that can go into that, but it is makes the percentage higher, but the sample size is lower. So take that for what it's worth. Now the drives that you see an absolute consistency. And so we have 14,797 drives versus the 14396 really similar, similar drive days, much lower failure, only 0.45%. And this is what's led me to really enjoy the SG, HG ST drives as and such as I feel the same way at least. And I don't have the sample sizes they have, but we've installed some of these and they've been very reliable. We built a handful of free NAS boxes for them. We do like the WD Reds as well. I've not had failures with those that we've built for some of our Unify, NVR camera systems we've put in for clients. We built them with rate arrays of those drives and rate arrays with HG ST drives and both of them have really seemed to hold up well. The HG ST drives, like I said, we built with them. They're good. I don't have a problem with this. And this is something you should consider when you're building storage arrays is how much speed do you need but how reliable does it need to be? You know, my gaming system at home, I want a really fast drive for that. So you kind of play that into a factor.   So you may take a little bit of a speed hit, but for the redundancy in drives and for the rentability of drives, because they're going in something that you want to be running for a long time for all your data. Now they also updated their three year statistics, which is really cool. So we can look at things at an even bigger scale and get to understand these. So same thing we're seeing, you know, here it is eight terabyte C gates. We see, you know, 0.96%, 1.2% on these ones over, you know, a lot of drives over time that they have in here, but we dropped down to these HG STs over time. And we're still 0.34, 0.33, 0.63%. So of slight increase, but still a lot less than C gates. So Dave, for what's worth, I'll leave the link to all these drive stats, but this is always interesting, you know, to look at so you can kind of get some ideas for reliability. And I mean, these are going in their data center. So they're not just kind of casually sitting here like my gaming computer, which is not on every day. I don't play games all the time. It's kind of, you know, when I'm in a mood or when the kids are playing it. So it gets used, but not even not near to the intensity that a data center uses. So this is some really solid usage on these to see how they're holding up. Especially because they're like a lot of these are consumer drives that you can get, or maybe some are pro-sumer drives, but the reliability stats really interesting to look at. And especially when you see some of these really high failure rates with some of them, but granted, when you only have a drive count of 60, it doesn't take much to fail. So don't get too excited about that. That's a really small sample size. So take that into account. We don't know for sure if how bad those really are, but it said, you know, we'll see when the drive count gets higher if it does that. But Seagate's track history in the past has been, you know, much higher than HGST. I mean, these percentages that they have are still the lowest on any of their charts. And we'll see how that plays out. And hopefully the hard drive companies are looking at this and working with them to figure out what the failures are and how they can make them better. But these kind of statistics when companies release is so helpful to the greater community. And the fact that you can look at the data yourself, if you have another idea of how you want to look at it and track some of the drives in there, they give you that data. So I'll leave you the links in the description below. If you'd like to kind of hear, like, subscribe and all that great stuff. Hopefully this was enlightening for you and it makes you think about the hard drive purchases a little bit. Thanks.


All right. So hi, everyone. So my name's Hong, and I'm the head of the Open Government Products team at GapTech. And today I'm going to be talking to you about zero-knowledge secret sharing, how we share data on the Singapore government. Well, not how we do it yet, but how we're trying to fix it. So basically, sharing data within the government is really, really hard. So just so you guys, I know there's a lot of talk about privacy and data sharing, but as someone who has worked in the government and has tried to do data projects, turns out that it's really, really non-trivial to even get access to really basic data that you're trying to do for a project. So to give you an example, we were trying to work on a project for, let's say, I think we were trying to identify single mothers and what their profiles were. So we could figure out what a subsidy scheme for them could be like. And so these are just a set of the steps that you have to go through. First, you have to ask about the data. You have to ask what data do you have. You have to explain why you need it. You have to go through a whole churn of not this, not that. And perhaps one of my favorite steps is that data transfer in the Singapore government goes by taxi, where you spend a lot of time at an inordinate amount of time where you literally cab back and forth. And as a manager, I spend a lot of time approving taxi claims for people to cab back and forth with hard drives, transferring data around, because that's the fastest way you transfer data around the Singapore government.  This is literally, we did a user study. So our UX team actually went to talk to a whole bunch of users who tried to do a data project. And this is what the timeline looks like. So you start out and you're really happy, right? You have a project hypothesis. It's like, I'm a smart, modern, data-driven person. I'm going to help transform how we do something in Singapore. So I'm going to get some data. I'm going to do a project. I'm going to figure this out and optimize it. All right. And so you start figuring out, all right, where can I get this data? And that's where you start getting sad. And you figure out, you see, you figure out there's multiple, multiple parties trying to find data. You just ding dong back and forth. And this isn't even starting. This is like, undefined period of time. And so after you've dinged on for a little while and figured out which is the correct agency to find the data it is from, now you actually need to ask them for the data. And this, you would think, is like a one thing, right? Here, I'm a government agency. I would like to get some data to do this project. Please and thank you. This turns out to take between two to five months. So if you're looking at this, you start, you write an email to ask for data. The agency, you send you a data request form. You fill it up. You negotiate about which fields you can or cannot share. They send you a data dictionary, because obviously, they don't actually explain what the various columns mean. So you need to go back and forth.  And this actually goes back and forth multiple, multiple times until you finally get approval to get the data. And God help you if you change teams. Because if you change teams, you have to go back all over again. Once you've done that, now you need to actually get approval. So this is just filling in the form, not even getting approval yet. And so you fill in the form. You've got to get it signed by your policy director and then they've got to get it by their agency. You've got to wait for data to be released. And then there's the actual transfer to data, which, as you can see, takes three to six months, even those two steps. And if you can count the number of cab rides, that is. It's quite a lot. And after you've gone through this whole process, then after spending a year of getting all the data, you then have about two weeks to two months of analysis, and then your project is done. So if you're wondering why we don't digitize more in the government, this is why. So we are trying to fix that problem. And so total time is about 12 months to get started on a project. And so sure, we should just build a platform. This is like your startup pitch deck. Why not build a platform? We have a central platform where all agencies can upload their data. People can search, preview, and download it. Seems pretty straightforward. You just have a file server. People put stuff up. People take stuff down. That's the problem. Now you have a service, which now you have a single software system, which has all of the Singapore government's data. Now if something were to happen to that, and things never happened, obviously, because you were very, very good with security, that would be horrendous. Like you would basically leak all kinds of private things out. Not even talking about military secrets, even just things like medical records, or people's indebtedness, and things like that. Like all kinds of stuff which people treat really seriously. All right, so how do we get around this? We clearly can't go back to this. This is security through bureaucracy. It's stronger than security through obscurity. So what do we do? So that's where zero knowledge comes in. So this is how we're proposing to work. This is how we are building one of our data sharing platforms. And take note, you don't have to do this for it. I just want to caveat. This is not for every single last data set because it adds a bit of a burden. But it is how you more easily share something securely without creating a big, juicy hacking target if the data is a fairly sensitive bit of data. So this starts out, basically, if you look at it, we have a web app. And a user just uploads a file using a web app. It's pretty straightforward. But instead of just uploading a file straight to the server, what we do is on the client, in the browser itself, before it ever touches the server, we encrypt the data. We encrypt it. And the encrypted data goes to the server. And the encryption key stays only with the user. We showed on screen. We tell you, please write this down. Take a picture of your phone. Don't put it on a post-it or leave it on the office. But keep this thing safe. The person who wants access to data can go to our search index and can search around and find the data sets they want. They download the big blob of data. Then out of band, instead of taking a taxi back and forth, they just need this guy to send over the encryption key. And then they can decrypt the file and they get access to the data. So you can see you're using the server to transfer the big bulk of the file. And then you use an out of band communication. Out of band is a fancy way of saying, I have not described the mechanism specifically. Basically, you can show a picture to someone. You can write them a post-it note. Some other way, other than the main server, so that even in this case, if the main server is compromised, there's nothing to be found.  And that's the key principle here of zero-knowledge, that the server has zero knowledge about what it's storing. My server, even though I'm the one, so even though we're the team who built the service, we have no idea what's in the data there. We don't know and we don't want to know because if we don't know, even if someone compromises us, there's nothing to leak. And that's the key principle. It's not about trying to harden and harden and get something like super hyper secure and pinky promise that you'll never get hacked. It's about making sure that there's nothing to steal. But this does cause a problem. And those of you who might have spotted this, where the key itself is a single point of failure. So let's give you an example. So hypothetically imagine some government officer's boyfriend was a social path and decided to leak age data to the public. That would be a problem here still because the person who have access to it, he accurately has the key. You can get the key and you can decrypt the data. And that's a problem, right? You should not, and you know, even like just even more benign than that, right? Let's say we had some really, really important data set about like people's indebtedness or something like that. And someone just lost their password. Like you just lose this key. Whoops. Now the Singapore government has just lost all that data and it's just gone because it's an encrypted blob by design you can't get access to anymore. So what do you do? So our solution is to take the key, split it into multiple parts. And the way I think about it is that you take the key, you split it into let's say five parts, and any three parts of this key can regenerate the original key. So does this make sense? So I'll take the key, I'll cut it into five portions, but I don't need all five to regenerate the key. I just need any three of the five to regenerate that key. And this seems like a really complicated math, like math magic trick, but it turns out to be really, really simple. It's based on nothing more than secondary school math. So this is known as Shamir's secret sharing. I would highly recommend reading the paper. It's literally a two page paper, like that's it, it's just two pages long, and the sort of intuition behind it is remarkably simple. Any two points can define a line. You know you learn this, right? Two points define a line. If I have a quadratic equation, so x to the power of two, I need three points to define a quadratic equation, right? If I have a cubic equation x to the power of three, I need four points and so on and so forth. So let's say I want to have a key, which I need at least three people to regenerate the original key, right? So let's say that secret is here. So what I do is I define a quadratic equation which passes through this point, which is my secret. And then I just sample any other points on the quadratic curve. And you can see that any three of these points will uniquely define the quadratic equation. And so if I were to get x equals to one, y equals to two, negative two, x equals to 1.5, y equals to negative two point, two five, so on and so forth. And then I just solve a simultaneous equation. I literally just solve a simultaneous equation to figure out what the x square equation is and therefore when x equals to zero, what's y? And that's my secret. So the intuition's really simple, right? It's literally simultaneous equations to solve a quadratic equation. It takes a bit of time to think about and it takes a bit of time to wrap your head around, but intuitively you can imagine how you scale this to any number of people and any number of parts needed. So let's say I wanted to have a key with 10,000 parts and any 9,000 of them could regenerate the original key. Well, I just need a 9,000 minus one power polynomial and then I just sample 10,000 points anywhere and it's easy, it's trivial to generate because you can get as many points as you want. And the fact that it's so easy is beautiful because if anyone loses the key, well, I just throw it away. Like I just get another point from my curve and I hand it to him and there you go. So a few things that are important about this thing. Firstly, no single person has the power to access the data. So you could imagine in this case, let's say you could imagine giving one key to let's say the minister of health. You give the other key to the director of medical services in the hospital. You give another key to like, I don't know, the chairman of like some bank or whatever you want and any one of them, if they decide to go rogue or do something funny, can't access the data, which is great because it means that you need at least this like those nuclear codes thing where you need two keys to knock the door. This is an arbitrary number of keys digitally to unlock it cryptographically. The second major benefit out of this is that I don't care if someone loses a key. So let's say I had five keys and someone loses one. Well, as long as three people don't simultaneously lose their keys, my data is still safe. And so you could imagine if let's say you wanted to space it safe, you could do like, you know, I give seven people the key and three people are needed to access the data. And so even if even three people just lose their keys once in a while, that's fine. I just issue new ones to them. I just keep track of who has them and once in a while I just check to make sure that not everyone has forgotten everything. So it gives you both security as well as durability, which is important problem we are trying to solve here. Security and durability in one. So this works fine if you have like, I don't know, like three to five people who you need to get keys from, right? So when I want to access this secret data, I'll just go to like the three or five key holders and I'll get it from them. But let's say I have many, many people. I say I want to get data from a lot of people, like thousands of people. So then this is not workable anymore. I can't actually get parts from a thousand people.  And a big example of when you want to use this is when you're collecting public data.  Especially with the government. And so let's say, you know, you're applying for a flat or you're applying for medical, you're applying for leave or you're applying for like medical assistance or whatever you fill in a form. And all these forms have personal data on them. And the government can't ask you to encrypt every single one of your forms. They didn't go around to every single person and ask you to get your keys. That doesn't make any sense. So how do we deal with this? Well, we extended to work with asymmetric key encryption. So how many of you here know what asymmetric encryption is? Okay, does anyone not know what asymmetric encryption is? And I need a quick explanation. All right. So for those of you who don't know what asymmetric encryption is, basically, instead of having one key which unlocks and unlocks a file, one key can only lock it, the other key can only unlock it. Does that make sense? So that's the key thing. So if I imagine a physical lock where I had one key which could only lock it and close it, but that key could not open it again no matter how many times I tried. And another key can unlock a closed lock, but it cannot encrypt it. So that's the concept in asymmetric encryption. So in this case, when someone creates a form, let's say I'm a government officer and I want to collect data on... You know, I want to collect data on, let's say like children's eating habits, right? I want to check whether or not they're having a good diet. And I don't want to just be shared with everyone, obviously.  Does he have a lot of sugar? Does he exercise? Blah, blah, blah, blah, blah. The browser, instead of just encrypting the data, generates a key pair. So one encryption key, this is to lock the data, and one decryption key to unlock the data. The form itself is stored on the server. So I put up my web form that says, you know, to ask people all the questions. And with these questions, the key is stored with it. The encryption key, the locking key, but not the unlocking key. So next, let's say a user comes in. So a parent comes and they access the form and they fill in the kid's sort of dietary information, right? Well, when they press submit, instead of just sending that form decrypted to the server, they use the encryption key that was paired with that form to lock it. They lock that, they encrypt it and send the encrypted form response to the server. Now, every single person who accesses the form has access to the encryption key. And so everyone can encrypt their data to put it on the server in a secure form. Yes? A encryption key per form. A per form, not per submission, per form, yes. And so everyone, so everyone accessing that same form has the same encryption key, but that's okay because just because of the property of asymmetric encryption, even though we have the same locking key, doesn't mean I can access your data. So two of us, let's say two parents, they both submit their form, they both encrypt it, but they cannot decrypt each other's data even if they were to hack the server because that's how asymmetric encryption works. And so once all the parents have submitted all their data, even incrementally as it comes in, what we do is we just, as the government officer who's trying to get this, I just download the data blob, decrypt it, and I get the responses. So we have now collected en masse data from a whole bunch of public, from a whole bunch of members of the public and citizens, and the government officer himself has access to the data, but me as the central guy, as the guy who's built the service system, the Amazon who like, let's say runs the servers, the ISP who like might monitor all your web traffic, they can't see anything. And that's the point of zero knowledge. And so this is with asymmetric key encryption. This is something we've actually implemented. So recently you know, so let's put this out here. So this right here for the first bit, so where we are. So we started from here, which is big bureaucratic process, right? Big bureaucratic process. You enter this idea, let's build a platform, platforms insecure because you have a single point of field because you have a big hacking target. All right, so let's go zero knowledge, helps us be a bit more secure. So you go for basic zero knowledge setup. Basic zero knowledge setup works reasonably well, but then now your key becomes a single point of failure instead of just a silver. All right, so what do you do there? You take the key, you split it into multiple parts. The key being split into multiple parts gives you durability as well as security because so there's no more single point failure than the key. After you split the key into multiple parts but you now want to get data from a whole bunch of people. You want to get data from a whole bunch of people. The way you do that is you go to asymmetric public key photography and that lets you get access to that. So you have durability, security, access to a whole bunch of people and all by this we're building a platform to share data in the government. So that's how we trace for. So where are we now? So we are in the midst of building this. This is what we call vault. Basically it implements that data sharing thing. And these are just obviously dummy data and stuff just to show you the idea. But to the user, despite all that complexity we put in, it's remarkably low, it's remarkably low complexity. You just upload your data when you need it and you just browse around and you find the data set you want then you download it. And then you go contact the person or however and then you get a key from them separately. But if the vault server is hacked, yeah you can look at all the listings of what the data is there but the files themselves will be useless at least for the super secret stuff. For the non-classified, non-super secret stuff. Sure, we can put it on the server so that you don't have to go fast about finding keys but the secret stuff is safe. Yes. Does vault use the asymmetric encryption only or does it also use... Does it also use what? Some years. Yes, so vault does not use the asymmetric encryption yet it's right now implementing but we have implemented a Chamele secret sharing split key. This is still under construction so we have tested it out with some small use cases but haven't scaled to have run up. It's not a general thing in the government yet it's what we hope that it can achieve. Forms or SG is the other one where we... Ironically, we have implemented the asymmetric encryption but we have not implemented the Chamele secret sharing yet so they're both sort of in half states of achieving this but they are both working towards each other. So data sets have the M over N key state? Yes, because you don't lose that and the forms has this because you'll do that and most times it's only one person creating form you don't want to create that high friction to have to manage those keys so that's why we staggered it in that manner but both are working towards having both features obviously. Yeah, and so Forms SG is our government form builder.  Like if all of the Singapore government's transactions were in Google Forms, that would be a little bit worrying but by using this, we're fine. So you have all these forms but each of them is individually encrypted and individually secure. And so yeah, the biggest use case of this so far was I think national day balloting for tickets. If any of you balloted for tickets for national day that was built with Forms SG. So ta-da. Yeah, so that's who we are. We are the open government products team here at GovTech where a team of software engineers, product managers, UX designers and we build products for the public good. And we are recruiting FEC so if you ever want to find a job, come look for it. Thank you. Okay, I think we have time for one question. Anyone has any? Yeah, please. Hi. So, okay, when you intermediate secrets share, right? Is it a teacher set that you want to have everybody present to contribute that part of the key? Because I mean, I've been thinking about this and the thing is, is it possible for every guy to sort about it somebody would enter a key and if we store it securely and somebody else could enter a key subsequently? Right, right. So you're talking about like incrementally doing it asynchronously, right? Yeah. And so someone could, so instead of having everyone there at the same time like nuclear codes, you guys have like, all right, we are stage one on lock, stage two on lock, stage three on lock, well, possible, it is something we have considered level of complexity to implement that process fairly high. So we're starting with a base case first. The problem with this incremental thing is that then you need to encrypt the stored keys and like you just, basically we don't trust ourselves not to screw it up. So we're gonna start with a simple thing first. But yes, it makes sense and it could work. You could imagine this is sort of similar to how like, for WhatsApp, you know they do the double ratchet protocol, that sort of incremental, yeah, you could imagine doing something similar in order to like accumulate the key so that it makes sense, but I have not thought through the full implication and yeah, there we go. Other questions? Yeah, okay, well, I'll be around if anyone wants to talk to me, but thank you so much.


in the culture, but I think even among people who read Ayn Rand, it continues to be confusion about what altruism actually means. What is at the core of altruism? So what is altruism? Why are we so against altruism? They're definitely true. There's confusion about what altruism means exactly as there is confusion about what selfishness means. Now the reason I say altruism, I call it the tyranny of need is because if you look at it and ask yourself what altruism actually demands of us, it doesn't say be kind to your neighbor, give him some help if his apartment burns down or he's in an accident. What it tells you is that his life is more important than yours. You must subordinate your needs to his. If you want to be moral, the way that's measured, the only way that that's measured is by how willing you are to sacrifice for the sake of someone else. How willing are you to subordinate your needs and place someone else's above it? The heroes, the ideals, the paragons of altruism are people like Mother Teresa or Albert Schweitzer and why? They're praised because they are selfless because they don't care about their own happiness, their own welfare, their own money, their own needs. They are effacing their existence and instead they live to serve others. They are a servant to anybody in need. That to me is a terribly unjust and destructive way of living and that is what altruism actually demands of you. It demands that you live to serve others. Some people will say, but Mother Teresa wanted to do this. This was in her interests because, I don't know, made her feel good or this was her desire. These were her values. Well, first of all, I don't think that's possible. I think the whole point of altruism is if something benefits you, if you're going to get pleasure from something, give it up. It's wrong. You'll be motivated by something, by selfishness, which is an immoral premise. Altruism says if you're doing it for your benefit, that's bad. If you're doing it for someone else's benefit, at your expense, that is, it's a sacrifice, then it's good. Now, if Mother Teresa actually got real pleasure out of helping the poor, which is, she didn't. And if you read what she wrote, she'll tell you how miserable and depressed and the suffering she went through, which is what altruism demands. It demands that you suffer. But even let's say, hypothetically, if you find someone who takes pleasure in being an altruist, that is not an altruist.  It makes me happy. Makes me feel wonderful. Well, that's selfish. So don't try to twist altruism and somehow make it compatible with your benefit. Altruism says the highest virtue is self-sacrifice, which means give up yourself, not enjoy yourself, not benefit yourself, give up yourself, sacrifice simply because you have something that somebody else lacks. That's what altruism demands. And indeed, even on egoists, there would be some people who made a career out of, I don't know, social services or helping other people or doing things like that. It's not an illegitimate career to have if you truly enjoy it and if you truly see value in it. Yes, but it's a contradiction to say at root, you gain pleasure from being an altruist. It's like saying, my happiness, my happiness consists in giving up my happiness. That's what makes me happy. Now that's absurd. The point of rational self-interest is to hold your life and your happiness as values and to pursue it and to do what is necessary to achieve it as opposed as opposed to the idea of altruism which says don't hold your life as the standard of value, don't hold your welfare as a moral good. That's an immoral goal. Give it up, don't be selfish, be selfless. So there's no way to make these two somehow compatible. They are two opposite antithetical philosophies of ethics. Thank you for listening or watching The Iran Book Show. If you'd like to support the show, we make it as easy as possible for you to trade with me. You get value from listening, you get value from watching. Show your appreciation. You can do that by going to iranbrookshow.com slash support by going to Patreon, subscribe star, locals, and just making an appropriate contribution on any one of those channels. Also, if you'd like to see The Iran Book Show grow, please consider sharing our content and of course, subscribe. Press that little bell button right down there on YouTube so that you get an announcement when we go live. And for those of you who are already subscribers and those of you who are already supporters of the show, thank you. I very much appreciate it.


Here's your host, Jeff Frick. Hi, Jeff Frick here with theCUBE. We are on the ground in Seattle, Washington, for really a great tech week here. We wanted to bring theCUBE up, get a feel for what's going on. LinuxCon, DockerCon, OpenStack, Seattle. Seemed like everything that was going on this week in tech was going on in Seattle. We wanted to take advantage of the opportunity to come out and see Bluebox, Jesse Proudman, visit right in the ground central of what's going on in Seattle. So thanks for having us out. Our pleasure to have you. So absolutely. So it's pretty interesting because this is kind of, where Cloud started, arguably kind of AWS really popularized the idea of Cloud computing as an outsource provider to enterprises through kind of the adoption of Shadow IT. We've got Microsoft Azure here. Satya's rebuilding Microsoft around Cloud and Office 365. So this is really kind of Cloud Central and then here you guys are. Successful startup recently acquired by IBM, congratulations. So is Seattle ground central for Cloud? Absolutely. Seattle has been and will continue to be Cloud City. You've got every company that's doing anything in the infrastructure space and really the SaaS space has a presence here. So Amazon, Azure, Google, CenturyLink, IBM now. We're all here and I think it creates a very interesting sort of vortex of talent, of expertise, of experience sharing and we were really excited as Bluebox to be based here and then now part of IBM being able to really establish a foothold, a presence for IBM Cloud in Seattle will be doing some pretty great stuff over the next year. That's great and what's interesting about you guys coming obviously you're built on open stacks, big part of your story but you still now offer a choice of Clouds for people. They can have an in-prem, off-prem. There isn't one Cloud solution that's appropriate for every workload. There's a variety out there and you guys kind of come at it from a variety based on kind of an open source underpinning. Yeah, so I think one of the coolest experiences about going through the M&A process is being able to go sit down and talk with many of the giant enterprise providers of open stacks. So if you look at the sponsor list we get to talk to a lot of those organizations and the IBM Cloud strategy really resonated with us. So it's this public dedicated local model where the locale of the Cloud really is irrelevant. What we're delivering is an experience. We're delivering an API and an SLA and whether that sits on premises at a customer site or is a dedicated private Cloud in a software facility or ultimately is an open stack-based public Cloud. Having that consistent experience and that consistent API across all three is really key and IBM is putting significant energy and resources behind delivering on that vision. I remember that was really a big part of your talk at OpenStack Silicon Valley last year when we had you on talking about why are we spending so much time talking about the nuts and bolts and the pain of putting this stuff in when really the focus should be on the user experience and they don't really care. They just want it to work. Credit to AWS for really resetting expectations for what people think should be available on basically dialing it up, turn it on, log in and go. And that's been successful for you. Yeah, and I think that's been the OpenStack challenge. So many of the conversations have been why don't we see more adoption? Well, it didn't work for the first couple of years to the extent that an enterprise needed it to work. We finally crossed that gamut, but then the experience of a distribution versus as a delivery as a service wasn't driving that experience that customers were looking for. And so I think we've finally crossed that gamut now. There's companies like Blue Box and Platform9 and MetaCloud, Cisco that are able to deliver this capability as that experience regardless of the location. And this is where I think we'll start to see more and more of those enterprise use cases and more widespread adoption outside of just technology companies. Yeah, so dig into that a little deeper because you gave a presentation this morning at the OpenStack Scal event about really the death of the distro. I wonder if you can dive into that a little bit. What was kind of your point of view? Why are you taking that stance? Yeah, so part of that was just watching as an observer for the last couple of years. And then the other part is watching as a service provider for the last couple of years. So if we go talk to customers and prospects, the reality is that software distributions today, they've worked phenomenally well for things like Linux or things like MySQL or smaller single server installations. But when you think about cloud, you're no longer talking about a single server as the unit of measurement. You're not talking about one Linux distribution. You're talking about hundreds of interconnected servers and interconnected sets of software. And so being able to ship OpenStack as a software distribution, yes, that works. You can get everything up and running easily. We got a cool demo from Canonical this morning with them doing that. But the reality is that things go wrong. The operations burden of OpenStack, the operations burden of a distributed system, that falls on the shoulder of the software distribution user. And that's the big challenge. And whereas with Linux or with a database, when you have sort of one system go down, you have an isolated area of failure. When you're using a cloud for your production applications and that cloud goes down, you've lost everything. So we call it the blast radius. The blast radius has gone up dramatically. And so working with a service provider who has a network effect of hundreds or thousands of installations who can learn from each one of those installations and you can push those changes out and updates and upgrades and learnings back out into that network of installations, that's the way customers will be successful using OpenStack, not as raw software. So let's shift gears a little bit and talk about liquidity event, not part of IBM, but you guys have a real distinctive culture really driven a lot by you.   You have a great sense of humor and really kind of represent well. Now you're part of IBM, right? So it's goodness. You've got resources that you've never had before in terms of sales, distribution, smart people, distinguished engineers, et cetera. But you're also now part of a bigger family, 400,000 people now, 400,000 and 60. How's that changing the culture? How are you kind of managing that as well as taking advantage now of the increased distribution and resources that you can bring to bear? Yeah, it's a great question. I think it's one that hits any startup that goes through an acquisition and do a larger company. We certainly watched MetaCloud go through that experience almost a year ago now and good friends with a number of folks over there. So it certainly had a lot of learning that we were able to do from that team. You know, I think at the end of the day, IBM, when they came to us, they said, look, there's a lot of things you guys are doing very, very well. And there's a lot of things we think that we can bring to the table. And so our job collectively is how do we capture the benefit of both organizations and make sure that the sum is better than the parts. And so culture was a big part of what they thought we did right. And what we were able to build with 65 people was pretty phenomenal. But matching that up, as you mentioned, with the brand, with the distribution, with the sales force, and with the technical expertise, that's really critical. IBM has a really unique position of understanding enterprise requirements. They know what these buyers want. They know what the buyers need. And they have those long, deep-seated relationships. And so bringing that together with technology innovation, a much faster development cycle, an offering that gets customers in at the ground floor from a price point perspective and grows with them as the customer grows, we're able to blend all of those things together into one really compelling offering. And that's what we're most excited about. I think we are uniquely positioned in terms of open-stack acquisitions that have happened in the last 18 months to really leverage that acquirer to do so much more as a combined entity versus kind of just being folded in and disappearing. Yeah, yeah. I'm not worried about you being folded and disappearing. It's not your style. But I don't want to shift gears because it's a cultural thing, but anyone who pays attention to you sees it. It shouldn't be hard to see. And that's race cars and cars.  What is that all about in terms of, and what lessons do you take from, obviously, that outside of work and that experience into work? Why is that important to you and how do you leverage it? Yeah, it's a great question. I've been a car fanatic for years since I was in high school and have always had that racing hobby. I think as an entrepreneur, so much of your personal day and your personal identity is wrapped up in your business. I found myself sort of stuck around the clock thinking about work and what we were going to do next and what technology we could build and how we were going to close that next deal. You put yourself in a race car and you get it on the racetrack and that goes away. It's an experience where all you're thinking about is driving that car and the mechanical connection to something physical. It's so different from what we do digitally that it really became this interesting release, this interesting place to find some sense of calm and some sense of that physical, tangible world. We live in IT and cloud. We live in something that you never really touch and be able to go to the racetrack and touch the cars and work on the cars and experience that being so fundamentally different from what we do on a day-to-day basis. It's been just a phenomenal part of my life. I can imagine just the concentration. You cannot let anything enter your mind when you're focused on that track. Another cultural thing, so we're happy to be here, you guys have signs and posters and trophies all over the place which is very, very cool. We have the gong here, we have a big culture around winning and the sales team is critically important to us and I think often times in many organizations the sales team is often the corner and certainly they're closing deals but it's often difficult for pieces of the organization to see and to feel the success of each individual team. It's easy to share a product release and all the features that were added. Easy to share what marketing has been doing because it's all public but the sales team often misses out on that. We added the gong every time we close a deal that gong gets rang. Some people love it. I think we've almost started heart attacks a couple of times. I am a notorious loud gong ringer myself so we close the deal, the M&A transaction we did a pretty wild gong ring as well. It's now become this loved and hated part of the culture depending on who you ask here.  Obviously the people that hate the gong haven't been in startups that have not had a successful transition liquidity event. It's the auditory assault I think that they're most concerned about. Absolutely. I gave you the last word before we check out what you've gone through the acquisition. I'm sure there was a lot of stress and things going on up to that point. We've got through that. We're in the open stack season. We're at open stack summit in Vancouver Valley next week. What's your short-term objectives? What are you doing over the next six months that you can share? The first two months after the acquisition were really integration, getting the teams, the engineers, the employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees employees


Welcome to the weather forecast for the week beginning Wednesday, May 27th, 2020. I'm Chief Meteorologist John Ensworth for Longmont Public Media. This Friday, May 29th, we're at a first quarter moon, about half of it illuminated, rising it around noon and setting just after midnight. The weather this week is transitioning from spring to summer. This is going to feel like summer. It's going to look like summer. But first we have a little front on Thursday. Wednesday and Thursday is going to drift down into this vicinity. This forecast map doesn't show it making it past Longmont, but I think it probably will. You're going to get some moisture, storms firing up any mountains overnight and drifting out on the adjacent plains, and that is us. The big picture over the next 10 days involves that front. I've marked it here with this dotted line. Most of the ensemble models, different runs of all the same model, have precipitation happening on Thursday. Our normal low temperature is this climbing blue line here and the normal high is up here. So this front is going to knock temperatures down to just briefly into the upper normal region before real heat comes back. We are seriously above normal on through the weekend. Even low temperatures are far above normal. We get another bit of a front around the second of June, and that begins a cool down and we'll take a look a little bit further out at the end of today's discussion. So there could be a little front out here too. These are not earth shaking fronts. You can see some precipitation here, but not all the runs have it. It's actually a little bit later that we get more rain. On Wednesday we have a chance of convection around. This is going to become the rule that every afternoon you'll see thunderstorms start up in the mountains and some will drift out on the plains and we might get a spot of rain. Some lightning is dangerous. Don't take lightning for granted. Get inside. Get some place sheltered if lightning is nearby. There are plenty of weather apps that will alert you, like Weatherbug, to approaching lightning. By Thursday morning we have this building ridge out here, and this ridge is going to be the story for the next week, but we have a trough passing by just enough to punch down into this eastern side of this ridge. And with Northwest Flow, we've talked about it a lot here, Northwest Flow with a little ripple and it can kick off a front and some rain and some activity, that's what we have here for Thursday. We have this deep low down in Texas, that's really interesting to see down there. When we back up here, notice that on Wednesday most of the severe weather is right down here in Texas and along the Gulf Coast and Southern Atlantic Coast. That are going on to Thursday, still some severe weather down here in Texas and just a chance of convection up through the central mountains along the I-25 corridor, including Lawnmont. From there to Sunday, it's all about this ridge.  And we have moisture around. First map is precipitable water. This is how much water you could get out of the atmosphere in an ideal situation of convection, say. And the darker greens and blues are very moist air. So we have some Pacific moisture here, we have Gulf moisture out into the plains here. Some Gulf is fed up into the mountains, has Pacific moisture. We have plenty of moisture around Wednesday. So all it takes is something to lift it up to keep those thunderstorms off with some daytime heating, acting as a trigger. For the next five days, even with all that excitement, not a lot of rain. We have less than a tenth of an inch out here on the plains, maybe a quarter inch near town and over the balt boulder, just up to but below an inch up the foothills, so not a lot. Now this next map is just to show you how things can be crazy. This is the same model, so just adding five more days. And look at this, three to four inches of rain right around here and up around boulder and up in the mountains. I don't think this is realistic, other models are not agreeing with the GFS, so it's getting a little overly excited with the convection here. But Sunday there's still lots of moisture, look at that feed of moisture from the oceans here and here up into the entire inner mountain west. And we have lots of abnormally high precipitable water values here. So again, a little heat and moisture, that gives you thunderstorms. Taking a look further out, we have a week and a half away Monday, so this is looking far out. And this is the next time that a big trough comes in, so it's a ridge for the next week plus, until this one comes in and really cools us down just as noon, Monday, June 8th. And probably some good storms going off here. So in our next video, about a week from now, we should follow up on this and see if this actually comes to be. The next week then is 80s, cooling down briefly with our cold front Wednesday night into Thursday. We return to the upper 80s and top the 90s as that ridge really gets overhead. We have a chance of afternoon thunderstorms, better early on here with this front, giving out a little focus to the activity, but all the way through the whole week, every afternoon you might see the cause build up and start to hear some thunder and maybe get it hit by some rain. Chances are it will be less than an inch overall for the week, but we'll see. For more frequent weather updates, as soon as I get my account set up, it will be there at the Longmont Leader, replacing the Longmont Observer for local news and events. So please go visit the Longmont Leader. That goes live when this video goes live on the 27th. This has been your weather forecast for the week beginning May 27th. I'm Chief Meteorologist, John Innsworth, keep looking up.