a colloquium series named in honor of our three late colleague, Rajiv Matawani. So Matawani distinguishes lectures. They're definitely designed to be theoretically oriented, so they're aimed at a theory audience, but broadly so. So for example, I tell the speakers to imagine they're giving a keynote talk at a conference like Stockbox or Soda. And so we get fantastic speakers, and this quarter is no exception. So I'm very happy to introduce Umesh Bazarani, who's the Rajesh Stratz professor at UC Berkeley. He's also the director of the Center in Quantum Computation there at Berkeley. So he's really one of the intellectual founders of quantum computation, and that's part of what we'll be talking about today. He's also done seminal work in foundations of randomness, which I guess we'll also thank for any of the time today. And I should say one thing, I am sort of in awe of Umesh Abali's, his advising record with PG students is just unreal. So just to pick three names of random, you know, Sinjib Arora, Madhu Sudan, Scott Ironson, or all Ph.D. students of his. So today he'll talk about certifiable quantum advice, Umesh. Oh, thanks. Thank you. Thank you. It's a real honor to be here, and especially with this Motwani Memorial lecture, I guess you remember him fondly. So, OK. So, you know, before I was, I prepared this, you know, I was thinking about how to give this talk, and I realized that maybe I should try and experiment and show you the beginning and the end of the talk, and then we'll get to the middle. OK, so it's, you know, often Dilbert is a good place to start, because, you know, you can get right to the core of what you're going to speak about. So that's really the topic of the talk. To get to the end of the talk, you know, basically that's where we are trying to get to. OK, so let's start. OK, so this is what we are trying to, this is the question we are trying to get at. So let's say you have a set of dice, and you want to know whether they are really good dice, whether the outcome is really random. How do you certify it?  But now, what happens if you have a random number generator? So it's a box which outputs for you 10,000 bits, which are supposed to be random, OK? So, and you don't know what's in this box, right? So it could have memory, so you can't collect statistics because, for example, the output could be 01010101 and has the right statistics, so what would you do? So let me try to say this question a little more precisely, right? So let's say that, OK, here are the rules of the game. You can provide the specifications for what goes inside the box and then you hand them over to somebody who's going to implement the box for you.  Then you get to use the box only once and you can perform any test that you want on the output and your test should satisfy these two guarantees. So if the box was manufactured according to specifications, then your test should accept the output with very high probability, almost always. On the other hand, no matter what, if it passes your test, if the output passes your test, then the output must indeed be statistically close to random, even no matter who manufactured your box, even if an adversary did. OK, so this is sort of what we would understand to be certifying that the output is random. OK, so random number generators, they go back to the very first commercially available computer. There was a project to build a physical random number generator associated with it. Actually, Alan Turing was involved in that project. The project was eventually unsuccessful. So it's not such an easy problem to design true random number generators. Actually, very recently, a few months ago, Intel announced that they have an on-chip random number generator. OK, so let me just make a few observations before we go on. So this whole notion of what is randomness, this is a very big topic. And you can, you know, but on the other hand, to begin with, random bit sequences, there are basic resources in a number of areas, cryptography, game theoretic protocols, physical simulation algorithms. And actually there's, I believe, before the computing world changed and most cycles today probably go towards mobile phones and so on. But at some point, the majority of computer cycles went for physical simulation. So the point is that the quality of randomness you need in these different applications is quite different because in cryptography, you don't just want the output to be random, you also want it to be secure against adversaries. So that's a very different notion. Then there's this whole question about what's randomness in the first place. So if you're working within classical physics, this is really a very difficult and more problem because after all, classical physics is deterministic. So when you say something is random, you mean either you have a lack of knowledge like in dice where if you could figure out the initial configurations exactly and the forces exactly you'd know you'd be able to predict. Or computational power. So there are many discussions of this in terms of coin flipping or computational randomness, algorithmic randomness like Kolmogorov, etc. Or pseudo random generators where it's lack of knowledge or computing power. Okay, so there was an approach to this entire subject that was taken in CS in the mid 80s, which said something like this. Assume that you have a physical source of randomness that, assume that randomness is whatever it is, we are not going to get into these philosophical questions about what randomness is. We'll just assume that since we are trying to build random number generators, that we can at least build generators which output some randomness. And it's low quality randomness, there's going to be correlations and so on. Maybe there's an adversary who is in charge of doling out the randomness a little bit at a time. And now can we use it to generate real randomness? And so there were two kinds of results that were proved. One is that if you have multiple non-communicating sources, like two non-communicating sources, how do you take the outputs? Even though each one by itself has this correlated small amount of randomness leaking out and combine this randomness to get really close to uniformly random bits, bit strings. And the other kind of sequence of results said something like this. If you had such a source of randomness which leaked a small amount of randomness in terms of minentropy, how do you convert its output into a close to uniform distribution by feeding in just a small number of truly random bits? So say you wanted to output n random bits, you were allowed to sample a big O of n or some large number of random bits from the source. And then you feed in log n truly random bits and get, and massage these low quality random bits into close to truly random bits. Okay, so classically this seemed like the end of the road, right? Because clearly you have to assume something about the randomness output by the source. And then these results seem to make minimal assumptions about the source of randomness. So it seemed intuitively clear that there's nowhere else to go. And the surprising thing is that quantum mechanics allows you to get away past all this.  What are we trying to get at? So here's what we want to achieve, something like this. So we have some quantum boxes, which are going to generate some sort of outputs. We'll assume that these two boxes cannot talk to each other. They cannot communicate with each other. So maybe because of speed of light considerations or insulation, whatever. We are going to feed in some small number of truly random bits as C. And we'll use these to massage the output into n bits, which are epsilon close to the uniform distribution in total variation distance. But moreover, we'll be able to perform tests on the output. And we'll be able to certify that this particular output was actually a sample from some distribution, which is epsilon close to the uniform distribution, right? Without making any assumptions about what these black boxes look like. So another way you can think about this is that what this allows you to do is it gives you actually an implementation of a weak random source in a certifiable way. So you don't have to trust the person who built the box. You don't have to trust anybody.  It's sort of, this should strike you as being patently impossible. But this is what quantum mechanics allows. It's a very strange aspect. Okay, so let me just- Would the test be probabilistic in itself, or would it be? Yes, yes. Maybe it's a probability, but it's fine. Well, yeah, so in fact, so one can show that some number of random bits is necessary. Right, so if you were going to perform a deterministic test, then- I don't have an output to test on the string. Yeah, yeah, so these random bits are going to be used both to massage the output as well as to test. And you cannot possibly perform a deterministic test because if you announce your test in advance, then of course it's easy for somebody to manufacture the boxes in such a way that it passes the test with a fixed string. So that's why there's, at least the log 1 over epsilon is going to be necessary. So I hope that this talk is also an excuse for you to learn. If you don't know already, just a tiny amount about quantum computing. Okay, so where the tiny amount might be just a little more than this slide. Okay, but you have to start somewhere. So, okay, so first what's a qubit? You know, a qubit is, for instance, the state of this electron in a hydrogen atom, where it can be either in the ground state or the excited state. So if it was classical, you'd represent, say, 0 by the ground state and 1 by excited state. Now what quantum mechanics says is that in general, the state of the electron is going to be a superposition of ground and excited. And the way we write it is as alpha 0 plus beta 1, where alpha and beta are complex numbers. Okay, there's also the normalization condition that alpha squared plus beta squared is 1, which means that the state is a unit vector in this two-dimensional complex vector space. When you measure, you see 0 with probability alpha squared, 1 with probability beta squared, so hence the normalization. And moreover, when you measure, and if the output is 0, then actually the state of the system changes, and it's no longer psi, but it actually gets projected onto 0. So the new state is going to be whatever your measurement outcome is. So now, given all this, there's an easy recipe for generating randomness. And that's one of the points about quantum mechanics that it provides you with an intrinsic source of randomness through this Born rule or this rule of measurement of quantum states. So clearly, if you wanted to generate a random bit, what you would do is create this superposition, a superposition of 0 and 1, which is easy to do, at least in principle. And you'd measure, and there it is, you have a random bit, okay? The question here though is, this would be not a certifiable way of generating the randomness because you'd have to trust the experimentalist who actually implemented this for you. And you'd also have to trust that even if you trusted the experimentalist, you'd also have to trust that you don't have to keep recalibrating your apparatus and so on. Okay, so now, how do we actually start moving towards certifiable randomness? So the key to this is something called quantum entanglement. And this entanglement, this is a really fundamental aspect. Of quantum mechanics. It goes back to this very famous EPR paradox. And, okay, so, which we'll talk about in a bit. But there's this very interesting quote I found from Urban Schrodinger, from a paper that he wrote in a follow up to the EPR paper. Which sounds extremely modern, you know? So this is the way we think of entanglement today. But it's really surprising that anybody thought of it this way in 1935. And then it seems people forgot about all this for over 50 years. So where he says entanglement is not one, but rather the most important, the most quantum of a characteristic of quantum mechanics. Now it turns out that, actually about 30 years later, so this thought experiment, the EPR paradox, was Einstein's way of sort of challenging quantum mechanics, which he never liked. He didn't like the fact that it was probabilistic and he was looking for a deterministic analog of quantum mechanics. The so-called local hidden variable theory. And he tried for a long time to, he spent his last days trying to find such a deterministic analog. But then about 30 years later, John Bell showed that you could take this EPR thought experiment and if you analyzed it correctly and you came up with the right variant on it, you could actually come up with an experiment that distinguished between quantum mechanics and any local hidden variable theory. Any of these deterministic theories that Einstein was trying to formulate. So in some sense he was saying, the kind of theory that Einstein wanted, it sits in the following, for our purposes, the following computational model. Whereas quantum mechanics does not lie in that class. And so let me describe to you what this experiment is or actually a variant of this experiment that's much easier to understand. And which has actually been carried out in practice many times. And it's always given results which are compatible with quantum mechanics and incompatible with these local hidden variable theories. So this variant is called the CHSH game. It's some sort of, if you want, it's like a communication complexity game. Except that it's communication complexity with two players, inputs, outputs, and you want to say that the communication complexity is zero. So there's no communication between Alice and Bob in this game. Okay, so the game is played like this. Both Alice and Bob, each of them gets a random bit, X and Y, uniform 50, 50, zero, one. And they're supposed to output a bit each, A and B. What they're trying to do is, they're trying to satisfy this condition. X times Y equal to A plus B mod 2. So it's clear, right? So in three of the four cases, X times Y is zero. And they can achieve this by each outputting zero. So that's the easy part. And now you can convince yourself quite easily that classically it's impossible to do any better than 0.75. So the crux of the matter is that if Alice and Bob are allowed to share entangled qubits, then they can achieve success probability of cosine squared pi by 8, which is 0.85. So what are these entangled qubits? So basically, here's an experiment which says classically and basically any hidden variable theory, any local hidden variable theory, any theory in a certain class. You can show that the maximum success probability is 0.75. Quantum mechanics gives you a much higher success probability. And this is something that you can actually, an experiment you can actually perform. In fact, you can perform it, at this point, there's a student in my class who just performed it and got a standard deviation over the classical bound. So okay, so what's the, what does it mean Alice and Bob share entangled qubits? So by that, what we mean is, let's say that there are two qubits, right? One that Alice has, one that Bob has, and now the joint state is this, is an equal superposition of 0, 0, and 1, 1. So either both qubits are in the state 0, or both are in state 1, and with equal amplitude. So, so if you were to measure the first qubit, then you see 0 or 1 with equal probability. But now the rules of measurement tell you that if you saw the first qubit as a 0, the second qubit, if you measure it, you'll see the same outcome, 0, right? If you see the first one as 1, you'll see the second one as 1, okay? And this doesn't, doesn't depend upon how close the two qubits are. If they are entangled, then you separate them way to being very distant from each other, the same result holds. So it doesn't matter which one you measure first, you know, in what order, etc. You'll always get the same outcome. Okay, so so far this is not distinguishable from just sharing randomness. So here's what makes this really different, okay? So instead of measuring the qubit in this 0, 1 basis, you can also measure it in any basis. You can rotate the basis in which you're measuring the qubit, okay? And so now what you have, your qubit is a state, right? And if you're measuring it in some rotated basis, the probability you get the outcome u or u perp is just cosine square theta, sine square theta, where theta is that angle, okay? So now what this says is that it doesn't matter, you know, it doesn't matter what basis you're measuring the left qubit and the right qubit, as long as it's the same one, you'll, you know, the left and the right bases are the same, same. You'll always get the same outcome on both sides, right? Not just in the standard basis, but in any rotated basis as well. Also, if you measure in the u, u perp basis on the left and the v, v perp basis on the right, and there's an angle theta between u and v, then the chance that you get matching outcomes. So, you know, on the two sides, that you get u on this side and v on that side is cosine square theta, right? Okay, so this is where quantum mechanics deviates from, from, you know, there's just no classical analog to this. And this was the basis of Bell's inequality. Imagine that. So how did this become, how did this become a difference from the classic? Because, you know, you could use the same example, you know, left shoe, right shoe with randomly, and then do an imperfect measurement. Left.  And then both of us do some imperfect measurement of whether it's true or not. Well, it's, yeah, it's the nature of the correlations. So let me tell you in just a moment what the, you know, okay. So, you know, if it was in one basis, then you could just say, you flipped the coin in advance when the two particles were together, and then each of them remembers, you know, zero, okay. So they are far apart, and when you make a measurement, they just report that value. But now what we're saying is they don't only have to know this outcome for this basis, but they have to know the outcome for every basis, right? And moreover, when you do the measurement, if these particles are far apart, this particle doesn't know in which basis you're measuring that one. Okay, so they cannot, so they have to coordinate without knowing which question you asked the other one. And the claim is that, that, that quantumly they can, they can achieve this kind of correlation.  Right? It's, the correlation is, is, is very different. You need to get special shoes for this. I'm sorry? You need to get good shoes for this. Yeah, you need, you need, you need these, these, these exponentially large shoes, right? Yeah, they're, your Hilbert space has to be very different or something, you know, it's a, yeah, so. Okay, so, so how do you, how do you play the CHSH game quantumly? Well, here, here's how you do it. Well, Alice does this if, if her input bit is zero, she measures in the standard basis, the, the zero one basis. If it's one, she measures in the pi by four rotated basis. If Bob hasn't put zero, he measures in the pi by eight rotated basis. And if one, the minus pi by eight rotated basis. So, so why does this work? Well, you can sort of check that in three of the four cases where the answer is supposed to be zero, the angle between Alice's choice and Bob's choice is exactly pi by eight, okay? There's only one choice where, when x equal to one and y equal to one, where the angle is actually pi by two minus pi by eight. But they're also supposed to announce opposite answers. And so cosine squared pi by two minus pi by eight, which is, you know, is, is exactly one minus, you know, so, so one minus cosine squared pi by eight. So, so you get success probability equal to cosine squared pi by eight in each of the four cases. So if you think about it, what quantum mechanics is doing, is it's implementing the optimal STP solution to this problem. It's a vector solution. You know, it's, this is what quantum mechanics does, okay? And actually, you can, there's, there's this beautiful proof by Searleson, which shows that there, actually, this STP solution is optimal. That there's, there's no better thing that you can do. So quantumly, you, you achieve the STP optimal. Yeah, there, you know, it's, it, it keeps showing up in many, many places. And yeah, in fact, there's a, there, there's really this feeling in the air that maybe, you know, it, it could well be that if you, if you work with STPs, at some point you, you're going to have to learn about quantum mechanics. Okay, so, so now there was this, actually, so maybe, maybe I'll, maybe I'll go forward there. So there, there's this, there's a, there's this area of work called device independent cryptography, quantum cryptography. Which tries to work on, you know, quantum key distribution, where you try to share a random key in between two distant players. But you want to make, you want to create protocols where you don't really trust the devices that are doing the cryptography. And people had been working on this for a long time. But then a few years ago, somebody, you know, John Colbeck made an observation. It was a very simple observation, but I think a beautiful observation. So he said, well, suppose that you do, you know, do the CHSH test. And suppose that you're actually sure that the probability that, that the CHSH condition is, is, is met is, is strictly bigger than 0.75. Then the output of each player cannot be deterministic. Because remember, any local deterministic theory, we, we said, you can achieve at most 0.75. So if you exceed 0.75, you must have some randomness in the output. So this would seem to indicate that you should be able to test for randomness by testing for quantumness, right? And, but there's a problem, which is that in order to do this test for randomness, you only generate one bit, one, one random bit. Maybe two if you think of A and B as independent, but we have no reason to, you know, leave that bit. But on the other hand, we have to input two random bits to make all this happen, so it seems like a bit of a losing proposition. Okay, so, so, so there, there was a paper by Piranha at all. It, it's actually, it appeared in Nature in 2010, which showed that, you know, which gave a scheme by which you could take square root and random bits and, and you could, you could take the, you know, you could use the square root and random bits to, to come up with n inputs to the two boxes. So these are not uniformly random, but they are something such that the output of these boxes must have order n bits of min entropy. So there's order n bits of, of, of randomness hiding in those, in those, in, in the, in the output. And so now you could use an extractor to, you know, to convert the output into order n bits, which are very close to being truly random bits. So you could get roughly constant times n bits of randomness by inputting just square root n bits, okay? So, so, so what we do is, well, there are two things. You know, there are two issues. One was, can you, can you actually improve the, can you actually expand the randomness by an exponential factor? So that's the first thing that, that, that we do. Where you, you start with log n, log 1 over epsilon random bits. And you end up with order n bits, which are bits of min entropy or order n bits of, which are close to random. And there, you, you can make sure that the output is epsilon close to truly random bits. So, you know, depending upon epsilon, you can choose your, choose the number of input random bits appropriately. And to do this, you have to use a variant on the CHSH test, which I'll describe to you. It's a small variant. Okay. So let me, let me say in what sense certify it. Okay, so this is actually an interesting question. So, so, so the point is, you, you get these random bits and moreover they are certified to be random. So let's see what it means certified. So, actually there, so I put down two conditions there, you, you really, okay. So the output is certifiably random, provided three conditions are met. The first is that the small random seed you started from is truly random. So that you, there's no getting away from. The second is that the outputs pass this simple statistical test, which is built out of the CHSH test. And the third is that no, there can be no signaling between the two boxes, okay. So, again, as I'll, as I'll show you in a, when I show you the protocol. In fact, this no signaling condition doesn't have to be maintained throughout the protocol. You can actually break the protocol down into phases or short, short phases. And within each phase, there must be no signaling. But between phases, you can, you can allow the boxes to communicate. So for short bursts of time, you must make sure that there's no signal between the two, two boxes, okay. But then at the, at the end of this process, you end up with a proof that the output must be close to uniformly random. Where the, where the, where the, where the proof does not in any way depend upon the correctness of quantum mechanics.  It doesn't have to be through quantum mechanics. Quantum mechanics gives a way of achieving bigger than 0.75 bias in this CHSH game. But if reality is different, then it gives you bigger than 0.75. Then the output is guaranteed to be random nonetheless.  Absolutely. Absolutely. Okay, but then you can ask a different question. You can ask, well, the output is random. But what about, what about if you were using it for cryptography? Is it, is it, if you use this, you know, if you use that random output, the, the randomness output by this, by this protocol to do, to do cryptography, would your protocol be secure? So there the answer, there, there the question is really, can somebody else guess that randomness? Would they have any better chance than, than whatever, one over two to then? So in particular, here's the worry. So the manufacturer of the box, E, actually entangles herself with both of these boxes. So she, she manufactures these boxes. You know, she builds in the entanglement, but then she entangles herself with these two boxes. So now, everything we said so far is correct. You know, the output is still random, and it's probably random. But it could be that Eve might be able to, she might be able to reconstruct that randomness exactly. Right, so it's, it's, it's no use for cryptographic purposes. Okay, so, so what we can show is that there's a, there's a suptap protocol, which now requires more random bits as input, log cube then, and you have to change the test even more. And, and what you get as a result is that if you apply a quantum extractor, you can, you can get order n bits which look one over poly n close to uniform, even to Eve. So they are really, really random in the cryptographic sense. Too much, but is Eve computing a classical computation? Is Eve, Eve can do, you know, Eve can, let's say that this is all information theoretic, right? So Eve can do, have infinite computing power, but she, she is also quantum, right? She can store quantum information, yeah? But it's not an adversary, it's not the algorithm. No, no, Eve is, Eve is an adversary. Sorry, so maybe, maybe I should have put the box up here, right? So, so let's say the box was, was up here and Eve is outside of the box and- So Eve is not the algorithm that applies this, is it? No, no, no, no, no, Eve, Eve is the, sorry, okay. So, so let's, let's not look at that diagram too closely. Eve is the, is this evil manufacturer of the box. You gave the specifications to her. She made the box for you, or the box is for you.  Right, right, and, and Eve is sitting in her own lab sort of figuring out what your randomness must be and then, right, so, so. Okay, so there, there are some, some related results. So it turns out that this, this, the Peronio et al paper from 2010 actually had a, quite a subtle bug in it. And so there were two papers that both fixed that, that bug in recently and gave a rigorous proof of it. And they also showed in the process that this, this, this protocol is composable. So what this allowed them to show is that you can get this exponential expansion to use, use only log n bits, or, or the log, log or log squared n bits as seed to generate n bits of randomness. But now you have to use four non-signalling boxes, four independent boxes. So when, when they actually, you know, early, early on in, when they first, first came up with this, they actually thought, thought that they could also deal with the cryptographic case. You know, the entangled eave. But it turns out that, again, there's a, there's a, there's, there's, there are these very subtle issues that creep into their proof and it doesn't seem to work. So, so it does seem like, okay, I'll, I'll give you a very small sketch of what we do. And we actually have to work, you know, there are some hoops we have to jump, jump through to make it all work. And as far, you know, this sort of gives us a little more confidence that maybe those hoops are necessary and it's not just because, you know, we picked the, the, the first thing that came to mind. Okay, so let me, let me describe, okay, so here's what I'm going to do for the rest. I'll describe to you the simpler protocol and then I'll just give you a one slide sketch of, you know, what are the main ideas behind the more complex protocol. Yeah. Just another question. So you said that you have like two or four, whatever, like, different boxes and in order to, in order to succeed, these boxes need to share entanglement. Yeah. So where's this entanglement coming from? Right. Does it need to be refreshed, does it need to be? So that, that's, that's, that's to be, you know, so it's whatever, whatever is done. So it depends, you know, if you can store entanglement, maybe you have it set up already. If it's, if, if it has to be communicated, there are ways of communicating entanglement and then distilling it. So, so as, as I'll show you in this proof, you can allow the two, two boxes to communicate with each other, between rounds. And as, as long as within each round there's no communication, everything goes through. So they will sort of. Yeah, they can, so every, if they run out of entanglement, they could communicate and build up more and then, then you could do this again, right? Okay. Okay, so, so here's, okay, so here, here's the, so what we've got to figure out to make all this work out is, what do these inputs, x1 through xn and y1 through yn, look like? Okay, so, so what do the inputs x and y look like? So here, here's what they look like. So they're going to be divided up into blocks of length k, where k is order log n plus log 1 over epsilon, okay? Where the bits within each block are equal. So, so each block consists of either all zeros or all ones. And, and moreover, almost all the blocks are zero blocks. Except once, except for once in a while, when we, when we have a pair of blocks, corresponding blocks, which are called bell blocks.  So there are very few bell blocks, only order log 1 over epsilon. Where the total number of blocks is order n times log 1 over epsilon. And what we're going to do, is we're going to feed these in. So we'll, we'll use our small amount of random, number of random bits to, to generate this string. And then, from then on, the inputs are not adaptive, so we just keep feeding them in and collecting the outputs. And we're going to test that for each block, the outputs satisfy the CHSH condition to whatever degree we want to test it. So if, if our goal is to make sure that, that the correlation is at least 0.8, right? We'll make sure that that's true within each block. And we've chosen the parameters so that if, if you're really working quantumly then, then you satisfy these conditions in each block with very high probability. Okay, so, so now how do we show that, that, that the output of, of this, of this protocol is really random, right? So we want to look at Bob's output, B. And we want to say, this must be a really random output, okay? So, so remember what we are doing. So most of the time, even the two players know most, most blocks are going to consist of all zeros. And so they might try to, try to, you know, they might, if they knew that it was all zeros, they could just output zeros. So no randomness. But every so often, very infrequently, we check that they are, they're doing the right thing by using a bell block. And they don't know where the bell blocks occur. And so what we're going to show is that because they don't know, they are forced to be honest on all the blocks, okay? So, they're all equal to each other. But, but which bit it is, is chosen at random. So it's 50% zero, 50% one. Independently in X and Y. Independently in X and Y. So if you're seeing ones, you know you're going to tell a block.  So if, if Alice sees a block of, of ones, she knows that this is a bell block. But Bob, she doesn't know whether Bob knows that it's a bell block. And so she doesn't know whether she, you know, if she tries to switch strategy because it's a bell block, she doesn't know what to do. And whether Bob will react to it or not. And so, so that, that's the coordination problem. So now we want to show that this is really a coordination problem. And it won't, you know, there's no way that they can coordinate. Okay, so, so here's how we'll show that. So, so we'll start by saying, suppose B's output does not contain much min entropy. There's not much randomness in B's output. So that string is, looks, you know, doesn't have order and bits of randomness. Okay, so then what we can show, you know, then it follows that there must be some block where conditioned on what came before, that block of bits is almost completely deterministic, right? So if there's not much randomness in the, in this output, then conditioned on, you know, there must be some block which is, which is determined by what came in previous blocks. Almost completely determined. So now we're going to use this block to, to show that, that there must be signaling between the two boxes. Okay, and so to do this, we define a guessing game. So, so this guessing game is, goes like this. It's sort of a trivial game. It's, it's a, it's a very silly game if you weren't using it in a proof. So, so the game is like this. Alice and Bob share entanglement. Alice and Bob get random inputs. Alice gets x, which is 50, 50, 0, 1. Bob gets y, which is 50, 50, 0, 1. Independent, and then Alice is asked to guess Bob's input. Okay, it's, I mean, it's a silly game, but that's, that's what, that's what we need to use too. Okay, so what we're going to show, and it's clear, right, that it, you know, Alice cannot guess with probability different from 50%, higher or lower, right? So, I'm sorry? Even if, yeah, yeah, yeah. So in the absence of signaling, there's nothing you can do. So now, okay, so, so how do we, so now what we're going to do is, we're going to show that if there wasn't much, much randomness in the output, therefore there was this block with, with low conditional entropy. So, which is almost deterministic given the past outputs. Then they can use that block to actually signal each other, right? So they violate no signaling. So, so the, the, the way they're, okay, so, so here, here's how they will proceed, so to set it up, let's assume that Bob's output on input zero in this block, in this particular block is almost deterministic and let's say it's B naught. So we look at all the previous outputs and, and given those previous outputs, we know that if in the next block in, in this, in this chosen block, Bob gets input zeros, then his output must be B naught, which is, which is this block, B1 through Bk. We'll assume that the CHSH condition is satisfied for the block which we were checking everywhere. Now Alice, okay, so, so, okay, so here's, here's what we did. We, we simulated the protocol until we got to the chosen block, right? Both, both of them simulated it. When they got, just before they got to the chosen block, they got together and they talked to each other and Bob said, I output such and such and such and such so far, you know, she, he tells Alice and, and now they separate again and now they're not allowed to communicate. So now Alice knows that Bob's output on, on zero for the next, next block is supposed to be B naught. So she knows B, B1 through Bk. She gets as input, you know, she inputs x, x, x, x, x, you know, whatever her input in the guessing game is into the protocol. And she sees what her output is. So let's say it's A1 through Ak, okay? So she just checks whether the hamming distance between A and B is less than 0.2 or greater than 0.2. If it's less, she guesses that y must be zero and otherwise one, okay? And I claim that this, this, this strategy allows Alice to guess Bob's output with probability greater than 50%. And in fact, let me show you that if we are, you know, if, if we are assuming that, that this, that, that the CHSH bound is 0.85, they are, they have saturated the CHSH bound. Then, then we'll actually show that Alice succeeds with probability three quarters. Okay? So, so here's, here's how we prove it. So let's, there are two cases, right? So, so either Bob's, Bob's input is zero or one. So let's say his input is zero, okay? In this case, for the CHSH condition to hold, we want that, we want that for each bit, ai x plus bi mod 2 must be zero, meaning ai equal to bi, right? So we, we expect the a string to be exactly equal to the b string. Well, not, not exactly if you're, you know, if you're, if you're, you, you, you should be, it should be equal 0.85% of the time, 85% of the time. And so the distance between the a and the b string should be 0.15, right? So the hamming distance should be 0.15. So if you draw a hamming ball around b naught of radius 0.2, then regardless of, regardless of whether Alice caught as input 0 or 1, right? Her outputs, her output string must be within this point 2 hamming ball, okay? So, so half the time she's guessed correctly. So whenever y equal to 0, Alice always guesses correctly. So now let's see what happens in the case y equal to 1. Let's, so if we can show that either on input x equal to 0 or x equal to 1 for Alice, she guesses correctly, then, then we'd have shown that there's a 3 quarter of chance altogether of guessing correctly. So here's how we show that. So in this case, Bob's input is 1, which means we have no idea what his output looks like. Alice has no idea what his output looks like. She only knew that if his input was 0, then his output is almost certainly b naught. But now his output is some string that she doesn't know, let's say b1, okay? But now, in order to satisfy the CHSH condition, if x equal to 0, then Alice and Bob's outputs must match. And if x equal to 1, they must, they must be, they must not match. They must be the opposite, right? Meaning that for each bit, there's some particular output such that Alice's output is supposed to match each bit with probability 0.85 in the case that her input is 0. And on each bit, it's supposed to match with probability 0.15 in the case that her bit is 1, right? So let's say that a naught prime and a1 prime are her two output strings in the two cases. Then on each bit string, they on average match up with probability at most 0.3. Meaning the distance between a naught prime and a1 prime is at least 0.7, right? But, okay, so now what the question we are asking is, so we don't know where a naught prime and a1 prime are located relative to b naught. But the question we are asking when Alice decides whether to guess 0 or 1 is whether her output is within 0.2 of this guess string b, b naught. And the point is inside this hamming ball of diameter 0.4, radius 0.2, you can have at most one of these two strings, not both, right? So at least one of them is outside and so at least on at least one of them, she must output one.  So now I did this analysis assuming that we satisfied CHSH perfectly at 0.85. We saturated it. But now if you assume anything slightly above 0.75, 0.75 plus epsilon, then you get some half plus some function of epsilon. And so you get a contradiction all the way down to anything slightly better than classical, okay? Okay, so that's the proof of the simpler case. Now to deal with quantum adversaries, it gets a lot trickier. Okay, so here's the problem. So the crux of this argument I just showed you is that if b's output does not contain much main entropy, then there's some block of his output, which is almost completely determined given the past blocks. And now you can play a guessing game on this block to derive a contradiction, right, Alice and Bob play a guessing game, okay? In this quantum adversary setting, it could be that Bob's output is perfectly random, okay? But what we want to show is that Eve cannot guess it. So we really cannot use that approach the way it is up there, okay? So what do we do instead? So what we show is that if we use a particular extractor, which is the Travisan extractor, or what's locally here called Luca's extractor. Using a particular implementation, using Tx or codes, okay? So this particular extractor was proved to be secure also against quantum storage by Anindya Dey and Thomas Vidic. I guess one of each of our students. Then, okay, so the point is that let's use this extractor to take Bob's output and try to get random output from it. So then the proof of this extractor goes through what's called the reconstruction paradigm, meaning that, okay, so using the proof and actually something else in quantum computing, which is that, okay, so there's some associated work of Terhal et al. on pretty good measurements, which sort of implies that, in fact, if the output of this extractor is not random, then actually Alice can provide Eve with some small amount of side information, which allows Eve to reconstruct the output of the extractor. And now once Eve can reconstruct the output of the extractor, we are back in the situation above, where there's somebody, so we put Alice and Eve together and they can guess Bob's input. So they can solve the guessing game. The combination of Alice and Eve without communicating with Bob can solve the guessing game, okay. Okay, so that's sort of the big picture of this part. There's this very interesting last step to it, which is, of course, what this showed is that if you use this particular extractor, the Traversan extractor using TXOR codes, then the output must be very close to random uniform. But of course, if the output is now close to uniform, there must be a lot of min entropy that you started from. And therefore it shows that it didn't matter whether you use this extractor, you could use any extractor, which is quantum secure, and that would work. Okay, so this is the construction of these certifiable quantum for certifiable random generators. I don't think we really understand this thing too well yet. So I at least don't feel that we really understand what the certification means and where it's going, so on. So it's really something we are trying to work through and understand. Well, both what it means to be able to certify something as random as well as how one can use it in other ways. And there seem to be some approaches. So, thank you. Someone is not just a quantum skeptic, but is a randomist skeptic as the Einstein quote seems to suggest. So what would Einstein think about that? I mean, the setup of the problem and what we're asking to accomplish involves kind of believing some model of the world in which randomness exists and we can reason about it. Right. Yeah, so somehow you're right. So just to get off the ground, one has to believe that there's a small random seed that we start from. And if you don't assume that, then the argument doesn't get off the ground. But once you assume that, then the rest of it is completely independent. So that's being used to actually test. So somehow somebody could say, well, maybe the entire world is against me and there's a completely different, you know, so against me or maybe somebody has a different view. Perhaps the entire universe is conspiring in my favor but none of the accepted models is true and really there's a conspiracy to feed me these inputs and I'm inside a movie or virtual reality and it has its own laws and then there's nothing you can do about it unless you assume that there's some private randomness which allows you to test that virtual reality environment which that virtual reality environment is not aware of. So you need something to get off the ground. So the model is some kind of private randomness in that one hand that's no signaling has something to do with nothing of communicating the values of that private randomness between the two boxes. Right. Yeah. I'll be coming down a little bit.  Right. Yeah. And maybe those don't need to be independent. Right. Maybe you could do log n or epsilon plus log n. Actually that's a very good point. Yeah, that's a great point. So related to that, you know, what we know is that log 1 over epsilon is necessary but the only thing we know about the log n being necessary is because you need it at least for the extractor.  So you get only log 1 over epsilon and then you can get any amount of min entropy from this. So that we don't know yet. Yeah. This is a question of physics. I have seen lately many proposals for quantum random number generators in this literature. They might make ten different proposals. And they all claim that some advantage over the others. But I don't think there's a clear criterion which can say that this method of quantum random number is better than the other. Do you think one can... formulate in such kind of preparing maybe this certificate ability or some other... Well, yeah. So there are certainly many, many proposals for quantum random generators. But I think the question that those are trying to... solve... you know, they're just trying to say, well, you have an intrinsic source of randomness in quantum mechanics. And now how do you get at it practically or in some interesting way? I should mention that the Pyronian at all paper, I think I forgot to say this, the one that appeared in Nature in 2010, its main point was actually... what they did was... they actually implemented this. And so they collected... you know, they set up their apparatus and they let it run for a month and they collected something like, you know, 3,000 entanglement events and they derived, you know, eventually using this scheme, they eventually managed to derive 40 certifiably random bits. And they sort of said, well, this is the first time in history that you have certifiably random bits from an apparatus about which you assume nothing. And then we don't see them. Who knows? So, just to be on the safe side, they didn't publish that string. More questions? Let's thank them again.


When cultivated under stress conditions, many microalgae species accumulate both starch and oil, triacylglycerals, clamidominus reinhardti has emerged as a model to test genetic engineering or cultivation strategies aiming at increasing lipid yields for biodiesel production. Blocking starch synthesis has been suggested as a way to boost oil accumulation. This article was authored by Carrier Patrick, Nguyen Mai, Fesla Boris, and others.


My name is Matthew Barne. I'm a senior lecturer at the Open University. I run the Plantry Environments Research Group. What we do is we look at the landscapes of different planets, Mars, Venus and the Earth and we try to understand how they evolve and their history. This picture shows a debris flow from Iceland that happened a few years ago. At the top of the picture you can see there's a little arc shape of dark material and that's a slump. All of that material that was there has slumped down slopes. And it turns out that it was actually full of ice and that ice melted which triggered a debris flow. Fortunately this event happened a long way from people and habitation but there are similar looking areas that haven't had landslides yet that are above areas with lots of people and infrastructure. So this is what we're going to be doing in our next project is to go and investigate these in more detail. Well I've been doing this for about 15 years. I did my PhD a couple of years before that. I started off on Venus, then I moved to Mars and that's really what I wanted to do because Mars is such an exciting planet. It's got the same range of processes and sort of types of environment that you see on Earth but it's totally alien and the really cool thing about Mars is you can imagine us going there. This image gives an example of the sort of work we can do on Mars now. On the right is an actual Mars image from NASA's high-rise camera and this is a really high-resolution camera. It gives colour as well. But the cool thing is we can turn that into very high-resolution topographic models and then we can do our modelling wizardry to help understand how that landscape evolved. On the left is what we call the Wetness Index. It's a simple model that shows where water would have been if water was flowing over this landscape. From that we're able to move on and say whether this landscape was created by wet processes or dry processes, for example just rocks and dust falling down the slope or by moist processes.   So this experiment here is to simulate that. It's a little sandy bed and we put dry ice into it and then we let it warm up and observe with several cameras looking in 3D again to see how the change in volume and the change in slopes occur. And hopefully we'll be able to scale that up to real Mars. It's Mars.  So the work I do at some point a future geologist is going to stand there and read my papers and say, he was wrong. Or, what a clever guy. That's amazing. And I really like that because you feel like you're doing something for the future which at the same time is really exciting.


Sounds good? It is good. Well, the business quadrant is extremely simple in its idea but it does require a certain level of openness to new ideas. It's basically a template where you structure your business in a way where it focuses on the things that you're really good at, you're really passionate at and actually leverages things that are going to be good for you. On the other hand, things that you're not good at or you don't like, it's they're under leveraged or completely ignored. So that way you can create a business where you only do what you like doing. What you like doing is actually what leverages the business to become better and better and you don't have to focus on or even participate or even think about things that you don't like.  I did this with a lot of clients of mine. I did this in various lectures and of course for me and it works like magic. So listen up. The business quadrant is very simple. You want to put it in four squares. So the first one would be things that you love and that you're good at. That's where you want to put again everything that you love and you're good at and that's where you focus your entire point, the entire leverage of the business. So let's say you're really good at selling and it's something you love. Well then you want to focus your business around that compartment or let's say you're good at marketing or making videos or coaching people, whatever it is. You want to write down things that you're good at and you love. Next up you have things that you're not good at but you love as well. Well in this case I would urge you to simply consider them as if you're already good at them.  Well that's not really a problem because you're going to get better at it and once you get better, if it's something you love you're going to get better at it. So it's not really an issue. So you can leverage your business around that even if you're not good at it. Yet it's just a matter of time and patience.  Let's say it's things that you were in the past you loved and now you don't love them. For example for me it's stuff like designing, coding, programming, marketing, things like that. I used to be really good at them and really love them but now these are not really my type of things anymore. So I'm putting them in this category and what that means is I want to use them as instances. So I want to take this part of the business and do it in a way where let's say I create a marketing campaign and I only need to do it once and then it keeps repeating and doing the work for me so I don't have to focus on it. I just use my skill once and since it's not a major part of the business it's automatic. I don't need to focus on it or let's say I'm really good at selling but I don't like selling. What I can do is put the part of the business where I teach people how to sell and then I only need to do it once per person I teach but they do it many times. So I use my skill to create instances of people who use my skill or computer who replicates my skill. That's what this quadrant part is for and the last one is things that you're not good at and you hate. These things you want to make sure that your business is not at all around them and under leverage these parts for me for example it's things like accounting. I really really hate accounting so we're on my businesses in a way where I have an accountant and he takes care of everything and I don't even need to think about it.  I trust you again because I picked the right accountant and I just let him do what he needs to do because the business is not really based on having good tax rates or anything it's more based on the actual part that I like. So what I like for example is creating videos, creating content, it's destroying people's minds like you, it's changing people's beliefs, it's coaching people so I make sure the business is leveraged around these things. So the better job I do the better the business does in a very leveraged way. So let's say I do this twice as good the entire business is going to be ten times more highly revenue grossing and then you have the things that you don't like anymore but you're good at. These for example are marketing campaigns that I set up it's people who I taught how to sell for me basically again things your instance you make them automatic either you give them to the computer and you want to make it automatic computer based if it's things like math or you know a sales page or a campaign basically things that you can replicate but don't need actual human delicacy or it's quantity over quality on the other hand you want to replicate things using people there including selling making you know customer phone calls things like that because these things have a very personal nature so you want to prefer quality over quantity so again the premise is very very simple things you love and things you hate and things you're good at and things you bad at again good and love you want to put in these categories everything that you want to leverage in your business so that's what the business is going to be about so if you really love selling make sure our business is focused around selling and everything else is automatic for example if you really love selling you could create an online campaign or let somebody else run it for you and then all you need to do is just sell let's say that you really love making videos well you want to make the other parts of the business automatic and leverage the part where you just make as many videos as possible and that's where the revenue comes from again this model is extremely simple this is a very quick overview of it and I will explain it in much further detail in the future but I hope this gives your good glimpse into how you can create a business where you just have fun do what you love and make a lot of money doing it enjoy till next time


So I have been on a never-ending search for the proper web browser. I have been a Firefox user For ever since the beginning of Firefox I've been a Firefox user and it's great for a full featured web browser but I've always wanted something more minimal more privacy oriented and Looking at various minimal web browsers and I've looked at a ton of them. None of them have really been Satisfactory they all have some pretty serious shortcomings, but I came across one the other day that Really impressed me and this is the first one. I've ever launched and started using right away that within a few minutes I thought yes, this is usable everything else that I've tried in the past all the other minimal web browsers I've tried in the past. I opened them up and within a few minutes I find things that are way wrong with them, but this one I don't know I'm impressed with this one I thought I needed to make a video and share this particular web browser with you guys because it's one you guys have probably never heard of it's One I had never heard of until the other day I came across a mention about this particular web browser on reddit and this web browser is called bad wolf now bad wolf is a Minimalist and privacy oriented webkit GTK browser and I've tried other webkit GTK browsers in the past minimal webkit GTK browsers things like Succes's surf browser which is really nice But that particular browser was slow the surf browser if it just had better speed as far as it didn't take Like a day and a half for a web page to load I would probably use surf as my main web browser, but the speed is it's just too bad with surf Qt browser was also originally a webkit GTK browser and then they switched I think to the chromium engine I think now though you can actually compile Qt browser to use Webkit GTK if you still want to use it that way Qt browser though is a fantastic browser But it has some limitations to the big one that most people have is the fact that Qt browser really doesn't have a way To block ads there's no ad blocker plugin that works Some other minimal web browsers I've installed and just very briefly taking a look yet I haven't done anything on the channel with them But because I haven't spent but you know a few minutes at a time in them I've taken a look at vmb taking a look at the min browser I've taken a look at you know a lot of these alternative minimal web browsers But bad wolf is really interesting. It has a very small code base It is written in under 1500 lines of code And of course the 1500 lines of code doesn't include webkit GTK This is just the bad wolf, you know browser itself the skin on top of you know all the webkit GTK stuff It is customizable. It's got some native extensions. It has a really nice interface And you'll see that when I launch it and it does have some nice sensible keyboard shortcuts Those keyboard shortcuts are not Vim shortcuts, so they're not Vim like bindings So that may or may not be a problem for some people The creator of bad wolf though. He says he purposely avoided Doing the vi modal kind of stuff, you know with the key bindings in bad wolf because so many other minimal browsers already do that He was looking for something Not vim like as far as the keyboard commands and everything in bad wolf Which I can respect that when I was looking through the yet history of bad wolf I noticed that this guy has been developing bad wolf for about a year and about a month ago He actually released what is officially called bad wolf one dot zero dot zero So it's now a one dot o release. So I guess this would be the first Non alpha or non beta release, but again, I don't think most people have ever heard about this You know, it's a small project a one-man project And I did notice that bad wolf even though you can grab the source I did notice somebody actually packaged bad wolf for the a u r So if you're on arch linux or any arch linux base distribution You can do a yay dash capital s bad wolf and you can actually install bad wolf directly from the a u r So let me switch over to the desktop And this is the cutal window manager that I'm in today And I needed to log into this particular window manager because I've been spending a lot of time in x-mode add And in exwm here recently and those two particular window managers I have a lot of key bindings that involve both the alt key and the control key Well bad wolf this particular browser has a lot of keyboard shortcuts that involve both the alt key and the control key So I know cutal. I don't think I have any keyboard shortcuts that involve control or alt and cutal Most everything is using the super key for the modifier key. So let me launch bad wolf. I'm on the wrong Screen here, but this is bad wolf by default when you first launch it You have a empty tab this blinding white tab. It says new tab. You also have this tab here It's not really a tab though. This is your downloads screen. Of course. I haven't downloaded anything So this screen is empty as well, but let me go back to the new tab But what's really interesting about this interface is you have two things that you can toggle on and off at will And that includes javascript which is by default toggled off And images which by default is toggled on now. Let's go to a website. So if I went to youtube.com Since javascript is toggled off.  So the speed is is not bad actually with bad wolf Let me turn images off. I know we need javascript Enable to load youtube, but you don't necessarily need images to load I mean you can render the page without images and you know, it's the same page Just no thumbnails or anything if I click images on all of a sudden the images load for us I really like the simple clean user interface here I would prefer it be a little more minimal I would like the tab bar at the top to be toggled on and off You know have that ability to toggle it on and off show and hide when you need it Same thing with the url bar.  You have the forward and back buttons You can toggle on javascript and images You have a print button over here and then you have this button here that says open new tab And if you click that of course now you get a new blank tab I can close that also in the bottom you have a status bar, of course, but you also have the search Field here and that's the same as if you did it like a control f I can go ahead and talk about some of the keyboard shortcuts if you do control f You automatically go straight to that search field at the bottom there And this page is blinding white. Let's open up a new tab And let's go ahead and talk about the keyboard shortcuts if you want a new tab control t As a keyboard shortcut to get you that new tab then you can do alt and the number of the tab So that would be the second tab. So if I did alt two or is it alt three I think it's going to be three because one is the downloads two is youtube three Is the empty tab the new blank tab And if I wanted to I could go to my website if I did control l I can get into the url field And then I'm going to type https And let's go to distrotube.com. Let's get into a dark website so we can get into something That's not so blinding white and my site here distrotube.com doesn't really require any javascript At least not the main portion of the site. Maybe the forums Require some javascript. I'm not sure on that and you know the speed and everything The rendering of the pages is quite fast. Let's go over to the blog and I'm going to click on an article And how do you zoom in and out because that's a big thing in most web browsers? Sometimes you need to zoom the text in and out for readability Well, you do this by holding the control button and then zooming in and out with the mouse wheel So if I just zoom in with the mouse wheel and zoom back out with the mouse wheel And if you ever want it to set it back to the normal Setting control zero should set it back to the default view setting But let me do a control t to open up a new tab And then I'm going to do alt four to go to that fourth tab that I just opened the new tab And if I did alt d I could delete that tab So remember control t for a new tab and then alt and the number of the tab to go to that tab alt d closes that tab And pretty much that is most of the key bindings you need to know I mean there's a couple of more but they're pretty much not key bindings you would ever use F1 on the keyboard gets you the about information for bad wolf really I've shown you pretty much all the keyboard shortcuts and you have seen everything there is to see as far as the user interface for bad wolf One interesting thing is in a tiling window manager, you know, you don't have a menu system or anything You have to use the keyboard shortcuts for your tiling window manager to close bad wolf So for me super shift c closes any window with focus here in cutal But like if I close that tab and I close that tab, I've closed out all the tabs There's no way to close out the downloads tab. There's no menu system to exit out of you Actually do have to close it out with a keyboard shortcut If you're in a tiling window manager, those of you that are running Traditional desktop environments with floating window managers, of course, you're going to have a close button As part of your your gtk theme or whatever Now one other thing I want to just briefly mention if you do install the bad wolf browser from the AUR One thing I did notice let me open up a terminal here and if I run a man bad wolf The man page is broken. It's broken in one big way You're probably the main reason why you would launch this man page, of course, is to get the key bindings There's one problem though. The key bindings have the descriptions But the bindings for those descriptions are not there There should be a key binding here where it says, for example, closes the current tab Well, I showed you that was alt D. Where is alt D? It didn't make it. So I probably need to file a bug report with the bad wolf developer to let him know that his man page at least Regarding the AUR package is broken. If you need a proper man page though for bad wolf What you can do is go to the bad wolf site And I'm going to link to the site in the show description and if you go to the bad wolf website Um about uh just a third of the way down that page You see powerful and useful and then you see this link that's written in this pinkish text that says Shortcuts and documented click on and documented And you get a web version of the man page for bad wolf that does include the key bindings as well as the description for the key Bindings. So that was just a very brief look at this Rather interesting minimal and privacy oriented browser that is bad wolf. I love The somewhat minimal interface. It could be more minimal for my taste, but it's not bad It's minimal enough for me. I kind of like it. I love the fact that javascript is disabled by default And for me, I would just leave it toggled off except for the websites that I go to where I absolutely have to have Javascript, which for me is really just a couple of websites I visit that absolutely have to have javascript and I have to be on those sites youtube being the most obvious example Will I start using bad wolf as my Daily browser? I might I uh, I probably am at least for a little bit. I'm going to give it a shot for you know, a couple of weeks Because I'll be honest most of the other minimalist browsers that I've tried I didn't make it in on that long. There were just too many paper cuts, you know, too many pain points But bad wolf it's a pretty nice web browser. I mean it it functions like a proper web browser But it just doesn't have all that extra crap That I don't need in those full feature browsers like firefox and chromium and things like that anyway So guys, I urge you to actually check out bad wolf. This is a good web browser Now before I go I need to thank a few special people I need to thank michael gape haplonate corbinian mitchell entropy uk arch 5530 chuck dj donnie dill and george omri paul shon to bias and willy These guys they are the producers of this episode without these guys You wouldn't know about this ultra minimalist Privacy oriented browser that is bad wolf. You wouldn't know about it The show is also supported by each and every one of these ladies and gentlemen All these names you're seeing on the screen right now This is all my supporters over on patreon because this channel is supported by you guys the community You'd like to support my work. You'll find dt over on patreon. All right guys peace


Live from Las Vegas, it's theCUBE. Covering Dell Technologies World 2019. Brought to you by Dell Technologies and its ecosystem partners. Okay, welcome back everyone. CUBE's live coverage day three, wrap up of Dell Technologies World 2019. I'm John Furrier, Dave Vellante, Stu Miniman. On set one, we've got the set two over there. Blue set, white set, we've got a lot of content. It's been a CUBE canon, guys, a canon of content firing into the digital sphere. Great guests. We've had all the senior executive players, tech athletes at Dell Technologies World, Michael Dell, Tom Sweet, Marius Haas, Howard Elias. We've had Pat Gelsinger, CEO of EM. We're on the key partner in the family there of Dell Technologies World. And we've had the clients, guys on who do Alienware as well as the laptops and the power machines. We've had the power edge guys on. We talked about Hollywood. It's been a great run. But, Dave, it's been 10 years, Stu. Remember the first CUBE event we ever went to was EMC World in Boston. The chowder there we had. And what was the slogan of that show? Journey to the Private Cloud. I think that was the slogan. Journey to the Private Cloud. That was 2010. Well, in 2010, it was Cloud, Cloud, Cloud, Cloud, 2019, it's all cloud. Now, the difference is, back then, it was like fake cloud and made-up cloud and really, there was no substance to it. We really started to see, Stu, especially something that we've been talking about for years, which is substantially mimicking the public cloud on-prem. Now, I know there are those who would say, no, no, no, no, no. Andy Jassy probably being one of those. That's not cloud. So there's still that dichotomy. Is it cloud? Well, Dave, if I could jump in on that, one of the things that's really interesting is when VMware made that partnership with AWS, it was the ripple through this ecosystem. Oh, what's that mean for Dell? VMware and Dell not working together? Well, they set the model and they started rolling out in VMware and they took the learnings that they had and they're bringing that data center as a service down to the Dell environment. So it's funny, we always hear AWS, they're learning from their partnership, they're listening and everything like that. Well, Dell and VMware, they've been listening, they've been learning too in this and it brings into a little bit of equilibrium for me that partnership, and right, David, you said, there used to be that cloud-washing discussion and today we're talking about stacks that live in AWS and Google and Microsoft and now in my hosted or service provider or my own data center, if that makes sense. I mean, if you want to just simplify the high order bit, Dave, and cloud, it's simply this. Amazon's trying to be enterprise, everyone in the enterprise is trying to be Amazon, right? And so what that basically means is it's all cloud, it's all a distributed computer system, okay? Scott McNeely had it right, the network is the computer. If you look at what's going on here, the traditional enterprise vendors over decades of business model and technology, you know, had full stack solutions from mainframe, mini computers, to PC, the local area networking, all cobbled together, IT wires it up, creates application services, all of that is completely being decimated by a new way to roll out storage, computing and networking, it's the same stuff. It's just being configured differently. Throw on massive compute power with cloud and Moore's law and data and AI, you have a changing of the architecture. But at the end of the day, the cloud is an operating model of distributed computing. If you look at all the theories and theses of computer science do and networking, all those paradigms are actually playing out in the cloud, everything from AI, AI in the 80s and 90s, you got distributed networking and computing, but it's all one big computer. And Michael Dell, who was the master of the computer industry, building PCs, looks at this probably like it's one big computer. You got a processor and subsystems, so this is what's interesting, Amazon has done that. And if they try to be like the enterprise, like the old way, they can fall into that trap. So if the enterprise stays in the enterprise, they know they're not going to be well. So I think it's interesting how you see the enterprise trying to be like Amazon, Amazon, trying to be like the enterprise. So at the end of the day, whoever can build that system, that's scalable the way I think Dell's doing it's great, horizontally scalable, using data for specialty. So it's a distributed computer. That's all that's going on in the world right now. And it's changing everything. Open source software is there. All that makes it completely different. And it's a huge opportunity. Whoever can crack the code on this, it's in the trillions and trillions of dollar total of adjustable market. Well, in 2010, we said that we noted the gap. There's still a gap between what Amazon could do and what the on-prem guys can do. We'd argue it was a five years, seven years, maybe 10 years, whatever it is. But at the time, we said, if you recall, look it, they got to close the gap. It's got to be good enough for IT to buy into it. And I think we're starting to see that. But my view, it's still not cloud. It doesn't have the scale of cloud. It doesn't have the economics cloud. And when you peel the onion, it certainly doesn't have the SaaS model and the consumption model of cloud nowhere close yet. Well, and you know, here's the drumbeat of innovation that we see from the public cloud. You know, we're at the show this week, the public cloud providers, how many announcements that they probably had? Sure, there was a mega launch of announcements here, but the public cloud's just that regular cadence of there. You know, public cloud CICD. We're not quite there yet in this kind of environment. It's still, what Amazon would say is, you put this in an environment and it's kind of frozen, well, it's thawed some. And it's now, we can get data center service, consumption model is something we can go. We're shifting in that model. It's easier to update things, but you know, how do I get access to the new features? But we're seeing that blurring of the line. I can start moving services, that hybrid nature of the environment. We've talked a few times. We've been digging into that hybrid cloud taxonomy and some of those services to span because it's not public or private. It's now truly that hybrid and multi environment and customers are going to live in all of these. And the question, John, is it good enough to hold serve? Well, I think the reality is, is that, you can go back to 2010, the journey of the private cloud. Enterprise is almost 10 years to figure out that it's real. And I think in that timeframe, Amazon has absolutely leveled everybody. We call it the tsunami. Microsoft quickly figures out that they got to get cloud. They come in there, got a fast follower second. Google's trying to retool Oracle. I think missed the boat completely. Got Alibaba and IBM in there. So you got the whole cloud game happening. The problem with the enterprises is that there's no growth in terms of old school enterprise other than reconciliate and position for cloud. My question to you guys is, is there going to be true growth in the classic enterprise business? Or will all this SaaS run on cloud? So yes, if it's multi-cloud or even hybrid for the reasons they talk about, that's not a lot of growth compared to what the cloud can offer. So again, I still haven't seen, Dave, the visibility in my mind that on-premises growth is going to be massive compared to cloud. I think cloud is where SaaS lives. I think that's where the scale lives. And how much scale can you do with consolidation? We are in a prolonged bull market that started in 2010, and it's gone on, we're in the 10th year of a decade of bull market. The enterprise market is cyclical. And at some point, you're going to start to see a slowdown.  Cloud can grow in a downturn, the- But Dell pointed out on this, Michael Dell pointed out on the Cubans as the lieutenants. The IT is, the consolidation of IT is just a retooling to be cloud ready operationally. That's where hybrid comes in. So I think that realization has kicked in. But as enterprises aren't like, they're not like Google and Facebook, they're not really that fast. So they got to kind of get their act together on-premises, that's why I think in the short term, this consolidation and new revitalization is happening because they're retooling to be cloud ready. That is absolutely happening. But to say that's the massive growth, Stu, I don't know. Look, as Dave's pointed out, the way that there is more than the market growth is by gaining market share. There are areas where Dell and EMC didn't have large environment. I spent 10 years at EMC. I was a networking guy. It was mostly storage networking, some WAN connectivity for replication like SRDF and like today at this show, I talked to a lot of the telco people, talked to the service providers, talked to where the SD WAN, the NYSERA, some of these pieces, they're really starting to do networking. That's the area where that software defined, not SDN, but the OEM partnership with companies like BigSwitch. They're getting into that market and they have such small market share there that there's huge uplift to be able to dig into the giant in that space. Okay, couple questions. What percent of Dell's 91 billion today is multi-cloud revenue? Great question. Okay, what percent? I mean, very small. Okay, very small. Zero. And is that multi-cloud revenue all incremental growth? Or is it going to cannibalize the existing base? These are the fundamentals of the cyclical market that I'm talking about. To get into this, you love the financial conversations. We had Tom Speedon, the CFO, he nailed this. He said there's multiple levers to share older growth. Pay down the debt, check, he's got to do that. You love that conversation. Margin expansion, get the margins up, use the client business to cover costs, as you said, increase go-to-market efficiency and leverage the supply chain.  Throw up cash, and that all leads to cash. Okay, one thing he said that was mind-blowing to me is that no one gets the valuation of how valuable Dell Technologies is. They're throwing off close to $7 billion in free cash flow. Free cash flow. Okay, so you can talk margin expansion all you want. That's great, but they've got this huge cash flow coming in. You can't go out of business right now. Listen, you don't run out of cash. When the market is good, these guys are in as good a position as anybody, and I would argue better position than anybody. The question on the table that I'm asking is, how long can it last? And if and when the market turns down, and markets are always cyclical, we're like, again, we're in a 10th year of a bull market. I mean, it's somewhat unprecedented. If Dell can use the war chest of the free cash flow, check on these levers that they're talking about here. They're going to have the leverage to go in during the downturn and then be the cost optimizer for customers. Right now they're going to be taking their medicine, creating this one common operating environment, which they have an advantage because they have all the puzzle pieces. Ula-Pakar Enterprise doesn't have, they have gaping holes in the end to end. They can't address it. So that is a really good point that you're making now. So then the next question is, okay, if and when the downturn comes, who's going to take advantage of it? Who's going to come out stronger? I think Amazon is going to continue to dominate, and as long as they don't fall into the enterprise trap of trying to be too enterprising, continue to operate their way for enterprises, I think Jassy's got that covered. I think Dell Technologies is perfectly positioned to leverage the cash flow and their thing to do that. I think Cisco's got a great opportunity, and I think that's something that you don't hear a lot talk about the EMware Cisco war happening, but Cisco has a network. They have a developer ecosystem just starting to get revitalized. That's an opportunity. So I got thoughts on Cisco too, but one of the things I want to say about Dell being able to come out of that stronger, I keep saying, I've said this a number of times and asked a lot of questions this week is, the PC business is vital for Dell. It's almost half the company's revenue, maybe not quite, but it's where the company started, and it sucks up a lot of corporate overhead. If Ulet Packard did not spin out HPE and HP, they would be in the game. I think spinning that out was a huge mistake. I wrote about it publicly, took a lot of heat for it, but I try to go along with the HPE focus. Dell has proven bigger is better. HP has proven that smaller is not as leveraged. If they had the PC, they'd have the Mojo in gaming, they had the Mojo in the edge, and Dell's got all those levers to cross-pollinate the front end and edge into the back end, common cloud operating environment. That is going to be an advantage, and that's going to be something that we'll see how that's going to play out. Let me counter what you just said. I agree, the spin out, but the autonomy was the big mistake. Once HP bought autonomy, what Meg did was almost a fate, a complete, they never should have bought autonomy. Meg was Leo Apatekker. But she inherited that bag of rocks, and then what are you going to do with it? Okay, so that's why they had a spin out, and it did create shareholder value. If they had not purchased autonomy, then it would have been a much better shape, not to split it up, and they would be a much stronger competitor now. Shareholder pop, they had a pop on value, people made some cash for the long game, I think that's going to hurt them. HP Inc has actually done pretty well for shareholders. As a standalone PC company. But again, I think Dell, with that leverage, assuming PCs, it's going to be really interesting. I don't know as much about that market, you were loving that PC conversation, but the whole, you know, the new gamer markets, and the new way to work, they're throwing an edge in there. I don't know, is edge, is PC an edge, is that sort of peanut butter? So the big thing that Michael Dell said on theCUBE was we're not a conglomerate, we're an integrated company, and when you have an integrated company like this, with the tech landscape shifting to their advantage, you have the ability to cross subsidize. So the strategy game, if Matt Baker was here, we'd be talking about, okay, I can cross subsidize margin, you even brought it up on the client side. Smaller margins, but it pays a lot of the corporate overhead. So then you got higher margin EMC business, which you know those margins, that's contributing. And so when you have this new configuration, you can cross subsidize and move and shift. So I think that's a great advantage, I think that's undervalued in the marketplace. And I think Dell, stock price, is well undervalued, you point out the numbers, they got VMware in there. The question is, what point does VMware blink and go all in on Dell technologies too? Or, because remember, Pat Kessler's got a partner. You don't think the phone was ringing off the hook in Palo Alto from their partners? What, and what's this Azure deal? So VMware's got to be the neutral party.  Well, look, if I'm a traditional, historical partner of VMware, it's not the Azure announcement that has me a little bit concerned, because all of them partner with Microsoft too. It is how tightly combined Dell and VMware are. EMC always kept them in arms like, now they're in the same. It's like Dave, they're blending it. It's like Dell from a market cap standpoint gets 50 cents on the dollar. VMware is a software company and they get their multiples. Dell is not a software company, but VMware, pivotal are. Well, if we can blend that a little bit, maybe we can get that market cap off. Is it too blended? No, no, I think the strategy is absolutely right on. You have to go hard with VMware and use it as a competitive weapon. But studio point, 50 cents on the dollar, it's actually much worse than that.  Core Dell is undervalued. Core Dell is worth more than a billion or two billion dollars, okay? So, it's a really cheap way to buy VMware, right? Tom Sweet nailed this. He said, you know, basically these companies, the street's not used to tech companies having such big debt. But to your point, John, they're throwing off cash. So, this company is undervalued in my view. Now, there's some risks associated with that. And that's why the investors are penalizing them for that debt. They're penalizing them from Michael's ownership structure. You know, that's what this is, but. I think there's a lack of understanding in my opinion. I think. I just think they don't understand, look at Dell and they think GE, they don't look at Dell and think distributed computing system with software filling this gaps and all that extra 10 expansion. It's legit. I think they can go after new market opportunities as obtuse to us as the client business. I mean, mirroring trade ends and just that's massive, trillions of dollars is. So I think that is a huge deal. But I'm a bull. I'm a bull on the value of the company. I think there's no question. All right, guys. Most important developments. Dell technology world. What's the big story that you think is coming out of the show here? Well, it's definitely, you know, the VMware on Dell. I mean, that is the big story. And it's, to your point, it's Dell basically saying we're going to integrate this. We're going to be hard. We're going to go hard.  No doubt that is top for Dell. And Pat Gelsinger said it. VMware and AWS is the first and preferred solution. Those are the two primary vectors that are going to drive hard. And then, oh yeah, we'll listen to customers, whatever else you want, Google, Azure, fine, we're there. But those two vectors, they're going to drive really hard. Yeah, Dave, I'll build on that because we saw VMware building out its multi-cloud strategy. And what we have today is Dell is now putting themselves in there as a first-class citizen. Before it was like, oh, we're doing VxRail and NSX and, you know, we'll integrate all these pieces there but infrastructure, infrastructure, infrastructure. Now it is, it is multi-cloud. We want to see it at the big table. Right. And Jeff Clark said, why are you doing both? Let's just, one strategy, one company. It's all one cash register, is the saying goes. Yeah, I heard that before. I think the biggest story to me is something that we've been saying in the KubeLaw, you know I've been on this rant. Horizontally scalable operating environment is the land grab and then vertically integrated with the data into applications that allow each vertical industry leverage data for the kind of intimate personalized experiences for user experiences in each industry. Whether it's oil and gas, public sector, each one has got their own experiences that are unique, the data drives that. But the horizontal end-to-end operating model, whether it's on-premises, hybrid or multi-cloud, is a huge land grab. And I think that is a major strategic win for Dell. And I think if no one challenges them on this, Dave, if HP doesn't go on an M&A change, if HPE does not do a M&A complete change-over from strategy and fill in their end-to-end, I think that going to be really hurting. I think there's going to be a tell sign and we'll see who reacts and challenges Dell on this end-to-end. And I think if they can pull it off without being contested. The only thing I would say to that, the only thing I would say to that, John, is you know HP very well. I mean they got a lot of loyal customers and there's a huge market out there. So, you know it's- Dave, the economics are shifting in the new world. New use cases, new step function of user experiences. This is going to be new user experiences at new economic price points. That's business model innovation. Loyal customers, that's hard to sustain. They'll keep some clutching and grabbing, but everyone will move to the better mousetrap in this scenario. So, the combination of that stability with software, it's just- It's a big market. So, John, 2010, little table, that corner of EMC, Dell Technologies World, double set, beautiful theater of presence. Lot of things change in the industry, but the partnership and support of this ecosystem is something that's helped us along the way. You know, when we started doing this, Jeff came on board, the team has been amazing. We have been growing up and getting better every show. Small incremental improvements here and there. It's been an amazing production, an amazing team, all around us, but the support of the communities do. This has been a co-creation project from day one. We love having these conversations with smart people, tech athletes, make it unique, make it organic, let the paid stuff on the other literature pieces go well, but here it's about conversations for and with the community. And I think the community sponsorship has been part of funding more of it. You're seeing more cubes.  I mean, Stu, what have we missed? Yeah, it's phenomenal. You know, we are at a unique time in the industry and honored to be able to help document it with the two of you and the whole team. Dave, Howard Elias sitting there, giving him some kind of a victory lap because he's been with us for 10 years. He's been one of the co-cappings of the integration. He deserves a lot of credit. Yeah, Howard has had an amazing career. I met him like literally decades ago and he has always taken on the really hard jobs.  He took on the services business at EMC. You remember, Stu, when Joe Choo Choo said, we're a product company, not a services company. I was like, give me services. I'll take that. It's been on theCUBE 10 years, Dave. He was drawn away. He was on fire this week. I thought Pat Gelsinger was phenomenal. Yeah, he's an amazing guest. Tom Sweet, you know, very strong, Marius. That's a great cube moment. It was great. What's your favorite cube moment? I'll never forget, Joe Tucci had my little camera out. Bill and Joe Tucci had it in one of the sessions. Give us some commentary in the hallway. Well, that was at 2010, one of, 2011, I think one of my favorite 2010 moments, I'll go back to the first time we did theCUBE was when you asked Joe Tucci, you know, why is storage sexy? If you remember that. Yeah, I did, I did. He never came on again. But that was a meme, that was a cube meme. All for the next couple of years. Yeah, right, to remember Tom George's, we have to go, I'm not touching that. So I remember when we were critical of hybrid clouds like 2012 or 2013, I go, Pat, is a hybrid cloud a halfway house to the final destination of public cloud? He goes to me, he goes, halfway house. The interview was just like, the whole crowd was like, what just happened? Stu, favorite moment. Oh, gosh, I mean, so many here. John, as you said, it's just such a community.    So Dave, thanks for popping me out. It's been a fun ride. And yeah, I mean, it's amazing to be able to talk to this whole community. My favorite moment was, Stu, when we were at AWS, our first show, we're like, are we still live? Hell, this is James Hamilton, Andy Jazzy, come on up. Very small show, now it's a monster. Dave, the cube has had some good luck. Well, we've been on the right waves and a lot of companies have sold their companies, been part of the queue. Companies went public, unicorns, Nutanix came on early on. No one understood that company. What I'm thrilled about too, John, is we're now a decade in, we're documenting a lot of the big waves. One of the most memorable moments for me was when you called me up and said, hey, we're doing Hadoop World in New York. I got on a plane and went out. I landed at like 2.30 in the morning. You met me. We did Hadoop World. Nobody knew what Hadoop was back then. It became like the hottest thing going. Now nobody talks about Hadoop. So we're seeing these waves and the cube is able to document them. It's really a pleasure. The cube canon, we got the cube studio, soon to have cube stories with cube network. Stu, cube all the time. Absolutely. Guys, thanks, it's been a pleasure doing business with you here, Dell Technologies. Shout out to Leonard, Chuck and the team. Sonya, Gabe, everyone else. Guys, great job, excellent set. Good show. Closing down, Dell Technologies rose to cubes coverage. Thanks for watching.