Alright, let's check this out here. Cool. Yeah, that's already in really good shape. I'm seeing basically vanilla exercise in your email. I think you are already really far along. What I will probably tweak is more polishy stuff. So I'm not sure if that's okay for you, but that's, you know, how far we want to go into the shop. But when I look at this with picky eyes, I feel like this section right through this drop into this is a bit too fast. Compared to everything else, there's a slight and I'm really talking one or two frames at it right there. If you look at the spacing of this, how small that is here and then suddenly we have that acceleration that will give this bit of a softer, softer set. If you're going for a vanilla, but also in terms of how the timing is here, the bounciness, and just how he moves from here to here. It's extremely picky just because it's already so far along. If I will be picky or it's a bit in terms of the shape language of the silhouette, this is fairly close to the body giving a little bit of a break up here. But when you continue, we're really kind of losing information of what is going on here. I like what you have in terms of the contact and everything, but up until, you know, when we get to here with negative space, it's a bit cleaner. But then we're getting into really broken feeling wrist and also again with a lot of information with the fingers here. Like all that just feels a bit busy and then watch out. You got a little bit of a wobble in that elbow going in and out. So what you could do is you can exaggerate just that relaxed pose. I'm strictly just got massive hands. You can also scale them down, but it could also be something where we see the structure. I mean, not that he has to have all hands out like that. Could even just be a little bit of here so that we see a little bit of forearm and then that hand can just relax down to here, even though that might not be a huge amount of negative space there. And then the hand has somewhere to go. And even then I will probably bring that shoulder back a bit more again. So we have maybe separation in the hands, maybe more on the side there. And there you might, I think it's probably too much to bring out that elbow already. So it's also some twinning, but that would be my picky thought on that just because it just feels like we're, we're so compressed in all of, especially here. But at the same time, maybe that's, you know, your feeling of someone being uncomfortable. Because you say vanilla, that's like, that's, that's to me almost a little bit of a shy, you know, uncomfortable pose. And then once you're into here, watch out, there's a lot of movement through there that I would continue to have in the wrist. It feels a bit IK where there's movement through there, but then this is locked and there's not much going on in that wrist section there. And I will probably just take out that forearm again, in terms of silhouettes, just because we suddenly have this coming that almost aligns with that part of the knuckles for a little bit of a tangent. And if you just take that out, it would be cleaner, even like a little tangent through there. So either you break that silhouette with an arm like this, or you bring it closer, kind of, or right in the middle, but it just rides that edge there. Again, off the picky notes, this lift here feels a bit soft, I'll probably give this a bit of a sharper, maybe to take two frames out of that, which feels a bit spliny, spliny soft. And then the chair, there's a couple of things, A, besides intersections here, you're hitting this, the chair just kind of scales down, which I would do a compression where it might pivot off of here and get off the ground more. I'm exaggerating, but you wouldn't pivot this much. But this is a weird scale where we have a squashy chair. I'm not super sure about that one. I would treat this fairly static with pivoting maybe off of one side and rotating and lifting one of the legs, but I wouldn't do a stretch. Now, I don't mind this, but if you have such, by this movement in the chair, but if you have such, you know, spacing difference here, like it really hits that chair, goes back, fine. But then the next frame is locked. That will need at least one more and a little tiny ease in, given that force. This feels a bit harsh for that chair to just stop on that frame. I do like that you recover, but I would just add a little bit in there. So it's not so, this feels more like there is a wall sitting against the wall. And it's kind of a, let's wait for it. Bit of a bounce like that versus there's nothing in here but a softer give. Again, mainly because how soft the chair is afterwards, it feels like it kind of breaks the rule at the very beginning. Now, if you do soften it, it might change the amount of impacts you have on that head there. Maybe this one, how sharp it goes back, maybe. But again, these are picky, picky notes. I think what's going to help you potentially with a chair moving back a little bit and maybe through that softness of the chair, that softness but kind of reaction to it or something giving a bit of a softer impact on that root as well. Because again, you're going pretty far on that sit and then it's that last one. And then it's totally locked.  Kind of chair goes down more than the root goes down, but it feels like we could have like one more frame of squishy forming into that, which will then also soften the spacing of the knees. They just also hit a bit hard. You could cheat that potential by bringing that knee out to his left. So then it looks like it would travel a bit more this way. Same thing with the right one. You're gonna have to follow that with the hands as well. But that could be that could be something. Now, if you're moving the hands back, it could have also a little bit of sideways movement, which could result in some spacing change in the knee. That's extremely picky. But just the thought there. Yeah, that's kind of that at the beginning. The only thing I would say, I love seeing the neck. And then once we do this, we kind of start to lose the neck part, which I understand, but it could be something where either it could be too much of a cheat. But as you turn either bringing down that shoulder and lifting the head a tiny bit, I would love to see a little bit of neck. There, it doesn't feel like a block on a line here. It's a bit tricky. Yeah, I don't know. Out of that will work. This is always nice. It's nice seeing the structure understanding how that fits on this. I think that's okay. I'm kind of looking at the chest rotation there. But I think it's okay. Moving over. I think it's what I'm reacting to is I understand he looks so the chest follows and also the arm goes back a bit. But then I'm also seeing this arm kind of going back. I almost feel like maybe that shoulder wouldn't follow as much. Like I feel like there's a turn, there's a turn, but then the arm was the other way kind of contradicting that like that shoulder would be to me lower more to the right because that arm is going back. This I would buy if that, if we could see that arm out, if that makes sense. Because I feel like that forward transit is the same as this or whatever rotate, whatever the however that rate functions. Again, all super picky. I do love that you have a slight squeeze in the hands here and in relaxation there. Again, I'm just being super picky because this is your first pass. Your first pass is already so much more, you know, so further along than so many other passes I've seen when I hand out a, to my students at least, a sit down assignment. Like this is already so much further along. So yeah, I'm gonna leave it at that, picky, picky stuff. Let me know what you think. I don't know if you have any eye controls to make that one eye slightly bigger than the other. I don't know if there's any control in the cube to give this a slight rotation, a line of action in the head, stuff like that. Or even here, but maybe bring out that ear more and this ear less, just kind of playing around with the silhouette of it. Like everything points, you know, this way to look, but then this ear goes, hey, look at me this way. Again, super picky, kind of taking away from that default mirrored cube. While there are so many different considerations in terms of lines, this feels like it needs more controllers. I don't know. I don't know that rig. And that's kind of that. Again, it's all super cool. Picky comments. Let me know if that's okay, if that's what you were hoping or imagining the comments to be, if that was English. And that's it. Thanks.


Hi everyone, Basel Chapman here. This is the Tiger Financial News Network, 3 p.m. market update. Dow is down 57 at 33,116. Try to run up. As charged on the left is the daily chart in the middle of the weekly. On the right is the monthly. It tried to run up. It stopped dead at that 14-period exponential. Moving average at 33,515 was the high. And now it's pulling back. It's pretty much at the low of the day. That was a rally attempt that just had absolutely no strength. The S&P was early on, was very strong. Now it's very weak. It's down 27 at 4232. I mean early on, I mean pre-market when there was that Putin nonsense that gave the market a big flow to the upside. You're looking at QQQ123. There we go. The NDX100. This is the Investco Trust series. And we're looking at 327 and down 4. It couldn't even break above the 9-period moving average. That's how weak it's been. IWM, the Russell 2000. That's the small caps. Down 228 at 197.66. It was an opportunity today to have a rally, hold a rally, and then maybe take some selling off of the clothes because we've got a weekend coming up. You never know what's going to happen in the geopolitical arena, but it didn't even rally much at all. And now everything's weak. You're looking at the gold contract. And this is going to be important because the gold contract being a Friday, sometimes the gold can get smashed on a Friday. When it was down sharp, it was down at 1960. Now it's trading in 1989. Very good strength. Came back quite nicely. You're looking at the dollar. This is going to be very interesting because the dollar is very strong. It's up 58 ticks at 99. This is ready. This is kind of an America. This is the currency of importance right now. The dollar just continues to be. You're looking at the TLT. This is so disappointing. The TLT tried to rally. It's up 36 cents at 134.82. It just can't get any momentum to the upside. I'll talk about this next when I do the Tom O'Brien show, Tom's Away. I'll be doing this show coming up and looking forward to there's a lot to discuss. Crude oil. Crude oil is holding quite nicely. It's up at 109. Up three. But it has pulled back very sharply from the 130.50 high that was made just five days ago. I think there's going to be a really important weekend coming up going into Monday. We'll talk about it as soon as I return. Puzzle Chapman signing off for the update. But we'll be back with the Tom O'Brien show as the guest host. Hope to see you in a few minutes. Important markets to look at.


Hi, my name is Foster Anderson. I'm executive director of shared adventures. And on July 18, we're going to be having our 23rd annual day on the beach, which is happening at Cowles Beach down in Santa Cruz next to Worf. And on that day, we're going to be offering people with special needs the ability to go out kayaking, out rigger canoeing, scuba diving, beach wheelchair rides. And new this year is climbing while it's 30 feet tall to challenge people with. So if you'd like to get involved by volunteering, you can go to sharedadventures.org and push the Day on the Beach button. And there's information all about it. And there's all the activities you can volunteer in. And without further ado, it'll be a great way for you to get involved with the community and be the person that you want to be. So come on out and have a great time.


The PI3K-AKT-MTOR signaling pathway is a complex network of proteins involved in various cellular processes, including cell growth, differentiation, and survival.  Several drugs targeting this pathway have shown promise in preclinical studies, and some have been tested in clinical trials for treating hematologic malignancies and solid tumours. This article was authored by Fei Xu, Lixin Na, Yin Fei Li, and others.


This lecture is part of an online course on Lie groups and will be about Engel's theorem. So Engel's theorem will help to explain the following mystery. Why is a nilpotent group called nilpotent?  On the other hand the word nilpotent, well nilpotent means zero and potent means power. So something should be nilpotent if some power of it is equal to zero. And at first sight this concept of nilpotent seems to be very little to do with the definition of nilpotent for a group. And the explanation of it goes via Lie algebra. So we say Lie algebra L0 is nilpotent. If when you keep killing off the centre of L0 to get L1 then you kill off the centre of L1 to get L2 and so on. A Lie algebra is called nilpotent if that eventually ends up as the zero Lie algebra. Well again the definition of nilpotent for groups is obviously defined by analogy with the definition of nilpotent for Lie algebras. Well at first sight the definition of nilpotent for Lie algebras doesn't seem to have much to do with nilpotents either. So this difference is explained by Engel's theorem. So Engel's theorem says the following. We have a Lie algebra contained in the Lie algebra of n by n matrices. And so L is going to be a Lie algebra. Then if all elements of L are nilpotent L fixes some non-zero vector v of r to the n. This is assuming n is greater than zero of course. Well at first I'd better say what we mean by fixing a vector. So if g is a group then we say that a group element would fix a vector if g of v is equal to v. This is not the definition we use for Lie algebras. For Lie algebras the definition of fixing a vector says that L of v is equal to zero where L is in the Lie algebra. The reason for this is that we think of an element of a Lie algebra as being a sort of difference between an element of a group and the identity. So we might think of g as being approximately the identity element plus an element of a Lie algebra. So this is why the definition of a Lie algebra element fixing a vector is given like that. Well this still doesn't seem to have much to do with nilpotent matrices. But now we observe that we can repeat this with r to the n modulo v. Let's call this v zero or let's call it v1. And we can find a vector v2 in r to the n over v1 which is fixed by the Lie algebra L. And we can continue like this. We get v1, v2 and so on up to vn. And if we use these vectors as a basis for r to the n then all elements of L are strictly opera triangular. So L is now contained in the subspace of these matrices. And the set of these strictly opera triangular matrices is formerly algebra. And on the one hand the elements are obviously nilpotent. And on the other hand they satisfy the definition of being nilpotent Lie algebra that I mentioned earlier. For example if we take four dimensional space and look at this Lie algebra. We can see the center of it is more or less these matrices here. And if we're quotient out by those then the center of the resulting algebra is given by matrices where these are allowed to be none zero. And if we're quotient out by the center of that then we're quotient out everything and we get zero. So Engel's theorem shows that the condition for being a nilpotent Lie algebra is closely related to the condition that all matrices of the Lie algebra are nilpotent. I should have a sort of warning that a Lie algebra L inside the n by n matrices can be nilpotent as a Lie algebra but not nilpotent as matrices. For example we just take gl1 of r and we just take the matrix one in gl1 of r. Well this is obviously a nilpotent Lie algebra because it's abelian. On the other hand this is obviously not a nilpotent matrix. So the connection between nilpotent Lie algebra and nilpotent matrices isn't quite as clean as you would really like. So let's sketch the idea of the proof. This is a proof of Engel's theorem. The main idea is we repeatedly use induction on the dimension of the Lie algebra and the dimension of the vector space r to the n that is acting on. So we can sort of assume if we've got any smaller Lie algebra or any smaller space then we can apply Engel's theorem to that. So the proof really involves three steps. So step one is that L acts on itself by nilpotent operators. Well what do we mean by L acting on itself? Well any Lie algebra L acts on itself because if you've got an element L of the Lie algebra it acts as the map from L to L taking M to the bracket of L and M. So we can think of L as mapping to the Lie algebra of linear map from L to itself. This isn't necessarily injected because L might have a centre, in other words something that commutes with everything. And what we want to do is to show the action of L on L these things are all nilpotent. So we want to know are these nilpotent? Well we think of this as taking M to L of M minus M of L where we now think of these as matrices. And we notice that M goes to L times M is nilpotent because we assumed all the elements of L when nilpotent is matrices and similarly L goes to M times L is also nilpotent. And we notice that these two commute as linear transformations because right multiplication commutes with left multiplication. And now if we've got two commuting nilpotent objects so if x and y two commuting nilpotent things then x plus y is nilpotent. And the reason for this is that if we write if x to the n is equal to zero and y to the n is equal to zero then we notice that x plus y to the two n equals zero because if you expand this by the binomial theorem every term involves either x to the n or y to the n. So the adjoint action of L on itself which is this also acts by nilpotent matrices. So the second step of the proof is that L contains an ideal of co-dimension one. So we just recall what an ideal is. An ideal of a Lie algebra is something just such the bracket of anything in L and M is contained in M. So this is the analog for Lie algebras of a normal subgroup of groups. You can easily check that if we've got an ideal of a Lie algebra then we can take a quotient and that still has a Lie algebra structure. And this is easy, we just pick M to be a maximal sub-algebra that's not equal to L assuming L has dimension greater than zero. And now we're going to look at M acting on the space L modulo M. So here we've got a Lie algebra acting on a vector space which is just the vector space quotient of L by M. And now we're going to apply induction and by the induction hypothesis since M has lower dimension than L and we've just seen it acts by nilpotent matrices on this we see that there's a vector V in L over M with V not equal to zero and V is fixed by M. Well this means that if we take R, V and add it to M this is also a sub-algebra. So by maximality of M it's equal to L. So M has co-dimension one in L and you can also see that V M is contained in M because M acts trivially on V modulo M so M is an ideal. So this is step two we've shown that L always contains an ideal of co-dimension one assuming L is non-zero. And now the third step is very easy. So step three we've got L contains an M. M is an ideal of co-dimension equal to one. And now these both act on our vector space V and let's put V zero equals vectors fixed by M. And by induction V zero is not just zero because M has to fix some vectors on V because M has smaller dimension than L. And now L is generated by X and M so now let X act on V zero. Well this acts null-potently. This is where we finally use the condition that the matrices of L all act null-potently. So fixes a non-zero vector of V zero because any null-potent endomorphism of a non-zero vector space must have a vector that it kills or fixes if we're talking about the algebras. And this proves the theorem so V naught is fixed by the Lie algebra L which is what we wanted to prove. So that proves Engel's theorem. There's a sort of analog of this theorem due to Coulson for groups. It says that if G is an algebraic group contained in the general linear group over a field, an algebraic group just means it's a group that can be defined by polynomial equations. Then it says if G is unipotent then G is conjugate to a subgroup of the group with ones down the diagonal and zeroes here and something there. So what does unipotent mean? Well unipotent means all eigenvalues are equal to one. So null-potent means all eigenvalues are equal to zero. So this is the sort of group theoretic analog of a matrix being null-potent. If a matrix is null-potent then one plus that matrix is unipotent. And this is obviously very similar to the condition that the Lie algebra should be conjugate to something that is strictly oppertriangular. In some of the lectures I've made several rather disparaging remarks about null-potent Lie algebras and null-potent groups and said how horrible they were. And I would like to point out that although they're kind of evil, they're not completely evil and there is actually one nice property of null-potent Lie algebras that doesn't hold for general Lie algebras. So suppose we have a Lie algebra L contained in a group of strictly oppertriangular matrices. So in particular L is null-potent as a Lie algebra. Then the exponential map is an isomorphism from an L to the corresponding Lie group. Well what is the corresponding Lie group? Well if we like we can even define it to be the set of exponentials of matrices of L. I should say here we're working over the reals or more generally a field of characteristic zero because otherwise you can't define the exponential map. And this is very easy to see because in fact the series for X is finite. In fact you can see for any matrix in L, A to the N is equal to zero for some fixed N.   So the series for log of X and exponential of X now converge everywhere as long as you're just working with oppertriangular matrices. So in particular you can see that the set of matrices of the form X with A for A in the Lie algebra is the simply connected Lie group. And it's simply connected because it's isomorphic as a topological space to L which is just a vector space which is obviously simply connected. So the correspondence between simply connected Lie groups and Lie algebras is particularly easy because the exponential and logarithm map always converge. Now let's have an example of a nilpotent Lie group that is not simply connected and is not a matrix group. Meaning we can't identify it as finite matrices over the reals although we can identify it as an infinite matrix group. And for this we just take G to be the group of all these matrices. So this is a nilpotent Lie group of dimension 3 and we're quotient out by the set of matrices of the form of this form where N is in Z. So this is in the center of the group G so we're just quotient out by a subgroup in the center isomorphic to Z. So this is the famous Heisenberg group which appears a lot in quantum mechanics because it controls the position and momentum operators of a boson. And let's look at the Lie algebra. Well the Lie algebra is spanned by three elements. So we take X to be 0 1 0 0 0 0 0 0 0 and Y to be this matrix with a 1 there and Z to be the last one which is 0 0 1 0 0 0 0 0 0. And now we can work out the brackets between X, Y and Z and we find that the bracket of X and Y is Z or possibly minus Z I sometimes get this wrong. So Z bracketed with X and Z bracketed with Y is just 0 so Z is the center or spans the center of this Lie algebra. And now we want to show that we can't represent G in terms of finite matrices. Well we look at the image of Z. Here we're taking a map from G to the general linear group over N of the reals and the Lie algebra will map to something in the N by N matrices over the reals. And we want to look at the image of Z in N by N matrices over the reals. And now we notice that X of I Z sorry X of Z must be equal to 1 sorry we should be working over the complex numbers not the reals that I can diagonalize everything. We know that X of Z is equal to 1 and this implies that Z is diagonalizable. Because if a matrix isn't diagonalizable and you put into Jordan form you see that the X of it can't be 1 and we just get a one parameter subgroup isomorphic to the reals. So we know Z is diagonalizable and the other hand Z is in the center of the group or Lie algebra G. So we can pick some eigen space V of Z in C to the N and we notice that V is acted on by G because Z is in the center of the Lie algebra. So all eigen spaces are also preserved by G. So the Z looks like well it has to be diagonal and it's got only one eigen value on V so it must look like this in V for some A in C. And now we use the Lie brackets we know that X Y is equal to Z so trace of X Y is equal to the trace of Z. Well this is just the trace of X Y minus the trace of Y X which is equal to 0 because you know for matrices the trace of a product of two matrices doesn't depend on the order of the product. So the trace of Z must be 0 but the trace of Z is just equal to the dimension of V times A so A equals 0 as the characteristic is equal to 0. So Z acts trivially on any eigen space so the action of Z is trivial on V so the map from G to GLN over C is trivial on X of Z which is the set of group elements of this form. So there's no faithful finite dimensional representation of this group G. I'll just finish by mentioning the fact that here I sort of emphasized we were in characteristic 0. So in characteristic 0 if you've got matrices X Y such that X Y minus Y X is equal to the identity matrix. This implies if we're in characteristic 0 the matrices must be 0 dimensional so this is really not possible in characteristic equal to 0. I'll just point out that the condition of the characteristic 0 is actually essential because in characteristic P greater than 0 we can take X to be D by DX and Y to be multiplication by X on the space V which is spanned by 1 X X squared up to X to the P up to X to the P minus 1. We notice that D by DX the power of P is equal to 0 so this is why we can do this in characteristic P but not characteristic 0. Okay that would be all for the about nilpotent Lie algebras for the moment.


Coming up on DTNS, what Microsoft has planned for Bethesda Lines plan to fact check without weakening encryption and monitoring your heart with a smart speaker. This is the Daily Tech News for Tuesday, March 9th, 2021 in Los Angeles. I'm Tom Merritt. And from Studio Redwood. I'm Sarah Lane. And from the place where there's a soon to be father to I'm Patrick Beja. I'm the soon to be father of two. And I'm already a father of two. I'm the show's producer, Roger Shane. That place is Finland, Finland soon to be the place where there is finally a father of two. Patrick Beja, congratulations on the number two government man. Well, they're not here yet, but soon. We were just talking about names for Sonos products based on former Roman Empire capitals and a lot of other fun stuff. Get that wider conversation by becoming a member at patreon.com slash DTNS. Let's start with a few tech things you should know. Samsung announced to follow up to its 970 EVO solid state drive called the 980. The drive is an MVME M2 PCIe 3.0 drive and cost between $50 for the 250 bite 250 gigabyte model to $130 for the one terabyte version. This is Samsung's first DRAM less MVME SSD. It takes advantage of the host memory buffer feature in the NVME specification instead, which also brings the price down. Samsung says the 980 can achieve speeds of up to six times that of a SATA based SSD. CBS News reports the Twitter is suing Texas Attorney General Ken Paxton in federal court following an investigation the Attorney General launched into Twitter after it banned former President Trump. Twitter alleges the Attorney General is violating the first amendment by trying to punish the social network for exercising free speech rights over the content it hosts. Chrome OS is 10 years old and in celebration Google announced new tools coming to the platform. A feature called Phone Hub will let you find an Android phone from a Chrome OS device tether with one click and check your phone's battery life. Wi-Fi sync lets you automatically connect to Wi-Fi networks that your Android phone trusts. Nearby share lets you easily share files between Chrome OS and Android devices without needing an internet connection. Chrome OS screen reader is getting improved controls and the clipboard can now store up to five things. Apple released iOS 14.1, an important security update to address a WebKit vulnerability. That update aims to prevent arbitrary code execution in Safari and third-party browsers, so go do that right away. Apple also released a preliminary update from its women's health study team at Harvard TH Chan School of Public Health. The study of 10,000 participants in the research app found that menstrual cycle symptoms included some that are less commonly known or discussed, such as gastric issues and sleep changes. This kind of data can help researchers better understand various health conditions such as polycystic ovary syndrome, infertility, and menopause. Amazon is expanding its Amazon One technology which lets customers pay inside a store by scanning their poms to identify themselves, expanding to more stores in the greater Seattle area. It's now available in Amazon's four star store in Linwood and in the coming weeks in Amazon Books Store in Bellevue and its four star and pop-up stores in Southlake Union. Amazon says 12 of its physical stores will soon feature the technology. I will give you a dollar if you take a picture of yourself with a palm pilot trying to use it to log in at one of those stores. All right, let's talk a little more about what's going on with the European Union. Okay, the European Union has pledged more than $150 billion to develop next generation tech industries as part of its two trillion economic recovery package. The plan sets a goal for Europe to produce at least 20% of the world semiconductors by value to 20 by value by 2030. So got a little under 10 years to double it. Last year Europe produced 10%. The biggest European chip companies are Infineon and NXP, which make chips for automotive and industrial customers. ASML and the Netherlands makes equipment used for chip making plants. Taiwan and the U.S. are leaders in the space with companies like TSMC and Intel. Europe has had success encouraging domestic industry before with Airbus and GSM technology, but domestic tech self-reliance is becoming a trend. Last month, the U.S. launched a review of supply chain disruptions with references to encouraging domestic production. China built chip making self-reliance into its latest five-year plan as well. Well, Patrick, I mean, you're in Europe. What do you think about self-reliance? I, well, I think it's not only interesting but kind of mandatory now as we've learned. And to be honest, I didn't realize that Europe was producing 10% of the world's semiconductors. Obviously, we're talking about value here, so it might not be huge volume, but it's still not insignificant. You know, we have this image that in order to start this kind of, to or restart this kind of industry, we need know-how that we don't have in the West. And if you're producing 10% of the world's value or value of semiconductors, you at least have some of the knowledge, some of the know-how. So I think that going from 10 to 20 over a period of 10 years, if there's a consensus over the entire union, it doesn't seem impossible. And it would help a lot, not only in, of course, you know, independence and self-reliance, but also in having more of a say in the trade negotiations or economic discussions that you will have with your partners. It seems like, I don't want to say, you know, it's, it's, there's a, maybe there's a silver lining out of the pandemic in that area for us. Yeah, I think a lot of people don't realize, if you're building a chip factory, it doesn't matter if it's in India, Brazil, South Africa, Vietnam, you are likely to be buying from ASML in the Netherlands. They are, they are considered the leader in the equipment needed to make chips. So there's some secret hits in Europe. My gut is a little concerned at this idea of everybody wanting to be self-reliant. I'm not that worried because I don't think it's achievable, but I think it would be bad if every country tried to be like, we're going to make all our own chips ourselves, which is not what Europe's trying to do. They're only trying to go from 10 to 20 percent. So, you know, I'm not, I'm not going to panic, but we, I think hopefully what the good outcome of all of this is we have a wider distribution of manufacturing capacity so that if one country gets targeted or one country goes down, whether it's because of governmental problems or, or weather or a pandemic, it doesn't affect the global supply chain as much as when it's all concentrated in one region. So I think the, the way we look at it in Europe is not so much, let's make sure, you know, things can keep running for the world. And more, let's say we have a rush on some components, well, we need to make sure that we have at least enough here to keep the essential infrastructure and things that we need running, running. So maybe you're not going to have all the latest technology or maybe you're not going to have enough to, you know, you're not going to start making iPhones if you have a global drought or not drought, but, you know, a global shortage on those kinds of components. It's not to make sure that you can make enough iPhones for everyone in Europe, it's more, let's make sure we can keep building, I don't know, submarines and. Or cars, I mean. Or car, yeah, yeah. Important stuff. Automotive chips are having a shortage and that's one of the areas that Europe has good capacity and so that they're feeling it more, I think that makes sense. I mean, we were talking about Airbus, the, the aviation industry is also in that. Yeah, yeah, yeah. Issues, so. All right, let's talk about nothing. Well, won't we? Yes, we will. Carl Pay, co-founder of OnePlus and now head of his own new company called Nothing, which will never get old, unless it does, tweeted a picture of concept one, the precursor to its first product, wireless earbuds expected to come out this summer. The earbuds are semi-transparent and shaped a bit like a tobacco pipe. Pay also made a blog post about the company's design principles, writing no screens, no dedicated devices, just barely noticeable technology that empowers us to be more human. Well, first of all, I think that the design is kind of neat. I mean, it looked like earbuds. There is some transparency. The tobacco pipe part of it and, and Pay specifically said it's like a grandmother's tobacco pipe and the blog post announcing the design, which I'm like, okay, sure, there's grandmother's smoking tobacco pipes here and there, but it's not the first thing I might think of when I'm putting something in my ear, but it's kind of cool. I guess promising no dedicated devices, no screens and wireless earbuds and future products that just work.  They said they were going to do this and now they're doing it. I don't know. I just want to make a McGree joke at this point because it really does not look like, it looks more like a snail shell to me than a pipe, but the important thing to note here is that Carl Pay is a master at getting the technology world to talk about his new company and he doesn't even have a product yet. You know, this flowery design language has a lot of people out there very excited, like, oh, I love their approach and everything. All we've seen is this concept that's not even the actual product yet. I'm not saying the products will be bad. It's a master at work. Yeah, it's really annoying to me because he's so good and everyone is kind of foiling for it. You know, there's really, even the name is clever and annoying because there's really nothing to talk about and everyone's talking about nothing. It's so annoying that it works and the product is, I mean, there's no product. There's, again, nothing. The design, honestly, is not that interesting. It's a lot of, oh, what could it be? What could it end? OPPO is a great brand. Is it OPPO? Am I hallucinating? OnePlus, sorry. OnePlus is a great brand, but what they did was make stuff that was really cool and expensive, really cool and less expensive. Maybe Carl Pei is a design genius and he's going to make interesting new stuff and that's the way he's presenting his 2B products, but he doesn't have the pedigree to innovate item thing beyond making stuff really, really cool at a cheaper price. Yeah, he's teaming with teenage engineering to partner on the design. That's a hardware company design company. Not just a bunch of teenagers, that's actually the name of the other company. Man, these names these days. The thing with wireless earbuds, before we move on, just sure you want it to sound as great quality as possible and fit and be comfortable to wear. I mean, I don't know how much you innovate unless I'm really missing something with the future of these things we're all wearing now. Also, it's a dedicated device. So get off my lawn. He says no screens. So he's not making phones. No, that's for sure. That's true. But the earbuds are a dedicated device. What does it mean? No dedicated device. So anyway, rest of world.org, which if you don't follow rest of world.org, go check it out. They do some great work there. Has a write up. Yes, please do. Yeah. Yeah, it's really good. Rest of world.org has a write up on how line partnered with Taiwan Fact Check Center and co-facts to combat misinformation on the line messaging app and then encrypted. So how are you going to combat misinformation when you can't see people's messages? Well, users can forward suspected misinformation to a line fact checker account. The system scans the message, compares it to a database of previously identified misinformation and then responds with an X if it's totally false, an orange triangle if it's partly false, partly true, and a green check mark if it's entirely true, and then links to a report that explains that rating in more detail. If there's no match, the system will try to offer similar topics and may ask the user if they would like the message to be fact checked from the ground up because it doesn't have anything on it, which can take from three to seven days. Lines research shows that about 33% of users in Taiwan are willing to report suspicious content. 25% would forward a fact check to their own contacts once they got it. Line also shows frequently reported fact checking on its homepage and the system lets line track false information being shared on the platform because they otherwise wouldn't see these messages while still using end-to-end encryption. Now, I can't do video or memes yet, but Line says it hopes to launch that part of the feature later this year. Princeton cryptography researcher Anune Kulsretha told Rest of World that the approach is novel but could be easily implemented by others like Signal or WhatsApp. However, Taiwan has a robust system of fact checking already. Line's not paying. Facebook pays its fact checkers. Line's just taking advantage of existing resources. And Taiwan has a culture of combating misinformation that not all countries share. It feels like this is easily replicable technologically speaking, but kind of depends on the region as far as whether it would work or not. Yeah, I think that's exactly the issue. The thing works very cleverly for implementing fact checking and checking period in an end to end cryptographic messaging system. And that I think is the most interesting and novel takeaway from all of this. And it's a very clever way of doing it. And by the way, yes, Rest of World is great because they surface these kinds of things that we have really never heard about. And that article is a great example of that. But beyond that, I think the culture in Taiwan is probably a big part of it because it could be implemented, as you said, technically. I'm not sure how well it would work in situations like the ones we see on Facebook and Twitter and others. What's really interesting to me, though, is that this is a step that users have to take themselves. You have to see a story, think, oh wait, there's something fishy about this and ask if there is indeed something fishy about it. The approach we've had until now in social networks is presenting the validity of the story along with the story itself without people even asking. So I wonder if there isn't a kind of an added benefit of having the end to end encryption having to force the user him or herself having to ask for the check. Yeah, I think for the most part it's hard to get upset about giving users of any messaging app more tools in order to figure out what's true and what isn't. The main problem I see with this is just, yeah, the length that it takes to get your answer. I mean, we're talking about information being shared at warp speed, waiting up to a week to find out if that thing I read is bunk or true. Although that's only if they've never fact checked it before. Most stuff you get immediately. Well, sure. But yeah, but if something is going to take a while, you've probably moved on or decided what you've decided already. Yeah. I think the 33% seems low to have much of an effect as well. But I don't know. I think 33% is, of course, not huge. But there is also a lot of people who wouldn't change their mind anyway. So the 33% is seems like the number of people that you can't actually affect. So the people that matter. That's a good point. It's self selecting, right? The people who wouldn't change their mind anyway aren't going to bother to forward this. So yeah. All right. I'll buy that. Hey, folks. You can fact check each other by submitting some stories to our subreddit. What do you want us to talk about on the show? Let us know. Submit stories and vote on them at dailytechnewshow.reddit.com. Oh, yes. That's me. I want to tell you about Zenimax and Microsoft, because on Monday, the European Union approved Microsoft's acquisition of Zenimax, the parent company of Bethesda, which now officially has joined Microsoft. Microsoft announced Tuesday that some new titles in the future will be exclusive to Xbox and PC players, meaning they won't be on PlayStation or Nintendo. Microsoft has previously indicated it would continue to publish Bethesda's games for Nintendo and Sony platforms as well, and said that PS5 exclusives like Ghostwire Tokyo will release only for Sony as planned. Those were deals that were struck before the purchase. If that sounds possibly contradictory, Venture Beats sources say Microsoft will release a video presentation on Thursday, March 11 to explain what the acquisition means, particularly for Game Pass subscribers. So it seems like Thursday we're going to hear everything's going to Game Pass unless it's exclusive to Sony. Immediately. But this idea of Microsoft making some titles exclusive to Xbox and PC has put some people in a sour mood, let's say. Well, this is a really difficult thing to wrap your head around, because Bethesda is a huge developer and publisher, or Zenimax, if you take the parent company, and they have a lot of very beloved IPs, and Microsoft buying them is of course incredibly important because as we've seen in this new age of media and entertainment, content and IPs is what matters. You need to have more than the the opponent, quote unquote. And so do they keep publishing things to all the platforms as it has been before, but they have the company, so they should keep it for themselves. But at the same time, they've been pushing Game Pass, which is a subscription service, which changes the game a little bit and the way you think about it. As they said, some of the games are going to be exclusive, but not all of them. And I don't think they talk just about the games that have already been in a deal to be on other platforms, because think of it this way, if Elder Scrolls 6, Skyrim 2, for those who don't know what Elder Scrolls is, the new Skyrim essentially comes to old platform and costs 70 bucks on Sony's PlayStation. You can turn around and go to the Xbox and get the Xbox Game Pass, which includes that game, and hundreds more for 10 bucks a month. So if you want to give Microsoft your money through Sony, you're welcome to, but you could also get that thing for much cheaper. I think it could make sense. I think that just has people wondering why would anything be exclusive to Xbox then? If Game Pass is the big advantage, why antagonize people by doing that? Well, because they still want to get people in their ecosystem, which is the whole point of exclusives. It really comes down to content. You know, we're entering an age in video games that is analogous to the age we've entered in TV, I don't even want to say TV, but video subscription service. The content, and often the exclusive content, makes all of it, makes everything. And they want to get you into that ecosystem because on the Xbox ecosystem, anytime you spend a buck, you give 30 cents of that buck to Microsoft. So it's a balance to strike. They want to get people into the fold and then milk them on everything they buy on the system. So they do need to get people interested in this platform more than another. The Game Pass does a big part of the job, I think, but it doesn't do the entirety of the job. Scientists at the University of Washington have developed a system that can use an Amazon Echo or Google Home to detect your heartbeat. The system can send inaudible sounds from a smart speaker, which bounce off things in the room, including a person. And if they're within a half meter of the speaker, you can detect the heartbeat. Two algorithms analyze the sound waves that bounce back and detect heartbeats almost as well as a medical grade ECG. The speaker system was at most 30 milliseconds off of that medical grade ECG. One of the algorithms uses beam forming microphones, same one that tell when you say the wake word to find the heartbeats among the other sounds and a second algorithm then measures the time between the beats. The algorithms were trained using self-supervised machine learning. Regular heartbeats are easier to detect, but this system can detect irregular heartbeats as well, which is harder to do and makes it more useful for monitoring people with heart conditions. Current system can be used for spot checks. You sit down and say, hey, check my heartbeat, but they hope to make it work for continuous monitoring as well. I think this is great for anybody who either doesn't want to wear a smart watch or isn't in the market for one right now and may have something where, sure, you have to be close enough for it to be accurate, but maybe there's something on your nightstand that can give you valuable information and it's already a relatively cheap device that a lot of people have. And maybe some company is going to want to design a dedicated device that will work five meters away or 10 meters away and that doesn't have you needed to be half a meter away and that could be incredible. You just have an ECG in your home all the time and you don't need to worry about wearing your watch, for example. Yeah, just being a yeah, if they can increase that range, then you can just have it on and it'll alert you by talking to you. It'd be like, hey, you should call your doctor. Yeah, it seems like not everyone would need one at home, but certainly people with heart conditions could get a benefit from it. And it could call your doctor for you, actually, now that I'm thinking about it. Oh. I could just ask you would you like me to put through that call? Yeah, true. Incredible. It's really interesting all of these areas of research and I wonder how that, well, it's a wider conversation, but do we just not need to worry about it and the machines and the algorithms will do it for us and tell us what's wrong with us and know everything? It's a standard question, but this is some of it. I want to know that up to a point. Yeah. I think it's mostly good and sense. It's important. Well, all you chess fans out there, this might be impressive to you. Developer Matt round created kilobytes gambit. Get it? Yes. At the site, vol.wtf, which fits a surprisingly competent chess game into 1024 bytes of JavaScript. What? How'd they do it? This is built on Oscar Toledo, G's 1K chess program, which now seems positively bloated at 1.25 kilobytes. The engine looks for moves ahead, then identifies if moves are legal, and then weighs the value of pieces within that code. And it's all wrapped in a Queens gambit themed user interface that would look right at home on an Apple too. I mean, the actual code that runs it is shorter than the launch text of the game, right? You're not counting the images in the launch text and everything. This is just the engine that's calling out all those assets and stuff. So when I first launched it, I was like, wait, the actual JavaScript code itself is shorter than the page that tells me how to play the game and gives me the options to start. This is pretty cool. Yeah. I'm not even good at chess. This program is better. It's incredibly impressive. If you're a coder and you haven't looked at this, go check it out, because it's really it's really a nice piece of work. Good job, Matt Round. All right, let's check out the mailbag. Let's do it. We got so many good responses from our story recently about voice assistance and being able to understand a lot of different types of speech that might not be as standard as what they have been used thus far. Daniel wrote in and said, I was inspired by hearing from the other listeners about their struggles with voice assistance not recognizing their voices and how improvements could help. I have a moderate intermittent stutter. Sometimes my Google Home understands me just fine. Other times I freeze up and then it won't wait long enough for me to finish speaking and this can lead to awkward results such as when I'm sending a text message. I can't wait for these improvements to come out and have my devices learned to be more patient with me. Love the show. Man, that one story has spawned so many great insights from people who are sort of saying like, hey, it's normal to have problems with these things because of this or that. And it's a different situation every time which shows that long tail that we were talking about in the story where you can adapt to an accent because accents are fairly uniform. It's much harder to adapt to all of the differences that happen for other reasons. So thank you, Daniel, and everybody else that has shared their stories with us. So good. Indeed. Feedback makes our show better. So if you have some, send it our way. Feedback at dailytechnewshow.com. Also shout out to patrons at our master and our grandmaster levels. Today they include Jeff Wilkes, Bjorn Andre, and Scott Hepburn. Also thanks to our brand new bosses, Mirovina and Robert van Schulenburg. They both just started backing us on Patreon. Thank you both of you. You're our bosses now. Also big thanks to Patrick Beja for being with us today. All the way from Finland. Patrick, what's been going on in your life? You know what? Same old disabled, making children, stuff like that. But also podcasting. I do a few French language shows for tech and gaming news. And also Super Laser Punch. If you like WandaVision and want a French language debrief of every episode, go check out Super Laser Punch. It's really fun. Excellent. Where do they go to find all those? Notpatrick.com. You also find my English language shows over there. Hey patrons. Did you know your ad-free RSS feed can have just DTNS or just Good Day Internet or both? Check your tier on Patreon to see if it says DTNS GDI or all in the name of the tier you're on. And if you want to change, change to the tier that has the name that you want. At DailyTechNewsShow.com slash Patreon. We are live Monday through Friday, 4.30 p.m. Eastern, 21.30 UTC. Find out more at DailyTechNewsShow.com slash live. And we'll be back here doing it all again tomorrow with Scott Johnson. Talk to you then.


Good day, fellow investors. I'm here with head investment manager of NicheMaster funds, Peter Barklin, and as would Warren Buffett say, don't worry about the stock market crashing, just buy great businesses. As a former consultant for more than 30 years advising the biggest businesses in the world, Peter Barklin and his partner, Perry Enster, have their money in their own fund, where they focus on buying great, amazing businesses. However, we hear that word, buy great businesses and then you don't care about what happens in the market, then your focus lies on that and you don't have to worry about anything. But the question is, of course, what the hell are great businesses? How do we find them? How do we select them? And how do we buy them and then have sleep well at night, let's say, with our investments? I'm so happy today that Peter has agreed to explain how he does it, how he finds great businesses and how he uses his 40 years of consulting background to find those great businesses. And I have seen stocks in his portfolio that went up five times over the last few years because those are great businesses and they just keep doing what they do, no matter what happens in the market, in the economy, no matter what happened in the last ten years, which is actually a great business. So please tell us about how the hell did you find those stocks that went up five times because they are great businesses? Well, so when you start by saying we are value investors, we consider ourselves to be value investors, but people define that differently and some would define that as simply buying the cheapest companies you can find and that's a statistical case for that. It's not our style though because, you know, when you get burned from the problem with very cheap companies is that a lot of them don't deserve to be any more expensive. As somebody once said, a bargain that remains a bargain is not a bargain. So what our style has become, I think I can say, is we like to buy companies of very high quality and they are more expensive than, you know, just the cheap companies, but we distinguish very clearly between price and value and so if we can buy a really valuable company periodically when opportunities occur for a price that is lower than that value, then we tend to pile into those companies and that allows us to not only make the profit from the investing, but also to sleep at night because we know that these companies are very, very sure that these companies will sustain anything the markets throw at them. How do you know what is the value and when the price is below that value? So first, I mean, first, I think maybe I should just first say, so what is, how do you find these great companies? And most of them are easy. If you want to have, it's very easy. They're very famous. Coca-Cola is a great company. Procter & Gamble is a great company. Unilever is a great company. But here's the problem. They are all well known and very large companies. So those companies are likely to be called what we, to be what we call fully priced. So the price already is at the level of the value. So what we try to do is to look for companies that are not famous yet, but are already great companies, but are much, much smaller. And the way we find them is little by little, we trawl to information. We read the press, we search databases and so on. And we have a list of criteria for what we define a great company to be. The first thing, which it may be obvious, but people tend to overlook it in my opinion, is there has to be a long track record. You know, we don't buy anything on hopes and dreams. We buy things. For example, management can show that they have increased dividends every year for 15 years in a row. So we look for that long track record, solidity of management. A company where management has been there for a long time and is likely to stay for a long time and some managers will make some crazy decisions and diversify or start some business that they have no business starting in our opinion. Great management won't do that because they understand where the value of the company comes from. And we will look at a number of financial things. For example, in another video we mentioned the concept of competitive advancements. So it follows that if a company really has a competitive advancements, then it must make a high level of return on capital. Otherwise it's just talk. But then the logic also reverses. So when you find a company that consistently, not for one or two years, but consistently makes a high return on capital, then that company must have strong competitive advancements. Now we just have to go and look for it and find what it is. So we simply start by looking for companies that are very profitable in terms of return on capital, return on equity and so on and so forth. And then we use that to draw back to see where does that profit come from. So a high return on capital, a huge effect and advantage of high returns on capital is that companies that have these high returns can grow and finance their own growth without having to invest too much money by definition because they use less capital. So that means they can grow and still pay dividends to us while they become bigger and more valuable. An example of such a company? We were talking about one yesterday. Decrypharmaceuticals have increased their dividends every six months for the last 15 years at least, maybe even longer. And they're not at the expense of their debt going up, but simply as a result of them creating, generating more cash flow every year, more and more cash flow. They spend some of that cash reinvesting into the business and some of that cash flow could be, in their case they haven't done it, but it could be used to buy back shares. And the rest is used to pay to investors as dividends. So this Decrypharmaceuticals that you spoke yesterday on the conference, so you say this is the 15-year track record of improving dividends and you have seen a chart maybe I can show that chart to investors.  And if I remember now from the conference you said that they did something in 2013. Can you explain how they focus on their business and what they're good in? Which other management wouldn't do? That was amazing. Okay, so back in 2012 this company had two major business divisions. One were veterinarian surgeries around the United Kingdom. Another one was patent protected medicines for pets and other animals. And those two businesses were hugely different in terms of their profitability and cash flow profiles and so on. The patent protected part which was half the business was vastly more profitable than the surgery business. Then one day they got approached by somebody who wanted to buy the vet surgeries. And of course the negative effect of that, the positive effect is suddenly you have a lot of money in your pocket. But the negative effect for many managers is that who would sell half the business we run? Because it's almost like telling people that we have given up. Not according to me but according to a lot of managers they would say that. But a truly great manager such as the people who run Degra said, you know what? What we do is we sell half the business. We use the proceeds from those sales, hundreds of millions of pounds to buy companies and to invest in further research and development to strengthen our patent protected part of the business. And then we see that growth come back and this time in a much more profitable company. And that's what they have done. And they are now back almost back to the level of sales in 2012. But with much higher returns, profit is maybe at least twice what it was in 2012. So that would be an example of great management. That's what I call great management.  We're still invested. In fact it's a company that has already been affected by Brexit. Not Brexit itself, fundamentally in the company, but the market theaters around it. So we have actually just a few weeks ago increased our investment in the company. How much did the company fall because of Brexit? Because of these theaters. Maybe about 30%. And that's the fascinating thing, the difference between bad companies and good companies, or high quality companies, as I call them the good ones, is that they also fluctuate on the market. So the market seems to have... And the fluctuations means that it provides opportunities for investors, of course, to get in when they're not expensive. So it's not only... That's the fascinating part. It's not only the low quality companies that see their prices fluctuate. It's also the high quality ones. The difference is the high quality ones always come back. The low quality ones sometimes go to zero. And that's what we don't want, because that's what would keep us up at night. That would be permanent capital loss and that doesn't fit Buffett's rule, don't lose money, and it's his second rule, don't lose money. So how would you summarize now what would be the three or five points that we have to focus on when looking at great business and when wanting to find great businesses to invest in? Okay, so starting with the financial measures, return on capital, abilities to generate cash flow, ability to consistently increase dividends, are three key things that are very quantifiable. So an easy to scan, you go into any stock screener and they can find stocks that have those characteristics. But then we dig deeper. We look at, as you spoke about, the quality of management. You have to find out what are their track record, are they brand new in this business, is this really what they stand for? And the consistency of having done this over a very long time, and that is so important. You don't see in any, even if you go to Bloomberg, you see maybe three or maybe five years of financial numbers, I want to see a lot longer and very consistent. So you have to do some footwork. You have to read some annual reports. And what else? Then this understanding about where the competitive advantage comes from that we have talked about before, because without that we don't really know what the threats to the companies are. Because all companies, I mean all high quality companies are envied by competitors or potential competitors. So there's always some, Steve Jobs used to say, his nightmare was that every morning thousands of engineers go to work around the world wondering how to outdo him. And so imagine that must have created some nightmares. So I want to know also what is it that our companies need to be able to protect. So then I can look and scan the horizon for threats to those. So we try to understand that as well as possible. Is it patent protection? Because patents have only a relatively short lifespan. Or is it something else? Is it the scale of the business? Is it the quality of the branding? So there's at least five, six things before you can truly use the term high quality company. But just start by, I would advise you, start by looking at some that are famously high quality but are already too expensive. Just ask yourself, what are the qualities of Coca-Cola? Asking about Coca-Cola. What do you mean when you say that it's too expensive? What are you looking? What parameters are you looking there? So, I mean, we always do the easy price earnings, price book and so on and so forth and see how much the inverse of the price earning is the earning field. So if you have a price earning of 25 as you probably do in Coca-Cola's case the inverse of that is 4% return to me but then of course Coca-Cola's earnings grow but 4%, if I buy them at the current price I only get 4% return and then I wait for it to grow and I think I can find some that are high quality but where I can get 8% or maybe even more than 10%. So that's one way of looking at it. When we get to make a real investment then we always do a cash flow, discounted cash flow valuation which is fraught with problems of course. As that other investor you mentioned before used to say this discounted cash flow value is a number that is impossible to calculate but essential to estimate and I think that makes a lot of sense because once you go through the calculation it's not complicated to go through but you realize that you change your assumptions just a little bit and the number becomes completely different and so it really forces you to think about the assumptions and the assumptions are about the business so that means you have to go back and say what would a price drop of 5% mean or what would that be? And if we go back to the previous video we made you can find those higher earnings yields within small companies because big great businesses have already, let's say lower earnings year yield because everybody knows them and everybody wants them in their portfolio. Thank you, I think this was really amazing and it will really help investors to focus on and I think the hard part is you look at 100 businesses but probably 99 you have to just know it doesn't fit the criteria and you say next which is I think the hard part when it comes to investing. Yes, but it's actually it makes life easier because I know for example first of all I don't have to troll to a lot of different companies and looking for bargains because companies that are not highly profitable I don't even need to look at them. Secondly, so what I do do is we have a list of I don't even know how many companies are on it of companies that fit the criteria based on the value they create but don't fit it based on the price we pay the price is too high so I keep following those and I know I would love to own these if one day they come up for sale which they sometimes do and then we can add them to the fund so that makes life a little easier. The other thing about making life easier is that there are whole industries that don't create value and the most famous one is airlines airlines just do not create shareholder value they create lots of value for passengers but not for shareholders. So that means I don't need to follow a single airline so that already cuts out a lot. Not even the discount, Ryanair and so on. No, no, because even that last time I looked, because I do look there were 730 airlines registered in the world and three of them had any real profitability and if I need to look to 730 companies to find three markets my time is better spent elsewhere, you know. Very interesting. So Ryanair is a great company South West Airlines in the US is a great company but I would not propose to have been able to identify those. I'll tell you one thing though there's a company in the indirect airline business which is called Amadeus which handles most ticketing systems around the world and they get all the value of the... I mean this is a highly profitable company it's a Spanish company quoted in Madrid AMS, Madrid which has been an excellent investment it's too big so it's not in our fund but that's the way a place to look. So that would fit the great business. That would fit the... that is certainly a great business and an excellent high quality business. So that one is on your list or not? It's not on the list because it's too big. So it's... and I don't wish for it to get smaller so that's probably a ship that has sailed as far as we can tell. But if, I don't know, Spain goes bankrupt or Italy or something we might see the ETF sell it and then buy a great business at the lower price. Yes, but it's already... I mean it's big, it's already well known but it's just an example of a company that is living on the fringes and then becomes interested. Well, thank you for discussing this I think you mentioned some things that are very very interesting like return on invested capital or return on capital return on equity cash flows so we can make a video on that if you agree. Sure. Perfect, well thank you. Thank you for watching and we'll see you in the next video.


Live from Boston, Massachusetts. It's theCUBE at the HP Vertica Big Data Conference 2014. Brought to you by HP. With your hosts, John Furrier and Dave Vellante. Okay, welcome back. We're here live in Boston, Massachusetts. This is theCUBE, our flagship program. We go out to the events and extract the signal noise. I'm John Furrier, the founder of Silicon Angle. Our next guest is Shilpa Luwande, VP of Engineering and Aiman O'Neill, Director of Product Management here at HP Vertica. Folks, thanks for coming on theCUBE. Really appreciate it. Good morning. Thank you for having us. We're gonna talk about the product, product management, the product roadmap. Obviously, Colin Mahoney at a great keynote. This conference is all about your customers and it's great. A lot of practitioners on. We had the U.S. Postal Service on, which was just an earlier, fantastic interview. I mean, that represents everything in big data. Internet of Things, legacy, you name it. Great customer testimony. You guys have had great success. Congratulations. But one of the things that Colin Mahoney said in my interview this morning with him was, is that I asked him if HP Vertica's solution was a Ferrari. And I was kind of teasing out the question of, hey, you know, it's a high end, high performance. He said, yes, it's a Ferrari. That's really the flagship. You guys are known, had been known for high performance. But as you guys have gotten with Haven, as HP starting to broaden their portfolio, what does the product roadmap look like? Because not everyone can drive a Ferrari and no one wants a Ferrari in their driveway because they're going to be embarrassed and can't drive it. And if friends see that they can't drive it, they're going to say, no, just for that reason. So how does a customer engage, that just wants to drive with big data? Not necessarily. And then maybe grow into being a Ferrari driver. Well, we've made the product much more accessible very recently because we launched a cloud version of it. So this is for a business that doesn't necessarily want to maintain their own hardware or set up a software cluster themselves. They can now access it, host the BIOS. We also shipped an appliance. We have a few customers now who like the fact that they get up and running much quicker. So they're able to do analytics much faster because they're not spending so much time on set up. So I think it's become more accessible than a Ferrari while it's still as fast as one. And we've always had the community edition, which is free for you to use for unlimited amount of time, one terabyte on three nodes. That also is, we have a big focus on community, so on building out the community of Vertica. So it's a Ferrari that anybody can test drive, and it's a Ferrari that...  I kind of baited him on that question, but the reality is that looking at your wins and successes in the marketplace, it has been really high performance data environments. And that's not going to be the one off anymore. It's going to be the rule. Pretty quickly, as people start realizing they can get their data pretty quickly, that's going to be a requirement. So I kind of wanted to get that up, but not everyone's ready for the Ferrari. I was talking to someone last night when I was walking back from Legal Seafood, and he's here, huge data warehouse, huge enterprise, and he's here to learn about columnar store and what you guys have, but he's coming from a legacy data warehouse environment. What's your product do for him? He's new to Vertica, so how does he engage and how does he view your product? So the way to look at Vertica is that the legacy products for data warehousing, they basically stop at that. They stop at the data warehouse use case, but now with all of the machine data that is being generated every day and the volumes that are growing and the diversity of data, those products don't handle that. Vertica is probably the only product in the market that can handle that entire gamut from the traditional business EDW type of use case all the way to the big data type of use cases. And so I think that's where, we're seeing a lot of traction in these really large data sizes in enterprises who are looking to go from just the EDW to the broad platform. Hey, man, how about integration? How does someone integrate Vertica? And let's just say that, oh, I love the vibe, love the product, love the roadmap. How does someone get involved with the product? What's the entry point? Well, I think with Differency, it's the huge number of certified partners. Most of them are here, but from ETL to BI, there are a lot of products out there that showcase the fact that they run well on Vertica. And so there's, in addition, though, there are plenty of APIs that are on our community where developers are very active in supporting each other. And our developers answer the questions live, but also many of the developers from our customers do. So I think that's one of the best ways to integrate is to get involved with the Vertica community. Got a great tweet from someone from another interview just said, I asked some examples of how people are pushing things, not forcing things into a relational database, but looking at the data perspective.  Now they can identify profitable customers and transactions. What does he mean by that? Well, upstairs right now, the HPIT is giving a presentation about just that. They're showing you how you can analyze your sales pipeline. And they're using Vertica to examine, for example, how often salesperson changes the predicted close day, changes the size of the deal. And so they're showing people how to make, not be surprised at the end of the quarter and really understand the future of their business. So we've got a question here from the folks here on CrowdChat, which is better for getting things done? A Ferrari or a pickup truck? Guess it depends on what done means. I guess it's not a question, it's more of a statement. So engineering-wise, that kind of implies a road exam. What road are you on?  What is a pickup truck in the big data world? If Vertica is a Ferrari, what's the pickup truck? So we do see this, people moving a lot of data. First of all, you've got to store the data. And so I think we see HDFS or the Hadoop file system becoming sort of that place where people collect all the data. And then getting the value out of that data is where I think Vertica shines. So whether you're just exploring that data, Vertica's broad SQL capabilities, as well as our performance, helps you sort of get value out of the data to understand what's in it. And then when you're ready to put that data in production, is when you use the high performance, the Ferrari part of Vertica, right? So Vertica I think has these- Is Hadoop the dump truck? Is it the pickup truck? It's certainly the place where people start. So it's certainly where people start. But John, I'll actually finally exhaust this car and truck metaphor to answer your question about the data warehouse. So we have a new feature that came out a couple of weeks ago that we call the zipper truck feature. Because the biggest challenge for these people with enterprise data warehouses is how do you keep all the traffic in different lanes? Because they have a lot of demands from them, from people who want to run batch reports to do payroll or comp plans. And then executives who want immediate response on their ad hoc queries on their, say, Tableau or ClickView dashboard. And typically these compete and fight with each other because the same queries, these different queries are going against the enterprise warehouse. So we have, for a couple of years now, we've had a workload management feature in Vertica where we can put these different kinds of workloads in different traffic lanes so that they don't step on each other. And we took it further in this last release where we can dynamically change the lanes. So you've probably seen these zipper trucks early in the morning when you're commuting that pick up the barrier and create four lanes inbound to the city one time a day and then four lanes outbound at another time a day. So that's the feature we did. We can now dynamically adjust the resource pools for different workloads depending on the time of day or the business priority. So I got to ask the roadmap question. How do you guys, what's on the roadmap for you guys?   Now you got Haven. As these things come together, where do you guys stop and other people pick off? Because we saw news around Hortonworks as a new partner for HP. You have a relationship with MapR, Tableau's here, all your customers here. On the roadmap, where is the innovation going to stay core on the engineering side, product positioning side, and where do you leave off and others pick off? Yeah. So certainly that Hadoop ecosystem is something that we are trying to become a part of more and more because our customers are using it that way. And so the H in Haven is Hadoop. So what we are going to continue to innovate on and expand on is providing that Hadoop user base ability to do advanced analytics. Trying to leverage that data through the SQL paradigm and trying to get value out of that data. We are going to rely on the Hadoop distributions to really provide the core of Hadoop itself, right? So we are not intending to create our own Hadoop distribution. We would try to integrate with these. So we were working with MapR for a while, working with Hortonworks on things like Yarn integration. So we're going to play seamlessly with the other components of the Hadoop ecosystem. Same thing with the BI vendors. So we're leveraging, you know, Logi analytics, Tableau, MicroStrategy. We have a lot of partners who help us with the visualizations in how you consume the data that Wharticka now enables you to get at really fast. So that's how we see it. Any comments on that too? Yeah, well, we're going to focus on this scale. So we've gotten into some peripheral technologies recently but we focused on handling the massive amounts of data. For example, we have started to do some text and sentiment analysis of less structured data. But we still pull in autonomy libraries to actually break open that data and find the structure in it. But then we feed it into Wharticka to do analysis of massive amounts of data. So you'll see that again and again when we partner with, you know, when we get into peripheral technologies, we're going to partner with various people to understand the formats. But then once we extract data from those, we're going to be the scale answer. I got to ask you a product question, Amon, because this has been debated. Certainly Silicon Valley has been talked about. Product management, the best CEO of startups and product managers is a tough position because you're always saying no on one hand. And you also got to incent people to get things done on time.  What do you say no to a lot right now? Because big data is one of those markets where there's so much demand. I want this feature. You're simply smiling. I'm going to see just what your engineering team like. No more, we need higher, more engineers. There's so much demand. Where do you, what are you saying no to right now in the product roadmap? And where are you guys focusing on? Because that's really, I mean, everyone wants this bell and whistle in the software. So it seems to be unlimited and out of features that could be in products. So how do you handle that product question of the no? What's the no? Well, I am, I am blessed in that we have a- Oh, the ship will say no. But what makes it easier for me is the tight integration that we have with other parts of HB software like ArcSide, Opera Analytics and Autonomy because when I'm asked to add bells and whistles to say our tech searching or to our interface for, you know, showing how queries are happening, I don't have to put those into verdict and necessarily because I can leverage how they exist in autonomy and ops analytics and in our security product. So as these four or five HB software assets come tighter together, it actually makes it easier for me to concentrate on the core. So I'm going to ask the question I asked Jeff Kelly. It's a Hadoop world. I want you guys both to answer if you can't get on the same answer. You get the same answer, you don't need to answer. It's a Hadoop world. How does Vertica fit into it? So interestingly enough, the world of Hadoop and databases seems to be sort of converging quite a bit right now. The Hadoop world started out with MapReduce and, you know, I think as everybody has come to the conclusion that MapReduce is pretty much dead, you know, it's on its way out for sure. And the Hadoop world is moving now into a sequel world, right? So this is where I think Vertica has a lot to offer because one, we have a very mature sequel engine and over the course of working with so many customers, we've sort of grown up with the big data community in terms of expanding the nature of our product. You know, when I first started with Vertica, it'll be almost 10 years now.  We were very excited when we got our first benchmark on a terabyte, but now a petabyte doesn't feel very big to us. So I think that's where all of the learnings that Vertica has over the past years of what it takes to do a sequel on large datasets, that's what we have to offer to the Hadoop community. And your thesis there is MapReduce needs other tools are too complex to program. They're too complex and I think they're limiting. So sequel I think is a language that is, people realize that there is a lot of skill set out there that people already know how to use it. And then it's very simple to express a lot of things in it, right? So it's not something that can do everything, but it can do a whole lot of things very easily. And so if you can figure out the technology under the covers to make sequel be the language and leverage the whole ecosystem that's already built around sequel, then you can get a lot more out of your data lake basically. I think it's an HDFS world. When I ask customers over the last couple of days why they love Hadoop, the part of the stack that they love is HDFS. And so what Vertica can do for you is in our recent release a couple of weeks ago, we changed our storage layer so that now you can plug in HDFS to be your storage layer. This means you can ask us so much more data with Vertica. Previously there was maybe data that you didn't think was very valuable. You didn't query it very often and you didn't wanna put it into a database because you thought that was gonna be expensive or take your time to structure it. Now you don't have to trade off because we can query everything that's in your data lake because HDFS is our storage layer. So true or false, the future's about thinking about the data and not the database. Do you see that as what customers should be thinking about the data itself versus the database they're storing it in? Or is it still a database decision then, the data? What comes first? Thinking about the data or thinking about the database?  I was just gonna say, if you don't have to think about the database, just pick Vertica, so it is all about the data. That's a good answer. I think the database is still important because what people loved about SQL is that it abstracts their business questions from the way it's physically stored and that's what a database does for you and you don't have to care so much about the details of the data's location. So final question, we're getting cut on time here, Aiman, I want you to help with the product perspective and Shilpa, talk about the engineering perspective. The question is, looking at where Vertica is today inside of HP, HP software, what you guys have done with Haven and across the portfolio, explain to the customers in your own words out there, people watching, what's the update? What is it all about? What is the product all about and what's the technology all about, Haven and all the big data activities? I think it's about being able to consume many kinds of data, so we'll take any format. Also, don't throw any data away. You can bring many, many petabytes now and also it's no longer about just BI, with the new ways of deploying Vertica, we've gotten it out into the line of businesses, so it's not just for the specialists anymore, it's become more accessible to a lot of more people in your enterprise. Shilpa, from a technology perspective, what's it all about? So HP has this unique combination of assets, so there's Vertica, of course, but there's autonomy which allows you to do human data and get value out of that. We have some leading enterprise security products and Hadoop, of course. And Haven is really all about putting those assets together and building an ecosystem around them that enables people to use these assets to really solve problems. Ultimately, HP's mission is to make things matter, make it matter. So we believe that with this Haven suite of products, you can actually make a difference to your business, to lives, and so on, as you heard today, the Conservation International Project. That's a great example of what you can do by putting some of these technology pieces. And making it reliable too, making it have a reliable product. And making it reliable, making it available in different form factors, so making it available through the cloud, through appliances, different ways to consume that data, but it is really all about trying to get the most value out of all your data, not just structured or unstructured. I've been called the Big Data Fanboy because I love anything to do with big data, but I think the conservation example this morning shows the value of across the entire world, industries from non-profit to for-profit, how transformative data can be. The engineering and product perspective here at Vertica, this is theCUBE at HP Vertica's Big Data Conference live in Boston, this is theCUBE. We'll be right back with our next guest at this short break. Thank you. Thank you.