Welcome, everybody, for the paper session, which is part of the best young police search award. So this is the paper that is read out on the problem of reprocessing by everybody regarding the gifts and the treatment of COVID. And Henry, the stage is yours. Thank you so much. Thanks for inviting me to act on our session. So this is joint work with Dima Kogan, who is also a teacher student at Sanford. So the dispute log problem is really one of the foundational problems in modern-day growth. We use it to build signature schemes in the lives of artists of our D.H.Change, T.E. case-crypto-systems, parent-case-crypto-systems, and lots and lots of other things. So for the versus of this problem in mind, which is a dispute log problem like this, and this dispute log on the other side is similar to a Google Prime or an Ad for the district in a group, and a problem that's in the GVS, it has to have a dispute log X. So given that the dispute log is such an important problem for us, you can ask yourself, why do we believe this problem is hard? The first reason we believe it's hard is that the person has been tussled with analysis of the problem. But another reason is what I call generic control over balance. So a generic algorithm is one that works in every group, so a dispute log algorithm that doesn't really care about the group that's working in. And the picture she showed is that every such algorithm that works in a group of crime or an Ad that succeeds with good probability has to run at a time, at least where we live. So the best generic attack in a 256-bit elliptic curve group, let's say, takes two to one twenty-eight times. And since the best attacks on our standard elliptic curve, let's say, elliptic curve group is the means for key exchange on the internet, the best attacks on these groups are generic attacks. This gives us some confidence in the hardness of this dispute log. Because coming up with a better dispute log algorithm would somehow have to involve coming up with a better dispute log algorithm. So this is why generics dispute log over balance are a very useful approach. So since I would be talking about generic algorithms a lot, I want to define what I mean a little bit more formally. So a generic dispute log algorithm is one that can only make black box use to make a collaboration with me. Again, think of these as algorithms that work in any group. Formally, we define this with a generic group model where a group is defined by an objective wavelength function, a sigma, that it takes an input to the X one from one to n, and how it puts a label or a bit string that represents the corresponding group element. So an algorithm engineer, while it has access to a group operation horrible, then you give it this horrible two bit strings representing two group elements and it returns to their product with a group operation that is defined by a label of a single element. So a generic dispute log algorithm takes a sigma one, sigma one, sigma X that represents G and G to the X, and the algorithm makes some quarries with this group operation horrible, and then has to come up with a dispute log X. And we'll measure the complexity for the running time of an obsession out of the label by the number of quarries that it takes to this generic group horrible. And as many of you probably know, this has been a really, really useful way to understand the hardness of this dispute log that probably improves, including parent groups, all sorts of assumptions have seen sort of an analysis of this problem. But one thing that is a cause for concern about the generic model is that it doesn't account for what we call the processing of the past. So the premise of the model is that the adversary doesn't know anything about the structure of the group when it starts executing it, and the only way that the adversary can learn about the group G is by talking to this world. But in reality, for the groups that we use in real life, there's really only a small number of groups that we use for teaching on the internet. So a realistic adversary can perform more pre-processing relative to one of these groups and potentially use that pre-processing to solve this dispute log faster than later on. And it turns out that the existing generic floor amount don't say anything about what happens in the face of these pre-processing tasks. So the model I'm imagining sort of looks like this. The dispute log algorithm with pre-processing works in two phases. In the pre-processing phase, the algorithm A0 takes its input into the description of this group G. Does it work in an outputs and advice directory? You can think of it as a data structure containing what it does about the group. Then, to relate our online phase, the algorithm A1 takes its input of problem instance G to the X, and has it out of the dispute log X. And in this talk, both of these algorithms are going to be generic. So I'm interested in algorithms that work in every group. When we measure the complexity of such an algorithm, we can look at a bunch of things. We can look at the pre-processing time, so we measure the number of queries in the pre-processing phase. We can look at the size of the advice range that the algorithm outputs. We can look at the online time and the online outputs of how many queries it makes for a problem instance. And then we can look at the success problem of the S1, and think of the choice of the group, and of the choices of the challenge. So, this is sort of the plan for the rest of the talk. I first wanted to use an existing pre-processing attack to try to admit that these attacks are sort of relative and interesting. This is an attack that achieves a key group complexity, and it works for any group. So it's a generic attack. Then I'll get into articles on pre-processing lower balance in attacks. So we show that this pre-processing attack is actually optimal for generic operands. So you can't depend on that. And furthermore, any such attack has to use a really large amount of pre-processing. So if the online time is pre-processing time, the pre-processing time is in two thirds. And then finally, I'll talk about a new attack. We have a paper on a DTH-like problem, and so on. So the first thing, again, I want to do is show you this pre-existing result. It's a pre-processing attack on this pre-mod that works in every group. So the theorem here comes from that appears in many different places. And the result is sort of this form. There's a generic, disparate operand with a pre-processing that uses S-pensive group-specific advice in the online time t, and succeeds with probably the epsilon where the parameter is satisfied right out from the form from S-t squared to the right epsilon. And although it's totally here, it's highly log-in attack. So what this means is if you plug in an S-equals t equals Hubert event, S-pensive advice, and Hubert event all the time, you get an algorithm that succeeds with a constant parameter. And I'm going to sketch this out, because I think it's sort of a thing that all of us should know, and it's also just sort of surprising. If you're used to thinking of this pre-mod, it's a square root of that problem. So as a setup to the algorithm, I'll need one slide of the material. The one bit of the material you need is, I'm going to define a pseudo-random walk on that all in some different groups. So this is going to go from a group of g to the x to g to the x plus alpha where alpha is picked using a hash function, or you can think of it as a random function. So if we take our walk starting in some group of g to the x, and move to g to the x plus alpha one, then g to the x plus alpha one is alpha two and so on.  And an interesting property of such a walk is that if you know that this pre-mod can be 10 points of the walk, you can work backwards and solve for x and this pre-mod is right. So having given you this one tool, we can actually put the entire pre-processing algorithm on this walk. The way the pre-processing algorithm works is, in the pre-processing phase you build Hubert event chains, so you take this walk for Hubert event steps, and you start all these walks with this random random result. Then you start with Hubert elements. Then you store the discrete log of the end points of the walk. So these circles all represent your elements, and then the advice for you to store the discrete log of the walk. So storing these end points takes roughly Hubert events to the device, right? There's Hubert events to the walk, which is roughly the walk of this, and that's the whole process of this. Then, in the online phase you're given a challenge g to the x, and the online algorithm is writing a line pass. The way this works is by creating a walk of length roughly Hubert event, and hoping that you sort of collide with one of your pre-computed walks. If you do collide with one of these pre-computed walks, you'll end up with one of these pre-computed end points, and you'll be able to work backwards to the recovery of the discrete log that was starting the walk. And it turns out that this takes roughly Hubert event, Hubert event operations. And I'm not going to argue that this succeeds with constant probability, but it does. The catch is that the pre-processing time here is massive. It tends to do through its time, because we have to build many of these walks, and each walk is quite long. So this, the fact that the pre-processing time is large, is what allows us to serve an event, a shoe floor bound to the online phase type. So, just to emphasize what happens here, without pre-processing, we know from shoe floor bound that generative log attack takes Hubert event time at least, which is processing that happens here. So all the subjects you allow is pre-processing for free. The sort of security of 256 bit of the curve groups drops from 128 bits to something like 86 bits. And it turns out that a related pre-processing attack creates multiple discrete log problems and we discussed that in the paper. And the sort of related attacks would break the end of the long screw cipher, and one from this component is actually breaking the warp ledger back. So this Hubert event upper bound is what got us interested in knowing this is the best discrete log attack processing that's possible, at least in engineering study. The reason that's relevant to practice is you can imagine if there were a 10-3 event attack using a 10-3 event in space and time you would really worry about the security of the 256 bit of the curve group because it would imply that there's been a trap door for these a little bit curve groups that would let you compute discrete log really fast. And if this happened, you can imagine what we think of as discrete log crumbling we might have to revisit the key sizes that we use, revisit the demographic standards that we use, and so on. So that would be a disaster. So what I'm going to tell you now is that a disaster doesn't happen. In fact, that hubert of engineering discrete log attack is really optimal. And furthermore the pre-processing time that it uses is also optimal. So you don't have to worry about this intuitive decaying. So we proved the following theorem in our paper. So we showed that every discrete log out of the processing that uses s bits of the group's specific device in online time t succeeds with the problem. The epsilon has to satisfy a trade-off of this form. Again, sd squared is sort of where epsilon happened. And it turns out that the attack that we showed proves that this bound is optimal at least up to the log factors. So this is sort of a robust result in the sense that we know the best we can do for any choice of devices. And that's what I'm going to tell you. And if you're familiar with generic floor balance, I should mention that there's a technique that Victor Sheep used to prove this as a classic result. And many of the other floor balances follow up on that as well. So we crucially rely on the adversary having no information about the group when it starts executing it. And in our setting, the adversary actually has a few bits of information about the group. And he has bits of information about the group when it starts executing it. And in the same time, the lower bound in this setting requires a different setup of the case. The other thing we proved is that the lower bound of your processing time is a function of the all-night time. So the trade-off will be like this. If you want to make it concrete, if you want the out-of-the-door and all-night-time keyword event, the supply of the pre-processing time has to be at least the same. So there's a very smooth trade-off. The faster you want your all-night time processing phase is going to go up. There's no way around that. So for the bulk of the remainder of the talk, I want to go through how we prove this is first-generation because that's really the hardest thing to do. And before I do that, I want to remind you again of how the generic is well worth. So a group here is defined by an objective function of state-funded mass exponents to district-certified labels. And an algorithm that has access to this horrible implement group operation relative to this late-point state function. In the high-level, we prove this time space or bound using a new compressibility implement, which of course has a really long history of crypto, even longer history of complexity here. In the high-level, we'll use a better than possible generic discrete-logging processing algorithm to compress this mapping signal that defines the new group. So if we have an algorithm A that is really good at solving the discrete-logging, we can use it to build an encoder or a compression routine that takes a compressed representation of the signal in such a way that it will later be compressed. And we show that any adversary that uses a compressive device in an online time t such that SC squared is a little low amount gives us an including to compress as well. And since a random strength or a random sigma is incompressible, this immediately gives us a lower bound. So no, we're crucially using the fact that our algorithm works for a random signal or a primal signal. This is where we take advantage of the fact that our algorithm works. So I'm going to sketch how this encoder is going to work. And for the sketch, I'll just assume that the adversary here is deterministic, but I need to remove that. Okay, so I'll sketch how we build an encoder that compresses this random logic signal. And again, a high-level idea is we'll use this pre-processing discrete-logging adversary to compress compression. So we'll have to somehow construct an encoder that will take the pre-processing algorithm and will run it on a signal. So the encoder has the entire signal as input. And the pre-processing algorithm will run it on some adversary and will write that as a cracker. Then we'll run an online algorithm, A1, and we'll run it on each group element in which is essentially a fixed string in the image of the signal. So all zero strings here represents we'll make some horrible queries to the generic and horrible, and then we'll output some of the disparate algorithms. What we write into the compressive encoder into the compressive representation is all the responses to A1's horrible queries. So we'll continue running A1 on all the group elements in in mysteric graphic order, and we'll write the responses to A1's horrible queries.  So this is how we compress. Now we have to decompress. So given this compressor representation, I have to convince you that it's somehow easier to recover signal. And again, when we do this, it's not too surprising. We'll just take A1, the online algorithm, A1, and the decoder will run it on the first group elements in mysteric graphic order, which here is involved in this experiment. As A1 makes queries, we can respond to all A1's horrible queries in the compressor representation. And as we do, we'll sort of learn a bit of information about signals. So we'll build up a table of the function table of signal as we go. So for each query we'll be able to write one row into this table. The trick is that when A1 outputs a discrete log, we'll get one row on this table for free. Because we didn't have to write a discrete log in all zeroes into our compressor representation, A1 gives that to us for free. So if we continue doing this, we'll build up this table in a way described, and eventually we'll have all signal that. So if you believe this, you believe that we'll be able to encode and decode signal. But I also have to convince you that this is a compressive encoder, so that we use fewer bits that have been taken to 90-degree results. And I'll try to argue that in a high-level product. So my claim is that each time the encoder invokes A1, it sort of compresses signal by one bit, rather than the 90-degree result. There's two cases here. So the easy case is that the responses of all of A1's are distinct strings. In this case, A1 actually outputs a discrete log for free. We get one row on that table for free, and we can compress by something like a log in that's relatively different. The slightly more difficult case is if the response to an oracle query that A1 makes is the same as the prior response, that it's the same as, the same value twice. And if you're not careful, an A1 is going to be going to pay twice what the same value is. So you pay twice what the same row on the table, and then there's no savings. So instead, the encoder writes a pointer to basically the prior orator to cause this collision. And if you sort of do some work, you can see that if we run this all night out of the A1, for at most the number of T squared iterations, we'll be saving it basically because the pointer is not going to take too many time to invoke in one. Whether it's an easy case or a hard case, we'll save one bit in this size and term of the equation. So to complete the proof, we showed that we'll sort of invoke the fact that a random query is an encoder. So we'll say that if we run A1 on N over T squared instances, the encoder does. Each execution compresses by at least one bit. But then we have to pay for this estimate advisory that we sort of stuck at the top of our cracker equation. So the overhead of this encoding is T squared, and this thing has to be bigger than zero, again because the ram is very incompressible. So if you don't... in that sense, just think of using an incompressible error. Using a better than possible adversary to compress a random string. There's some extra technical bits that I'm going to get into that you can check out on paper about decision-making problems and how to lose a fail often, but I'll just review the paper. So once you study discrete log, the logical next step is to ask you about other technical problems. So, particularly the DEH problem. We have matching our upward and lower bounds for generically logarithms with your processing as I just showed. And it turns out the same techniques with not too difficult modifications also gave you upward and lower bounds for the DEH to match. But for DEH, we have a gap. So, it depends on how long the best upper bound we have to solve this problem. The best lower bound we have doesn't quite match. So, we're not sure if DEH is exactly as hard as the super-parter, so it won't be easier if you do it in the process. So, we don't know if there's a better attack. So, towards understanding this question, we study a related problem that I'll mention on the next slide called the squared DEH problem. And we give a new upper bound a new algorithm on the squared DEH problem that actually matches the lower bound. And so, these are the new results we have. Upper bound squared DEH and then these are the lower bounds. So, just one word about squared DEH. The squared DEH problem is to distinguish two rules a little more from gg to the xg to the a squared from random. And it turns out that for generic online only algorithms, if you're not a library processing, this is exactly as hard as the stream model. But for generic algorithms, quicker processing we actually show that it's much easier. And this is surprising to us because if you think of DEH, this problem is roughly at the same level of difficulty. And here it turns out that once you allow a reprocessing, some of these DEH problems turn out to be provably easier than the stream model at least for generic algorithms. So, the last thing I wanted to just mention, a couple of open problems and recent progress on this line of work. So, the thing that's been bothering us the most is the types of this DEH up to the lower bound. Is the DEH with reprocessing as far as the stream model, or is it ready to approach? Another direction that we think would be pretty cool would be to look at sort of non-generic processing attacks on a lot of the purposes of the model. This seems very difficult, but we do have such an attack for a DEH to start with. So, if we could come up with an idea that I don't think would be surprising. I also want to mention some recent work for any of those in the world that gives alternative proofs of similar techniques or similar ideas in the generic model. And they use the pre-standard line of that, which is a complementary set of techniques that we use here. And they prove the hardness of the one more or the two more problem, knowledge of maximum impact assumptions, many things in the ideal cycle model that we have for creation model. So, if you're interested in this type of result, you should check out it. So, I've tried to convince you that if you're processing attacks, it's surprising and relevant to the critical as we use it on the internet and the lower bound of the attacks, showing that there's fewer generations of public attacks optimal, that the pre-processing time has to be huge, and that there's some surprising attacks on the general public. And with that, I think it's a big question. Coming from the microphone. So, that's an answer to what we've recently learned, but it is true, thanks to the forum and so long to think this would kind of aggregate the problem. That's a good question. So, if you don't have more than a volume in many hours, and it shouldn't change the right time at all, we didn't look at what happens when we go to exponentially many hours of attacks at the end of the minute, and there are aspects of something, and you wouldn't get a bigger variation in the security. But actually, as you said, that's true even in the online perspective. The question about the collision in how the adversary gets such a collision, and is that helpful for the adversary in some cases? Yeah, so you're asking about the collision events. Right. Yeah, so that's the event in which the adversary keeps the distance apart. And so, it's representative to the forum. And so, that is sort of an interesting case, and why would it happen? Yeah, so the collision can happen as a result of a sequence of quantum coordinates, so I was just wondering what kind of sequence would that be? It's a sequence of queries that would lead the adversary around to be bought out of the element that's trying to find out. Okay. So, I know that he's so he can get a collision by making different quantum equations. That is that. Sure, so I guess generative clock algorithms are an essence of collision-fine algorithm.  So, there's some things right, so you were using this compression algorithm by using the fact that the shoe quantum gets the right representation. So my question is if the same result was solved in the string quantum by a problem? Yes, we didn't look at that supposed to be an ancient version of DNA in any discussion. I guess the reason we were interested in this problem is because we treat the things that the adversary, the queries the adversary in class again as actually an experience that the adversary can continue on, and that's relevant for many of the clock algorithms that actually require the adversary to be able to admit that the district is a different organization. Okay, so that's very, very good.


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Live from Las Vegas, it's theCUBE. Covering Discover 2016 Las Vegas. Brought to you by Hewlett Packard Enterprise. Now, here are your hosts, John Furrier and Dave Vellante. Okay, welcome back everyone. We are here live in Las Vegas for HPE, HPE Enterprise. Discover 2016, this is SiliconANGLE Media's theCUBE. This is our flagship program. We go out to the event, extract the symptom noise.  Three days of wall-to-wall coverage. We're into day three for HPE Discover. And I'm John Furrier, my co-host, Dave Vellante. Next guest is Chris Hsu, who's the chief operating officer for HPE. He's the man who makes the trains run on time. Some trains are leaving the station and some are growing. Welcome to theCUBE. Welcome to being CUBE alumni. Thank you very much. I like the idea of being on Game Day. So, you know, how do you feel? The game's almost over. We have one more day. The HPE Enterprise team now has got a good, almost a year into their belt with the split. It's a humanized company. We have access to, the customers are here. Different vibe. Yeah. Okay. What's your take on that? Is that by design? Are you guys talking as an executive team saying, hey, let's get down and get personal with the customers and everyone here? I think that's what Discover's all about. It's all about the customers. It's all about bringing the customers to Las Vegas and London, the one that we do in Europe. And really showcasing what we are, both from a solution perspective, but also who we are as people, who we are as a company, what our culture's about, and what we're trying to drive in the transformation of our own company, as well as the transformations that they have. So, you guys, I'll use a Star Trek analogy since you guys have that awesome commercial with the Star Trek Beyond. Check out the trailer. You guys have some concepts in there. So, you're on the bridge. Meg Whitman's in the captain's chairs, and you're basically running the main machine room of there. I don't know if you're Scotty or Sulu. I don't know where we go with that one, but I think maybe Scotty the engineering one. More power, Scotty, you know. I do it for years. You can be a spark. You can be a spark. We'll figure that out by the end of the interview. But, you know, the big thing that's going on, the split is under your belt, but the spin merge with CSC, really big news, dominating a lot of the conversation, certainly on Wall Street, where's the growth going to come from? What's the rationale behind that? Again, this is one of those trains leaving the stations. Give some color around that transaction, and really the impact both to HPE and the customers. Yeah, so, you know, we announced two weeks ago, the spin merge of our enterprise services business was spin it and then merge it simultaneously with CSC. You know, really a competitor in the space. It has a very similar business. And the way we think about this is, number one, we're creating a pure-play IT services company in the new merch code. And we have a company that is going to be at scale. It's a $26 billion pure-play IT services company. And we believe there's real growth opportunities for them. Number one, they've got a CEO and CFO of a public company, CSC, that it has a really good track record and really good performance. And then what we've built in our own enterprise services under Mike Nefkins and his team is, they've driven a real turnaround and they've posted two quarters of constant currency stable growth, which is outstanding in this industry because it's a fairly challenging industry. And they've done that through building practices and services and also go to market, really re-engineering the entire go-to-market. So we think by putting these two companies together, we create scale, we bring together management teams of the two companies that have different skillsets. I mean, Mike Lowry and Paul Soleil have really proven their ability to take out costs and drive operating profit improvement. Mike and his team have really proven their ability to service customers and build a strong set of practices for future growth. So from that perspective, we think we're setting this new company up for real success and our shareholders will own 50% of that new company. So it's super important to us that we set that up so that it can be strategically positioned and have long-term success. So the street really liked the move, obviously, but one of the questions people had that I'd like you to address to our audience is, well, given that the business was doing so well, why spin it out? Why now? Well, when we look at our portfolio, we think about things like, okay, what do we need to have in our portfolio that's going to make us strategically competitive such that we can win in the marketplace? And we think about what are the synergies between these businesses? And do we have synergies that are so great that by having these assets as separate entities that we can't maintain some of that synergy? Or are these things better off as a standalone? And in this case, we believe that this is better off as a standalone, both because the value that we create from a shareholder perspective, but also because we're creating a scale IT services platform that can then go do M&A and continue to grow both organically and inorganically. And within the broader Hewlett Packard Enterprise, our capital structure and our focus on where we're investing our money is not on building out and acquiring services companies. And so I think that's a case where, look, we can continue to maintain that strong synergy and relationship which we aligned around in a three-year contract, commercial contract to pull through our hardware, software and services. And we can continue to do that, but also set this company up. So on the capital structure, you mentioned 50% ownership. And the financing behind that is coming from HPE. So okay, so the cap table basically 50-50, right? The 10-2. And the financing is coming from HPE. So think about it like this. When we do the spin and the merge, we're creating a completely new company. And that new company has to go put in place a capital structure that we've jointly defined. That will be a new capital structure. So as they set this new company up, they'll go out and they'll raise debt. They'll raise debt to basically do a couple things. One, they're going to pay Hewlett Packard Enterprise a cash dividend of one and a half billion dollars. They're going to assume some debt from Hewlett Packard Enterprise in the form of pension liabilities and also some debt that we have on our ES asset. 2.5 billion. That's right. And we'll offset that. We'll contribute offshore cash to fund some of those pension liabilities. And thus, they create the beginnings of a balance sheet. So essentially, think of it as a clean view. So it's good financial engineering from HPE Stamp. We could leverage, love the use of offshore cash. Certainly Apple's got the same problem too. We know that. So okay, so that makes a lot of sense. Let's talk about the partnership and also the growth strategy. So you mentioned M&A. Was that M&A of the Spin Merge or M&A for HPE? Or both. Look, I think on the Spin Merge, on the new company, they again, they have a global platform at scale and they have the ability, I mean, the services market is extremely fragmented. And there are tons of services companies out there that can be bought in a verticalized space, in a specific application space, bolted on to this new platform and then used for growth and then also to get additional market. How about that fragmentation? Because we're seeing that the high end global system integrators, like CSE, Accenture and whatnot, that they've been disrupted and they kind of saw that movie, that train coming down the track probably two years ago in the past year, you see them find their swim lanes. Can you add some color on how the swim lanes are developing vis-a-vis the integrators, the big guys, the ones that are transforming their businesses on the delivery side and then also specialties like EY as a certain focus, Accenture as this. What is CSE, HP services, Spin Merge, Co. going to look like from a swim lane perspective? From a swim lane perspective, just to clarify, do you mean specialty focus? Is there going to be one kind of specific thing that you're going to hang your hat on? Got it. So it's a very broad portfolio. So if you think about it at a high level, they will continue to have a large presence in IT outsourcing. In the world that we live in today, when you hear all this talk about hybrid, every company, especially large enterprises, are trying to figure out how much of the traditional data center do I want to maintain? How much private cloud do I need in my infrastructure and in my IT organization? And then how much is public cloud? And what our companies can do together is really build out that suite of services around IT outsourcing, which spans that whole hybrid infrastructure space. And then they will jointly then have a large business in application development, application transformation, business process outsourcing. Those are going to be at the high level of the big businesses. And then both companies have different verticalized strengths. So as an example, CSE is really deep in insurance and just did a couple of industry vertical acquisitions around the insurance space. You know, we're really strong around consumer package goods and travel and financial services. And we've built out specific offerings for those verticals. Bringing the two companies together, you now have more depth in more verticals. And so I think those are the types of things that we see as real opportunities. David and I were talking yesterday about, you know, the turnaround plan from Meg Whitman and the five-year plan. And I was commenting and we were talking about kind of where they were. And the split really kind of took up a year and a half of that. If you kind of take that year and a half out, we're still close, not even close to the five years. That's what was my comment. But I want to get your take on, now that the split's done, you got the spin merge going on. This theme here at HPE discovers speed, go faster, be disrupting markets and win in current markets. What are you guys doing internally to make your thoughts faster as a company? You've got category changing products with the IoT edge line and some really cool stuff happening on the converged infrastructure side. How are you guys going faster? How are you guys going to execute? What's the guiding principles? What's the thoughts internally? Yeah, so I'm going to go back to the split for a second because I do think, if you think about the five-year transformation, we're right in the midst of the accelerate part of that transformation. And I'm glad you asked about speed because the split really allowed us to accelerate. If you think about what Dion and his team are doing over at HPE, they're accelerating transformation in a really tough market. You know, they're really taking out costs. If you look at the innovation that they're launching, I mean, it's really remarkable. You look at where they're placing their investments now. They're making investments that they wouldn't have made as part of the larger Hewlett-Packard enterprise because they have built their capital structure and their investment capacity focused on those things that are going to drive their growth. So that's an example of acceleration. On our side, we've accelerated the speed of decision-making. We're able to go much deeper on different aspects of our business. You can see us pivoting to campus branch IoT. We think that's a huge trend. We don't think that that trend is a subject to the same issues that you have in the core data center around public cloud and the transformation is going around hybrid infrastructure. So the speed at which we're moving, you've heard about hyper-converged and a launch of hyper-converged in five months. Who would have thunk it? You know, it's the ability to focus these companies on a narrow set of customers, a narrow set of products and competitors, and to be able to make decisions faster because you have fewer people at the table and then drive those decisions. Well, it's pretty shocking that the break-up, if you will, didn't have an effect. We don't like to use that word, but... Split, sorry, split, sorry. But it really didn't have an effect on your business performance. I remember the day that a son moved from an Amdahl system to a son system and it crushed him for three quarters. He really didn't miss a beat. We had Robert Gates on the secretary of defense and we were talking to him a couple of weeks ago in theCUBE and I think with your military background, some of the things that you face make this job look trivial, but how did that affect your decision-making and your ability? Because you were only in that job about a year. That's right. That's pretty record time. Talk about that a little bit. Well, look, I think there are a lot of analogies and similarities to the military. I mean, we had a clear mission. We knew that on November 1st, we were going to separate this company. We had to organize our troops. We had to know where the enemy was and the enemy was complexity. The enemy was the decision-making that is so diffusing the organization. And we had to mobilize our forces and we had to move online in consistent fashion until we met the enemy, destroyed the enemy and then we're able to separate the company on November 1st. Use your analysis. Yeah, all kinds of systems, the new site. I mean, basically it's a new company almost. It is a new company, infrastructure-wise too. That's right. And one of the things I would say is you may get the very beginning that's made a very smart decision. She said, listen, I want to stand up a fully dedicated separation management office and I want to resource that separate from the business because I want the business focused on delivery, delivery, delivery. We have to deliver our commitment to shareholders. And over and over, she said, listen, the first sense of credibility they have for the two new management teams is whether we're able to deliver during the course of separation. Then that freed us up as the separation management office to make tough decisions fast and rapid and then Meg and the executive steering committee completely backed us on those decisions because in a large diffuse organization with 300,000 people in 120 countries with 800 legal entities, the ability to obfuscate or wait till decisions are made and then go behind the scenes and try and undo those, it's just, it's a normal course of business. And what we were able to do is separate the run from the separation and then have decisions made quickly and stick. And the business teams bought into that. That's the, you know, the amazing thing. What about financial services? I know you're involved in that somehow, HPE Financial Services. What's going on there? That's right. So, Irv Rothman runs that business and reports in through me. And I think that's one of the best parts of my job. Basically, my job is to be an evangelist for Hewlett Packard Enterprise Financial Services. And I have to tell you, this business is on trend. And just to give you an example, you know, our Q2 volume growth was up 15% year over year, which is faster than anything in our portfolio is growing, which gives you a sense that it's actually driving penetration in the portfolio. And what's driving that? Fundamentally, it's a lot of what's going on in the marketplace around public cloud. You know, when public cloud really started emerging as a real deployment model that for enterprise, they changed the game around consume as you go, consume what you need, meter, billing, et cetera. And then what customers started to want to say, well, hey, look on my normal infrastructure, I want to be able to do the same thing. I want to be able to consume as I go. I want to be, I want more flexibility in how I buy and consume IT. And HPE financial services is spot on that trend. Well, that bill, well here, the other thing is that we love this composable message because that's up and down the stack. You want to get down and dirty with storage, you can talk about composable. You want to move up to the application of the developers. And ultimately your customers are builders now. So they're consuming and building, big build out.  So you've got cleaned up, Dave always has to have the balance sheet is getting healthier at HP, which can make you guys much stronger, certainly on the M&A side. So I got to ask you the innovation strategy from a product leadership standpoint. I was seeing some good stuff here beyond the organic growth internally. M&A, you guys feel good about that? Meg has said publicly that once things get cleaned up and strong, they'll do some, you know, inquisitive things. That's right. Look, I think we are very returns based, ROI focused investor. And you know, we have an M&A, we have a couple of different buckets. Number one, we have our Pathfinder program, which is run by Loc Ananth, and he reports up through me as well. And you know, that is where we make VC investments, typically series B, C and D, in emerging enterprise technology companies who are core to the strategy that we have. And it's not about making money like a VC 20% IRR, it's about making great investments in great disruptive companies. So that's mandate specific on the investors. So people understand it's not VC, meaning IRR based or financial return. It's not as much a profit motive, more than a strategic investment. Exactly, so you saw MISO sphere was out here the last couple of days. We have a Pathfinder investment, which is a small investment, venture based investment in that company. So we understand the technology. You guys just closed the amount on that? That much funding? It's big, it's large. It's much less than that. But these are small investments. They're anywhere from two to 10, in some cases up to $50. Exidite was public, I think it was eight, right?  You're not jumping in on the Uber billion dollar financing. You're not missing, you're not in the unicorn. You're coming into the people who need growth, kind of looking for an ecosystem is a certain profile. We're looking at customers that are really on the cutting edge of disruption in an enterprise space, who we can partner with. We bring them to meet our customers. We are working together, develop, go to market solutions that work together. We're embedding them in our technology and we're using them internally. But that's a small part of our M&A strategy, but really important. It's really part of our strategy, our core strategy to be out there on the cutting edge and really understand the market. I got to ask you a question. I got the number one question I get is two things. What's the transformation leader of the future look like? And I was just having a chat this morning with a community and it's going on in London DevOps event. And that was the number one question. I hear that all the time. And the other one is what is the white spaces that you guys would like the marketplace to fill in, certainly on the ecosystem side, whether it's entrepreneurial activity and or people that are, it's a softening of the market, people who can't get a revenue model, but with an ecosystem injection and some potential partnerships, that creates opportunities. So two things, transformational leader, what do you see as that profile persona? And then two, what's the white space for those emerging companies? Well, there's a lot of questions in there. Take your pick. Welcome to the queue. And it's a point where you come back to the M&A piece because there's a second leg to that I think is very important. But on the transformational leader, I think in today's IT world, you need somebody who really can see what's around the corner. You need somebody who is flexible because the speed and pace at which this industry is changing is not one in which you can have to use another military term, set piece battle. It's more like a battlefield that's changing all the time. So you need a 360 approach to this that's flexible, but also that allows you to place investments that you can have mature over a multi-year period of time. That's a real challenge for most CIOs because look, there's very few CIOs that have budgets that are going up 10, 20% a year. Most of them being told, I want real productivity. I want you to do the same with less. Bookings drive investment from their standpoint. That's right. And that's one of the things where, just maybe back to you look back at enterprise financial services is really important because a lot of our customers want to transform to the hybrid infrastructure, but they don't have the money to do it. You're going to help fund that. And so what we can do is help them fund that upfront. We help them fund their transformation upfront. And part of that is the asset management business that we have where we can go in and we can say, listen, you've got a bunch of older assets. We can help you monetize those assets and we can do it in a secure way because we can clean, take all your secure information data, et cetera. And then we can place those in the public markets. In addition to that, we can then give you money upfront to guess what, fund that transformation and buy more stuff from us. Well, you prime the pump and you de-risk the customer. Exactly. And the parachute opens when they go. That's exactly the way to do it. But look, I mean, a transformational leadership is required in an industry like this. It is moving so rapidly. And IT is not a back office function anymore. It is front office. It is core. You know, before I even joined the backward enterprise, I was in private equity. And what I realized the last couple of years in private equity is every company we were looking at, we were increasingly dilagencing their IT platform. We were increasingly dilagencing how the online, the relationship they had with their customer, the data was actually driving the fundamental business. And I think that's where we're at today. IT is core to the frontline, is core to the fundamental business of every company. Let's finish the thoughts on M&A. I mean, Aruba obviously looking great. HPE, we've been saying, is got to get really solid acquisitions going and get good at acquisitions. Aruba looks like it's on track. Three-part great acquisition, but John and I could have done that acquisition. It was a no-brainer. So, finish the thoughts on that. Maybe we should get in the private equity business. Exactly. Maybe we should establish a consulting relationship where you guys can help us with our M&A. You guys, we have a long list. But I think the things that you outlined, and especially if you look at Meg's track record since she's been here, she's done no big acquisitions that have been outside of our core. And Aruba is a great example. Aruba was a company that we bought that's really in our core that had a unique technology that was looking for access to channel, was looking for access to international markets. One of our core competencies is we have one of the largest and best partnership models and go-to-market models in the tech industry, bar none. If we can find great technologies and we can bring them into our company and scale them through that, that's a win-win. And then if we are able to buy something that's at really the forefront of one of the macro trends in the industry, IoT, mobility, connected devices, et cetera, it gives us another platform for growth. Something that we can build off of. And I think if you look at what we're doing with Aruba, it's really exciting. We're really excited. And the competition you guys talk about the military example, the battlefield, certainly changing, I would agree with you. And it really is becoming a big supplier battle. Not winner-take-all, but winner-take-most in most of the cases. So you got a lot of competitive landscape. At the same time, the ecosystem pressure to have a robust ecosystem is certainly critical with seeing that in the developer community. But in your core, you got to win those battles against competition. So what's your thoughts on the competitive strategy as you guys look at the 3D chess match or the battlefield with the competition? Well, in this battle, you don't know who your enemy is. Sometimes you don't know who your friends are. And sometimes you have to partner with lots of different people. And a great example is some of the partnerships we struck recently. If you think about what we're doing with Microsoft, I mean, Microsoft is aggressively going after public cloud with their Azure strategy. But we think that we can actually be a great partner for Microsoft. And we can also build a big business off of being the leading player in private cloud. And if we can bring Azure Stack to many of our customers, we can help them bring private cloud functionality and economics into their own data center. And many of our customers would prefer to have that functionality in those economics and control it within their own data center. But that's a great example of a partner ecosystem that we're building to really be successful in this transformation to hybrid. Chris, I really appreciate you taking any time out of your busy schedule to join theCUBE and share your insight and perspective on what's going on as you guys run the trains and spin out some more trains and merge in with the CSC appreciate it. I want to ask one final question for you. Share with the audience. You've got a private equity background. Obviously get the military analogies that really work well in this new market is what are the core assets of HP? Obviously we talk about this in theCUBE all the time. Great channels, great sales, great customer satisfaction, great leadership in R&D. As someone in a private equity certainly see what were the top three things that make HP super valuable with a lot of leverage to be successful in this new economy? Well, look, I think number one, and you said many of them, we have a great relationship with our customers and we have a great relationship with our partners in go to market. We think that's a big competitive advantage for us. Number two, we have a long history in a culture of deep seated research and IP that is underpinning all of our products. And then our services arm, especially through our technology services is an IP based technology services arm. It's sticky, it's like an annuity and it's highly profitable. So I think we have a great core with our infrastructure, our services and our software assets to really make that transformation. I think in addition to that, when we do the spin merge of ES and CFC, our investors and our employees and our customers are left with a financially sound, stable, high free cash flow generating company, which might not be exciting to everyone, but that's the thing that fuels the ability to be here for a long time and be able to reinvest in that business so that we can stay relevant for our customers. And the last thing I'll say is, Meg has built an amazing leadership team and many people say to me, it's amazing. We can tell you guys like each other. You guys work together and you guys are breaking down barriers and boundaries across the company so that we can all be successful. And it seems that people are very much approachable, the execs and the people around the trenches rolling their sleeves up. And certainly great congratulations. And as to end on the Star Trek note, customers in your field probably saying, Scotty, more power, fire everything. So congratulations on your success and thanks for coming on theCUBE. I really appreciate it. Thank you, really appreciate it. Chief Operating Officer for Eulah Packard Enterprise, HPE, E for Enterprise. This is theCUBE Silicon Angles flagship program. I'm John Furrier with Dave Vellante. We'll be right back with more coverage from HPE Discover. You watching theCUBE.


So guys I am back with another sensual video and today I will guide you in how to get this crazy looking car known as a potato wrapped in tin foil. As it going guys my name is dpg and if you do enjoy the video leaving a like really helps out and if you like what you see and want to see more sensual be sure to subscribe. Okay so this secret car is tied to five collectibles scattered across the map once you collect them it's known as the lust conspiracies. So there's five of these scattered across the map once you collect all five this car automatically is added to your garage. Now before we start I do recommend you getting yourself a helicopter. So go to this point on the map guys follow where I go and grab this helicopter it just makes life a lot easier for you. Once you're done here just follow the five points on the map I go to right now to grab all five parts to this car. Now what I will say is you can do this at the very start of the game well that's the very start of the game but since you unlock the open world where you're free to explore you can go and grab the helicopter and go and grab these five lust wheel collectibles once you get both five like I said the vehicle is automatically added to your garage it's known as the potato wrapped in tin foil who wouldn't want this thing simple as that. Guys if you enjoyed the video leaving a like really helps me out if you want to see more guides on central like more secret vehicle locations and much more check out my channel and there's also much more to come so make sure you subscribe. Again guys if you enjoyed the video leaving a like really helps out and hopefully might be beautiful people I will see you on that next one. That's strange.


There are many many things that could happen today 16 permutations between these four teams But it comes down to one very simple matter the Yankees win they're in the playoffs. Yeah, that's very true Michael It was true yesterday So you hopefully they play a lot better than he did yesterday the fact is I don't think they can play any worse than yesterday's ball game So I'm looking forward to a good game from the Yankees today to bullpen is well rested Maybe they can come up with some big hits and just take it from there All right, so there's been a lot of debate on whether or not the Yankees should have used Garrett Cole on three days rest today, and I've got to tell you I agree with them not using him because They're sure that this is not their last game even if they lose and everything goes wrong They still have a tiebreaker and then you get Garrett Cole on normal rest So I think that was the right move especially this time of year You know it's getting down towards the end of the season pitchers are throwing a lot of pitches And I think the extra day of the rest will do him well So I look forward to the Yankees winning today. Maybe we won't have to worry about it All right, so it's going to be interesting to see how they get nine innings out of their pitching and all likelihood They're not going to get a lot of length out of a Jameson tie-on. So how do you think it's going to go? What do you think they want from tie-on tonight? Well, I think at least three innings I think at least three solid innings where the Yankees either Have the lead or the game is close or no score and then they can turn over the bullpen, which is You know somewhat well rested. I think you're going to see Luis Severino in this game I think that he's a guy who could give you at least two innings Maybe three remember he's been a starter in the past. I know he's just coming back From a long time on the injured list But he's he's a guy that I think is going to play a pivotal role in today's game And if you look at the bullpen now, they have one more Arm out there and that's louis hill because they put dj lameu on the il So they're loaded with arms and every single arm is available today except likely michael king is not Yeah, michael king was used yesterday and I think that uh, you know, he won't be in play this afternoon You know so many people came into this series and said well the the rays have Nothing to play for so they're not going to play that hard and well, you just don't know the rays are a 100 win team Because the rosters don't expand to 40 any longer. It's 28 So you can have to play somebody that's important and they like beating the Yankees also. They're a very good team Yes, they are every Every player has a role on their ball club And I think the first two days kevin cash their manager left a couple of guys out of lineup But not today they've got their best lineup out there when you can expect to see in the playoffs All right, michael laka gets the start for the tap of bay rays and you might say well the Yankees should hit him Well, everybody hits him, but the Yankees haven't this year. Yeah, but that was a long time ago That was early in the season. There's more on the line for the Yankees today I just think you get a good pitch you put your best swing on it Hope for the best Maybe they won't be able to catch some of these shots the Yankees are capable of hitting


Is this it? Are we live? Hello! Welcome, it's Friday night here in the UK. I'm totally not prepared for this as you're about to see. This is a really unusual departure for me on two levels and I'm going to walk you through the two things that I'm doing for the first time live. It's eight minutes to seven o'clock at night, so I'm in the happy hut. I'm assuming that nobody is watching this, but if you are, then you'll know that my name is Neil Mossey. Hello! I'm a development producer helping high achieving creators and performers just like you. No sound effects because we're live.  They're not paying me. They're not affiliated to me at all. I'm just trying out this software. It's called Melon App and that's why there's this logo in the corner and I'm a bit freaked out because I thought I'd be able to stream this privately and record the stream and then upload it later, but the free plan only allows you to go live. So I wasn't quite expecting to be live. So hello! It's great to have you here and I'm so not used to this dashboard that I'm looking at that I don't even know if anyone is watching this. I don't even know if it's live. Let me check because that would be really helpful, wouldn't it? If I check my channel, let's show on stream. Yes, I've got a Bohemian Rhapsody effect going on there, but this is what I'm looking at. This is what I can see. Oh no, I am live. It's just that on my channel page, for some reason, it's showing as a blank screen, but if you go into the live stream, I am very, very much there. I can share that screen. Let's share the screen. And I can hear myself in delay, so that's a really good sign. There we go. If I go share and show on screen there. So we are definitely live and I can see on there that two people are watching, and I know one of them is me. So if you are the other person, thank you. You are the one person watching my live stream right now on a Friday night. Courage to you, my friend. So that's the first big thing that I'm doing. So I'll take that off using Mellon app for the first time and show the screen. I've done that. Now the second thing I'm doing, which is, I have to clear that because I can hear myself. The second thing I'm going to do is, as you can see from the words along the bottom here, I am going to do the YouTube Creator Academy courses. I'm going to do every single course. Let's put those up on screen. So I go share screen. Sorry, I have to say it out loud. Browse the catalogue and then I'll punch that to air. So we'll show it on screen. All right. So this is the YouTube Creator Academy and they have all these courses. I'll just show you the homepage. I counted them. There are 46 courses. And I thought like this afternoon, why don't I just do every single course and do the course exam live at the end of every week to show what I've learned and also to get you to play along and see if you can take the course exam too and maybe we could compare scores. And I don't know, I'm not encouraging any cheating. So if you want to talk amongst yourselves, that's great. But I'm going to try and do this course exam for real. And the course that we're doing today is the Quick Start Guide to YouTube. It's the first course, I think. It's one of the basic courses. There are 21 basics courses. This is the very first one. And I don't know if you can see this, but if I share another tab, I'm going to stop sharing. I don't like, this is a little bit clunky having to share screens by coming out and going in again. So that's another Mellon app thing I'm noticing. Let's go to Creator Academy. Share on screen. So these are all the courses that you can take. So it's a little sneak preview of all the courses we've got coming up. I'll just hit the basics ones. So these are the 21 courses that I'm going to go through one at a time. You can see I've started a few of them. And I thought the only way I can see this through is to use you as an accountability partner my one viewer on the live stream. Hello. I should have told some friends that I'm doing this. But like I say, it got to about four o'clock. I thought, why don't I just do it and see what happens. So this is so clunky. I'm going to have to hide that, get rid of that tab and find the actual course exam. I'm getting quicker at this. So that's one thing, I guess. We'll show this on screen now. So you can see right here. Let's make it bigger. These are the lessons that I've just done. It only took me half an hour. And if you're watching this on the recording, I'll put a link to the YouTube Creator Academy in the description. But I've also put a link to this actual course so you can follow along or maybe even go back and see if you get any wrong. Shall we do the exam? Shall we do it? Let's go down to course exam. And I think if I get it wrong, I think I've got to wait a couple of months before I can take it again. So the quick start guide to YouTube course exam. Well, we're going straight in, aren't we? Now I'm not looking at... Only because I can't. But I'm not looking at my chat. Maybe I should. Shall I look at the chat? Because I don't want to cheat. But you can cheat in the chat if you want to. I won't look at the chat or cheat as I should be calling it. And I don't know how many questions... I guess we've got 12 questions. So are you ready? When I put this recording out, I'll put some big bed of music here like it's a game show. And let's dive in with the course exam. So the first question and quick start guide to YouTube is, how can people discover your content on YouTube? I'm not looking at the chat because I can't open the window. So put in the chat what you think the answer is. And I'll go through the chat afterwards and we'll see if anyone get any of these questions right. Let alone me. So how can people discover your content on YouTube? It's like a really terrible pub quiz, isn't it? Have you got better things to do? I haven't. So the multiple choice answers are YouTube.com on their computer, YouTube app on their phone, YouTube app on their smart TV, or all of the above. Put your answer down now. I'm going to go for all of the above. And I need to zoom out and hit submit. Oh, next. Let's see if I can make it bigger. What is a good question to ask yourself when defining your channel's mission? How can I have an impact? How can I make a ton of money? Sorry, I've got Mike Reed in my head. There was a game show in the 1970s called run around. I'll put a link to that in the description. I'm going to hit record there as well. But I feel like I should be hosting this like Mike Reed on run around. So let's start again. What is a good question to ask yourself when defining your channel's mission? How can I have an impact? How can I make a ton of money? How can I reach 100,000 subscribers? Or how can I produce a viral video? Answer now in the comments or live chat if you're my one viewer on the live stream on a Friday night. I'm going to go for how can I have an impact? And then we'll hit next. Oh, so we don't get the scores or answers to the end. I promise I'll speed it up a bit so that we can get through these. Question three, why should you pay attention to your channel name? It needs to be different from your real name. It helps to include trending keywords. It will always appear in your video credits or it can live on your channel for years. Put your answer in the comments now. Why should you pay attention to your channel name? Well, I'm going to go for it can live on your channel for years. Next.  I'm finding these a bit easy. So it'd be a shock if we get any of these wrong. Before you publish a new video, question four, I think. Question four, before you publish a new video, what's an important step? Add details to describe what your video is about. Pre-populate comments for early viewers to see. Embed the video URL across your social media and the last option is write down your number of subscribers. So before you publish a new video, what's an important step? Put your answer down now. I'm going to go for... Because I'm reading them out, I'm not actually taking them in. I can't do more than one thing at a time. Before you publish a new video, what's an important step? See, it could be embed the URL but I'm going to go for add details to describe what your video is about. Next. What's the basic definition of watch time? This is question five, and that was my chair, by the way, not me. The hazards of live streaming on YouTube. What's the basic definition of watch time? The number of people watching your channel right now, the time of day that most viewers visit your channel, the average time that someone spends on YouTube, or the amount of time that viewers watch your videos. So put your answer now in the chat, in the live chat, if you're watching the live stream, and put it in the comments if you're watching the recording afterwards. I'm sorry it's dragging out of there. I will speed it up. I'm going to do this next week and we're going to really zip through these. I'm going to go for... Is it the average time someone spends it? No, no. The average time that viewers watch your videos. Next. By the way, if you've just joined us, this is a live stream where I'm going to go through every single Creator Academy course exam every week. There are 46 of them. So this is going to take me till November 2021. We're going to do one every week, you and me, and we're going to get through this and maybe learn something along the way. This is the quick start guide to YouTube. The very first course and the very first course exam, I'm doing this live on a Friday night, live from the UK, from the Happy Hut. And we're going to go through the next six questions with six questions into 12 questions, the halfway. Which action helps you build your community? Interact with fan comments like I'm not right now. I'm so sorry, but I can only open one window. I wonder if I've got any chat. This is going to be crushing, isn't it? Let's go back. Which action helps you build your community? Interact with fan comments like every video that you watch. That is always a good idea. Change your channel name or publish a new video every day. I'm going to go with interact with fan comments. I've got about 20 to catch up on at the moment. Are you getting many comments on your YouTube channel? Leave a comment, let me know. We can sort something out and comment on each other's channel. Question seven. Yeah, it's number seven. Your channel branding should be simple or relevant to your channel or consistent or all of the above. Oh, a trick, a curveball there for the last option. I'm going to go for all of the above. And I can see. I don't like, by the way, I don't like... I've got the word melon in the corner of the screen there. I've got the word melon over my bald head there. That's not right. I'm going to click next. I wonder if I can make it smaller. What if I move it? No, I can't. Why should you use consistent branding? This is question eight, nearly there. Why should you use consistent branding? Because you want your channel to be discovered in search results. Because you paid someone to market your brand. Because you want viewers to instantly recognize your brand. Or because you want to provide a fun experience. So why should you use consistent branding? I'm going to go for... Because you want viewers to instantly recognize your brand. How easy are you finding? I'm finding these quite easy. Do some bragging in the comments or the chats. If these seem a bit too basic for you. Maybe they get harder through the year. We're going to build ourselves up. Question nine, what branding elements consists of a welcome video to potential fans? The channel trailer, the channel banner, the channel card, or the channel description? This is a good chance to plug my latest video. It was how to make a channel banner. If you're watching this on the recording, I'll run footage of it over here. I'll put the link in the description if you're watching the recording. This is the live course exam quiz. I'm going to go for channel trailer. I've got two screens. That's why I keep looking from side to side. Cindy finds a video on YouTube that seems inappropriate. I've had that this week. I just got a community guidelines warning for one of my thumbnails. I appealed it. If you're in the UK, I appealed against it. The appeal was successful. Then three hours later, YouTube automatically banned it again. I've got a community guidelines strike. I've got a video on that coming up very soon. I bet it was Cindy flagging it. Anyway, Cindy finds a video on YouTube that seems inappropriate. What would you recommend her to do? Email the creator to express her outrage. Unsubscribe from the channel. Yeah, that would be a good idea, Cindy. Flag the video for review. Or add the video to her playlist, her evil playlist. So which one would you go for? Are you going to go for Cindy's evil playlist? Or unsubscribe and go away. Don't come back. I think it's going to be flag the video for reviews, isn't it? I'll hit next. Penultimate question. I'm channeling my inner Derrick Batey. If you don't know who Derrick Batey is, Google it after the quiz. But I need more hair, I think, to pull off the Derrick Batey. That deserves a community guidelines strike, doesn't it? Me talking about pulling, yes. So anyway, you can't have another community guideline strike, please. You've received a content ID claim. What does this mean? A copyright owner has identified content in your video that belongs to them. Another creator claims that you stole their idea for your video. I don't think anyone's going to steal the idea for this. And if they do, they've got 46 of these to make. You've received a content ID claim. What does this mean? You may have accidentally uploaded the same video twice. Or your video infringes intellectual property and you're probably in big trouble. So what would you go for? Well, again, this has happened to me by accident this month. We'll go for a copyright owner has identified content in your video that belongs to them. Next. Final question. We've got this. Here we go. What's a potential consequence of multiple copyright strikes? Your channel may be terminated. Your subscribe button will be disabled. Your channel banner will get a strike badge. I'd like one of that. Maybe I should make one of my own, like the play button that I made. Or finally, the final option, your videos may be age restricted. Put your answer in the chat or the comments now. Don't look at the person next to you. What's a potential consequence of multiple copyright strikes? I think it's going to be the big bad termination. Your channel may be terminated. So let's see if we've passed this course exam live on a Friday night live across the world from the happy heart here in the UK of K. Quiz complete. What do you do? Was that it? I thought it would tell us how we did. Get my letter. Shall we see? Letter of completion. I'm going to zoom out. That's it. Great. I thought we would get some kind of recap of the questions and answers. So we did it. I don't know what the percentage is. Should I print it? I should print it live, shouldn't I? Should we do it? Because we've only been going for like 22 minutes. Might as well go the whole hog. Let's get some paper. So how did you do it? You must have got them all right surely. I don't usually go back here during my videos, do I? Turn the printer on. Watch the lights dim. So yeah, what do you think? Did you do okay? Leave a comment with your score. I hope it's a bit more compelling than this. And we'll print this out. There we go. So I thought there would be some kind of fanfare or some kind of tension release at the end there. But it is quite like an episode of Mr and Mrs. That's it. So what happens now? This is the very first course I have completed on the YouTube Creator Academy.