And, well, Song Nim and I, we composed this panel very carefully. So we had the academic view, the government view, the business view. And now we have the finance view with Nicolas Piaot and also the energy and climate view. Because Nicolas has been a long time working for ANGIE in France. Huge energy company, so he is an energy man basically. But then he started to set up his own company that is Tilt Capital. And Tilt Capital is an asset management group which supports start-ups, well start-ups in different phases concerning the energy transition. And, well, that is an extremely important and interesting endeavor. And Nicolas, we are happy to have you here and the floor is yours. Thanks a lot, Friebert, and very happy to be there. It's really an honor. And it's also quite intimidating because, frankly, after Philippe, Jonathan and Christophe, as you were saying, I'm not at all an expert of this field. I'm more on the receiving side of all of what you've described as an energy guy. And actually I'm going to try to bring on board what I've just heard during the panel. I think for us what it means when you look at it from the energy perspective, and that's maybe the first message, is I would strongly oppose any views that say that with the energy transition, the energy tri-lama is dead. You may have heard this, you may have heard that, you know, energy tri-lama is basically you need to choose between, you need to compose between three pillars, affordability, sustainability, and security of supply. And I think what 2023 has brought is actually that security of supply has become the main focus of that energy tri-lama. I think it bears two challenges. The first one is we should not forget about the other two, affordability and sustainability, and we'll come back to that. I think the second implication is that it brings back energy in the field of geopolitics and industry. Think of the course of the last decade. Energy has been too much seen as a financial opportunity for a very simple reason. It was the early stages of renewable development. It was about securing contracts, EPCs, financing, etc. And there were no questions asked also because it was very limited in scope compared to other forms of energy. I think today this is changing radically and we need to acknowledge that. So I think that would be the first message is what we are seeing as energy investors is that for all the messages that have been passed by the panel is security of supply is coming back as a major topic in any energy investment. And what it means for us, for example, is today we may be embarking and you open, Friedberg saying, you know, Russian gas may have been a problem here or there, but eventually that's not the real issue. The real issue is much more the dependency on China on a number of topics and in general with those key materials. Today when you look at companies in which we invest, this is not a topic. This is not a topic because it is not seen today. If you want to obtain any, if you want to obtain an inverter, if you want to obtain nitrogen gallium based chip or silicon carbide based chip, you have no issues. The question is how long will that be? And so, of course, all what you've mentioned around, you know, enhancing the extraction, enhancing the recycling, etc., so having additional resources is something that as energy investors we welcome, but I think we should be much more vocal about the need for that. I absolutely agree there will be no energy transition without additional mining, without additional extraction. But then it also bears the question, of course, of sustainability. And here, let me maybe come back to one element coming from that world. The thing that I would have one message on this is let's try to not make the same mistakes as we have done over the last decades on oil and gas. We cannot afford to have another Ogoni disaster or Makondo disaster with the mining industry for those critical raw materials. I think if we have that, and Jonathan, you said it very clearly, there is probably some image issue too. But beyond the image, I think there is the fact that if we have something of the magnitude of what happened in Nigeria with the Ogoni community or with Makondo with BP, I think it will cast a very strong shadow on the reality of the sustainability of that energy transition. And for this, and please bear with me, I'm not at all an expert on that, I do think we need to engage into more cooperation on this front. Actually, I even think that this whole critical material issue could be a way to foster a greater cooperation between consuming countries and producing countries or extracting countries. Because let's be clear also, today when we are saying we need to mine more, we need to refine more, who are the distant theories of those materials? It's rather the developed and rich, I would say even rich population of the more developed countries. How does that affect locally the people who are on the land where you have this extraction and this processing? And I think here we need to engage into more cooperation. I think it should translate into profit sharing. I think we should maybe learn some lessons from some oil countries that have been fairly good at this. I always used to say to people, why don't we drill for oil and gas in Switzerland where there are no taxes, virtually no taxes? And why do we drill in Norway where there are 78% taxes? Well, because there's oil and gas in Norway. And I don't think the Norwegian government or the Norwegian people would tell you that it has affected us in a bad way that there was 78% taxes on each barrel that was taken out of the ground. I think we should have that same kind of reflection on the critical raw material. We need to use that to transfer scales, money, maybe try to create value chains locally so that we actually build not only some resilience, of course we need to do it in Europe, but we also need to build those trusted value chains on the critical raw materials outside of Europe or India or wherever so that we can multiply those trusted value chains. And I remember last year Caldo Malmubarak said that the UAE were focusing on those trusted value chain. I think this is one example, one area where we should be targeting this type of cooperation. And of course there's a lot of, we can say a lot about ESG etc. but I absolutely believe that if we were not sensitive to environmental and social issues in mining, we will have a backlash on the energy transition because people will say it is actually not a clean transition, an adjust transition. I think this is critical. And finally the last one I would like to make is more as an energy guy and I'll be more raising questions actually than providing answers. There was a very interesting report from the IEA following the increase in commodity prices in 21-22 and the freight prices. Actually when you look at this trend, commodity prices plus freight prices led to a 25% increase in capex for renewable energy, offshore wind, onshore wind, even solar power etc. One reason for that, we talked about electric vehicles. If you take an offshore wind turbine, you have 15 ton per megawatt of critical materials in offshore wind turbine. You have one ton per megawatt for a gas turbine. If you consider that a typical offshore wind turbine today is 15 megawatt, that's 225 tons of critical material. That is actually 40% of that is copper. If you have a doubling of the price of copper for an offshore wind turbine, it's just one million, one million more costs for each offshore wind turbine. So I think one thing we need to be aware of is that we have traded a short-term, variable cost-based energy economy, basically electricity prices and energy prices were determined by the marginal cost of gas or what have you called to a certain extent, to an economy that's going to be increasingly linked to fixed cost price. And that has dramatic changes to the energy market, not saying it is bad or good. I'm just saying it will have implications. If you invest in a time where the cycle is very high on commodity, we will be looking for 25 or 30 years higher cost, and hence we will have impact on competitiveness. And so I'm aware that I'm not bringing any solutions there. I'm just saying that we need to be very cautious of all those implications. And I think one thing it means is, as an investor, I would say we need to find ways to soften the boom and bust cycles that will have repercussions on the capex. I think innovation is critical, and Cobalt is a good example. We first had NMC batteries, which were 532, so 50% nickel, 30% manganese, and 20% cobalt. Now we're running rather on 900, so it's actually 90 nickel, 0.5 manganese, 0.5 cobalt. So indeed, innovation will help us build some resilience at the same times if we innovate and we deprive some of the countries that see that as a way to create sustainable wealth for them. This will also cause a problem. So that means that again this calls for heightened cooperation to avoid that some countries that may want to today invest massively in some of those minerals. If there is a massive innovation in 10 years, don't find themselves with stranded assets and a link to unjust transition. Well, thank you.


But now we're going to do the legs. They look kind of complicated, but they're really not. We're going to have eight pieces of the length that's on the plans, and then we're going to do what I'm going to talk about here. We're going to cut a tenon on the bottom of all eight of those. We're going to have another eight pieces that are five inches long, and we're going to cut a tenon on the bottom of those. So I have sixteen boards. What I'm going to do is bind them together four at a time so that I can cut that tenon by running it over the table saw blade. The table saw blade has been set precisely one and a quarter inches tall. I do that by using a one, two, three block, the one inch part of it, and then a quarter inch little measuring bar. So that gives you a pretty accurate feel for the height. So I just set it up like this with a one inch and with a quarter of an inch, and then try to find the apex of that. And let's see, if I wanted anything, I would want it to be slightly under so that this would be slightly too big, and then I can always sand that down. If I'd slightly over cut it and then this tenon was too small, I can't add wood back. So that's always the mistake you want to make, but I'm going to try to cut it as accurately as I can. You've got to find the apex of where that is the highest. I think that's going to be really, really, really close. All right, so I've got that set one and a quarter inches high, and I have measured in two inches. So when I cut out this part here and then cut out this part here, I will have a tenon that's two inches by, this is four and a quarter total. So one and a quarter, one and a quarter is two and a half, so that will leave one and three quarters in the middle. So that's what we're doing. I'll show you some of it. I'm not going to bother you with all of it. I decided to take these rough cut lengths first. I've got 16 of them, and they're all more than enough length, and then we're going to cut them after we do the tenons. We're going to cut them to size because if something went wrong here, then I would have the ability to cut the tenons again because I've got extra length. If I cut them to exact length and then something went wrong, then I'm done. I've got to do all new pieces. So it makes sense sometimes to not do your final length cuts until you've done some other procedures. Generally when you're doing woodworking, don't cut profiles and stuff too early in the process because you may want to have nice square edges for things, so you would never want to round over something early in the process. You'd stay that to the very end. All right, so that's what we're going to do. I've got my cross cut sled here. There's another video available in my channel on YouTube showing the building of this cross cut sled and using the William Ng five-cut method to measure if this back fence has been set to perfectly 90 degrees. You know we're going to be perfect, but for all practical purposes it's perfect. The holes, you'd have to see what the holes are for by watching that video on building that sled. If you don't have a cross cut sled yet in your garage, that's fine. You can use the miter gauge that came with your table saw. You'd probably just want to get a really stable fence on it though. In this case, I've got two, three-quarter inch, so I've got an inch and a half of stability on that, and then I would push my work piece across that. It's just that when you do build yourself a sled, you want to use that, but I could have used just the miter bar. Now, a couple of things I thought of while I was cutting that. The reason for eight of them that would be five inches long, I don't want to be cutting two inches into a five-inch piece, leaving only three inches to hang on to. For me, that gets me inside of my safety zone. I don't want to be holding on to three inches here to cut two inches, so cut these first and then cut it to five inches in length. That's the one thing. The other thing is, I'm using a 24-tooth rip blade on here, and that has a flat profile on the top of it. If you have one saw blade and it's a combination blade or it's an 80-tooth plywood blade, then what's going to happen is you're going to get ragged edges. That's all right. Don't go buy a whole new blade just for this build, but you will eventually want to add a flat top rip blade to your collection so that when you're doing joinery and you're cutting tenons like this, you'll get a nice flat top. The way these go together is you'll have the big long ones here with the tenon on it are going to go on the outside. We're going to glue two of these where all of these tenons are lined up, and then we're going to come in four and a quarter inches, and we're going to glue two of these leaving a four and a quarter inch span right here. So long board, then the components are the pieces, and then the other long outside board. So when we glue it up this way, and it's going to have the mortise, it's going to have the tenon, and it's automatically going to create the tenon on the top, just based on the size of the piece of wood. Alright, so the secret here is to put these pieces onto this piece and glue it, and then have this be four and a quarter inches, and then span by the outside. So that's what we're after. Now here's my one recommendation. This is a lot of gluing and a lot of trying to line up and stuff, and so whenever I'm doing a glue-up that involves a multitude of parts, maybe in my workbench here each half had six boards in it. So when you try to glue up something that's six boards wide, or in this case four boards wide with a couple of pieces, things can slip around, you can have difficulty getting it lined up, you think you're all lined up, you're putting on your clamps, there's a lot of moving pieces. The way to deal with that problem is don't do the entire glue-up all at once. So what I did yesterday was I just glued one of these little pieces, and one of these pieces on top of one board, and I stopped right there. Then I did another one. So just glue up two pieces, two layers at a time, let it dry overnight. Now I can come back, and all I'm trying to do when I put these together is simply one glue job in between. And so now this other stuff isn't going to move around, and this is much, much easier to do. So my recommendation would be to, you know, it may take an extra day or two, but do your glue-ups in sections instead of trying to glue up all four pieces all at once. So that's some advice from small workshop guy. I do, when I'm doing this, I do use some salt, in other words I put my tight bond two in this case. This is, if you, we're going to have this outside a lot, you might want to use tight bond three. It's more designed to be okay outdoors, but if it's primarily an indoor pop-up workbench, which mine is, and it's not going to be in the rain or anything, then I'm just going to use tight bond two. And what else? I just put the tight bond on, I spread it around my hands, I don't worry about trying to use sticks or brushes or all sorts of fancy things to keep it off your hands. My feeling is when you spread that glue around with your fingers, you have much better tactile feeling and you can tell when the edges are too dry and then you just keep rubbing more glue around to get those edges wetter. So just use your hands. The other tip that I use when I'm trying to line things up, if I've got something and I want them to be lined up this way, then I just put a board in a vice. Now you don't have your workbench yet. You can do this later after you've built your pop-up workbench, but I just put a board in a vice so I can get it up against there and keep things more lined up in that direction. All right, so I'm going to get a little glue up here. I've got a wet rag, I've got a dry rag, I'm going to get stuff on my hands and then take it off of my hands. So in other words, once you get the glue spread around, do two things. Put this back down and wipe it. It's called wiping the baby's butt. That's from Next Level Carpenter. That way I remember it.  And the same thing is true here. Don't pull this up and then do a whole glue job and set it down with a top up and a loose ripping around and then pick it up and do some more because you'll end up messing up all of the openings and you'll be cutting stuff off and it'll rag it pretty quick. Close it every time, wipe it every time with your wet rag and keep it nice and clean. Ah, let's see, secondly, to make it work better, keep it full. This works much easier when you've filled it up. So I've got the large bottles and every time I get about a third of the way down, I fill it back up. All right, so get it, you want to make sure when you're gluing that you're getting right up to the edges and then you're going to clamp that to, so this, to make sure the edges form a nice tight bond through your clamps. Again, with your fingers, you can feel where the wet is and where the dry is, so just keep spreading stuff around until it feels nice and wet everywhere. That way you don't have to use too much glue and you won't get as much squeeze out.  Go around the outside edges with a nice beam, go around the middle a few times. You can always come back and put more, it's pretty difficult to take it off.  Do never put down your glue bottle until you've cleaned it up. Alright, so you can start rubbing this toward the middle and then you can get right on the edges and you can feel where the, this is a good time to be able to wipe up if you went over the edge and got on to the outside. It's an easy wipe up. Generally, you want to be careful with excessive glue and wiping with a wet rag because if that wet rag gets all gluey, then you really, what you're doing is just spreading glue on to the edges where you don't want it. So, I want to make sure all these edges are nice and wet and well-covered and then feel if I've got good coverage in the middle. I don't want any great big globs anywhere. I want it all kind of spread out, so that works cool. Wipe my hand off and get these two glued together. Here's the beauty of having this mat, the gluing mat, is I don't have to worry about glue now getting on that mat. I got a little misalignment here, but that's okay. I'll straighten it out with chisels, so get it lined up as best I can. Probably more important to have the ends lined up here. Could have put some salt on there. Salt would keep it from moving around as much. I got enough surface here, that's not much of a problem. And then, here's when you're doing any kind of a glue up in your woodworking. Make sure you have a million of these little clamps and a million of these somewhat larger clamps. Many of your glue ups are just going to involve small things of this nature. Start on an end. Don't apply a lot of pressure, just enough to get it started. If you pry too much, it'll pull it up or down. And then, when you go to the next one, put the handle on the other side. I've got a whole video about how to make all these clamps slide easier. You might want to see that, and I've got some videos on keeping clamps clean. So, alternate. Try to go over a few inches. Now, there's nothing being glued here, so I don't need any here. I normally wouldn't do this big of a span, but in this case, there's nothing here to glue, so I'm just trying to go there. Again, do not over-tighten. So, you just continue that process, alternating on both sides, getting it just tightened down just a little bit. I'm starting to get some squeeze out there. And then, I come back on this side and squeeze everything down nice and tight and kind of wipe the bottom, if that's the process I want to use. I have a better process, recommended process, but I don't think right now I have any wood chips, so I'll have to look at my barrel. Instead of wiping this, you might come in here with sawdust. And if I take this one, it's bulging out like this, a little bead, and that's about the right amount. I want something to squeeze out, but I don't want excessive, so this is about perfect. As I tighten up more, this will squeeze out a bit more. And then, come in with some sawdust and rub all of that. I'll tend to ball up that glue and pick it all up without spreading it all over the place. So, next level carpenter says, and he's my guru for a lot of things, he says that once you use the sawdust trick for cleaning up glue, you'll never go back, it'll be your lifetime habit. So, give it a try, see what you think. Getting this glue off of plywood can be problematic. Here's another tip. Think about the components that you're doing and the fact that you're going to get glue on them, and you want the easiest way possible to get that cleaned up. This is four and a quarter wide. How about making it four and a half inches wide, all of them. Do your glue ups and then pass it. If you have, this is assuming you have a jointer or a thickness planer, and then pass it over the jointer or the thickness planer and take off another quarter of an inch, I guess eighth of an inch on each side. So, four and a quarter, make it four and a half, that's an extra quarter of an inch. Shave off an eighth of an inch on each side. You'll be down to your four and a quarter, and you will have had the easiest way to get all the glue off, because glue will show up under whatever varnish or polyurethane you're going to put on it. So, using that method, there is no glue. You've shaved it all off using your power tools. Alright, but that requires thinking ahead. Generally, and I didn't do this on these plans, but I didn't want to bother you with that.


Čutih, počutim, zelo naredamo vse teorema, z počutim, na konvek sez, v Hilberti spasih. Tegorem je to, da se vse nekaj, da se nekaj, da se nekaj, da se nekaj, da se nekaj, da se nekaj. Zato, kaj da bom razližila, da s比pusti preč, bilem blog P-k Open Space. Zda nekakvo PS, nekako H, nekakvo B space, in da, možem da, v sen vene, bilim po neko V, nekako P-komen ljudi v početnih s evosti gled endorse, Resakč, that closed here means sequenšal底 closed with respect to the strong norm so with respect to the norm induced by the distance. For when I don't write anything I mean, this is close with respect to the distance in h. for the long or Nas Durham dish. Pranje in š �čenje There exists a unique ... Nud Organization z štočef... ... Devil, that we denote by x, though we satisfy ... That distance between H and X Tudi, je zelo vsega odgovoriljna vsega vzgovijaj. Zelo da sem zelo komentato, če me zelo, kaj me ne patila. V sezhu odgovorile vsega h in zezir, je vsega h minus, zelo je, da je vršen začinjen, če je vršen, bo je nekozvršen, bo je to vršen. Zato bo je, da je vršen začinjen, če je vršen. Kaj je tudi? Kaj je vršen iz pomeče? Zelo je, da je vršen iz pomeče in vršen sub pomeče, Weekly space while a set sub set in the space is just the smallest possible, smallest in the sense the infimum of the distance. Which is nothing else, of course. Kaj je to teorem, zelo je naša izgleda, da se je vse konveč in tudi je in za vse, da je vse za vse, da je vse za vse, da je vse za vse, da je za vse za vse, da je za vse za vse. Zato je počak h, da h je vsega in vsega. Vsreč je, da h je vsega. Zato počak h. Zato počak h je vsega. Zato počak h je vsega. T wouldn't say that there is just only one, probably in this picture, is this X, which minimizes all possible distances. So the length of this segment is less than the length of all other segments. The idea is that if we could talk about tangent but we cannot. For the moment we cannot talk about tangent but the idea is that. Ok, infinite dimension this is 90 degree and this is the point which minimizes the distance. Ok, we cannot do this in infinite dimension. taj počet, pa ideja je počet. To je počet. Kaj je ideja nekaj? To je ideja. Počet način jaz počet. To je... To je... Nekaj ideja je počet. Taj počet. Počet način jaz počet počet način jaz počet način jaz počet počet način jaz počet taj počet način. To je... To je interseksja. Taj počet način. In taj počet način posez. There is just one intersection Why? Morality, to je nepečit. Just the idea, this is not the proof. Morality, why there is only one intersection? When there are no... When things can go wrong. Yes, of course, you have more. Well, the first is the point of minimal distance, no? The idea is, so you have two convex sets. One is the ball, the other is the sea. So you enlarge the ball until you touch the first time. And the claim is that you touch the first time ki je nekaj počet, nekaj počet, nekaj počet, in nekaj počet in infinitivno počet. Kaj je, da je počet, da je v finaj dimenzij, pa v istvu. Zelo, zelo je konveč, pa v istvu je to. To je konveč, je počet, je počet, je počet. Zelo, ki jaz sem v spasih, kaj je to unit, Kam bom se ona da je problem. Spodobno je izgovorila, katero se bolj jem je zelo po napravljenj snah, njen zelo po napravljenj, katero je ide dvler na bolj, kaj drugi vzlušal, ki so očilo imelje in refleti. N disappoint posledajte, da bolj je�� nesvetnim konvečnjem. but the definition of uniformity convex. And therefore the idea, okay... This ball is uniformity convex, is more or less like this, and therefore, even if s 나도 uniformity convex, but the ball is... So this is something behind, okay, so and you see this picture is very quickly done. Zelo, da je bilo izgledaj na bolj, kaj je, da je tudi na spračenost. To je neuklidian. To je nekaj počist, tako tudi je nekaj 90 gradov, začne, da je to nekaj počist, je počist. Počist je to, da je nekaj počist. Zobčite razvorega. Zdaj, se, ki H je v C, ne zelo včasne, naredi je zelo včasne včasne. Včasnje zelo včasne je mene delvega z konstitutnih zeljic, in je zelo alesem zelo včasne. Kako je zelo naredi, zelo včasne. je lahko, da gre zelo, ki zelo ta je tle. B Cinh se zato, da je tle. Bath. Rastče se je to, da vólj na zelo vzelo na tle. Bath. Bath. Čae je nrno. Kaj je prišel? Vač je tle. Ča je? we have zero equal to zero. Not only this, but H is unique. X is unique because if the distance is zero we know from the property of the distance, then there is just only one point having zero distance, exactly that point. So this is the unique solution of this minimum problem. So by the way, notice that you have to solve a minimum problem in infinite dimension. Se je probrnje vnitrat vsdo varješnji. Navelj cambiamo, da se dokazujemo vso mirany. Moj dr overlač s včeljih. V neko danas, da se te minimuač naredilo, tako klasik это vnitrat vsdo varješnji. Na početku z radinii, pros Charlie je x ak to h, zelo da je zaštej. sreči, da h je nekaj v zivu. Zazaj da načaj... Zame načaj... Zazam, da je tudi standard metod i način kakoliv nič, da njemo vse, da tudi načaj vse. Zelo je. A načaj vse, da je tudi način? Tudi je to tudi, da je tudi vse. Tudi je to tudi. Tukaj, to je infimum, če je infimum z vsem H minus C, kaj je v C. Ok. Then we can pick a minimizing sequence, which is the following, sequence of points, let me denote it by C... C n. Let me denote it by C n, sequence of points of c, such that the limit as n goes to plus infinity of the C n h C n, n is equal to the infimum. This is by definition of the infimum simply. This is an infimum of this function. You can take a sequence of point here converging to the infimum, such that this h minus cn converges to the infimum. This you can always do. OK? Sorry for the notation. You have to be careful. Capital C, this is capital C. And this is small c. I will try to write symbols. However, these are points in c. So maybe I am using the letter c for this reason. So I will try to write cn very small. OK? So this always exists. There is a minimizing sequence. So now let me give you two proofs. One proof, first proof, we use the parallelogram identity. So from now on, therefore, this proof is adapted to the Hilbert setting, right, because we know that this characterizes Hilbert norms. So this proof cannot be, if we want to do the proof using the parallelogram identity, this proof cannot work in Banach. So we use the parallelogram identity. So remember, so our parallelogram identity is the following. So we have a, b, and therefore r's. One half a squared plus b squared must be equal. This plus this is just this plus this. So this is our parallelogram identity. And we try this with the following choice. h minus, say, cn, and b equals, say, h minus cm, with two different indices. The idea is that, which is the idea. We want to show that this sequence is Cauchy. Therefore, if you want to show that this sequence is Cauchy, we want to control the difference cn minus cm. And so, to control the difference, you see, if I take this minus this, I have the difference. And then there is something else. So I try this. So because we want, because we want to control cn minus cn. Hope, the hope is that cn is Cauchy. This is the idea. So let me apply that, so let me write it exactly like it is. So we have, say, I prefer maybe to multiply everything by one half, so that this is one four. And so we have one half. Now, h minus cn square plus h minus cm square. Equal, one four. And then we have the sum, which is 2h minus cn minus cm square. Plus, now the difference is what we want to control. So cn minus cn square. So let me write the right hand side as follows. This is equal to h minus cn plus cm over 2 square plus one four cn minus cm square. Because I put the four inside the norm, but the norm is squared, so this is actually a two. Two cancels with these two, and the two remains just only here. And therefore, so we have, so let me write this as follows, one four. What I want control, meaning control, meaning that I would like that this goes to zero. So this is equal to one half h minus cn minus one half h minus cm square plus h minus cn minus cm square. The opposite, yes, sorry, plus, plus and minus. Now, this is a minimizing sequence. So this converges by definition to one half the distance, because it is a minimizing sequence. So h minus cn, as m goes to infinity converges to the one half the distance between h and c. This is as n goes to infinity. And this for the same reason for as m goes to infinity converges to one half the distance c. Now, we observe that c is convex. And therefore, this cn plus cm divided by two is just a combination, convex combination of two points of c. So cn, cm both belongs to c, which is convex and this belongs to c. This belongs to c. This implies that this is the distance between h and one point of c. So this is h minus cn plus cm over two is the distance between one point and one point of c. So this is surely larger than the distance. It is clear this, is it clear? Therefore, when I put the minus, I find that this object here, so let me go here. So this is surely less than or equal than one half h minus cn square plus one half h minus cm square minus distance square. Well, then this goes to this. This goes to this. Therefore, when n and m is sufficiently large, this goes to zero. And this shows that this goes to zero. Sorry, there is a square here. This square, sorry, here there is a square. So one half, one half minus one, this goes to zero. Is it clear? Is it okay? So cn is Cauchy. So we have used convexity of c here. So we have for the moment used that c is non-empty and convex. Still we have to use that it is closed. Now, cn is Cauchy, h is Hilbert. Therefore, cn converges to some point x in h. Now we are done. Because cn converges to x, the distance is continuous with respect to the strong convergence. So this limit is also h minus. This limit is then also equal to the distance. And therefore the distance from h to one point is equal to the infimum. So we have found a solution to our minimum problem. Is it okay? Uniqueness not yet, but for the moment, okay? Well, now, so these are equal, and this shows existence, okay? Because x is in c, right? C is closed, x is in c, and we have a solution, uniqueness for the moment, okay? So we have used closure, so non-empty. Convexity when we want to show that convex combination is an element of c and closure to know that this strong limit belongs to c, because c is strongly closed, okay? So that we have a solution. Now, uniqueness, so maybe there is a remark here. This minimum problem, no. The minimum problem dhx equal dhc is equivalent to this, to this. This is maybe home. The point is that this square from the outside of the infimum can go inside the infimum. Namely, a solution to this is a solution to this and converse, okay? Now, this function here has one property, it is strictly convex. Strictly convex on the convex set c, therefore it has a unique minimizer. We will prove uniqueness also in other ways. But this maybe is one. By strict convexity, I mean that, well, strict convexity, this is in a convex set. What is strict convexity? This is a scalar value function. So it is strictly convex. It is known what does it mean. Okay. Now, let me give you, so strictly convex. Let me give you now another proof of existence, which is not really completely self-contained. So another proof, so another proof is the following. So take again cn, let me still denote it by cn, minimizing sequence. This proof is probably more instructive than the previous one. The previous one is just magic because of the parallelogram identity. But as soon as you don't remember that there is the parallelogram identity, or as soon as you don't want to use the parallelogram identity, then you don't know what to do. I mean, that proof is perfect, but adapted to the Hilbert case. Now, minimizing sequence. And then we know that minimizing sequence means that the limit of h minus cn is equal to the infimum of h minus c in c, which is finite. Okay. This is what we have for the moment. Now, since this is finite, this means that we can assume that for any n, for any n there is a k such that for any n. Okay. So this is sequence of bounded numbers. This we can assume. Now, we also have that cn is less than or equal than h minus cn plus h by the triangular property of the distance. Okay. And therefore, also this is uniformly bounded. Because this is uniformly bounded and this is just a given number, independent of n. Okay. Therefore, there is another constant such that this is true. Now, this says that our sequence, our minimizing sequence from this, from this bound here is a bounded sequence. Okay. So the sequence cn is bounded, strongly bounded, of course. Now, you remember something that we have proven here last time, which says that bounded sets are weakly sequentially compact. Okay. In Hilbert. But this property is true in higher generality than this. But at least in Hilbert we know we have proven in L2. Okay, sorry. We have proven this in L2. So now assume that h is equal to L2, but this proof is much more general. So since this compact, weak compactness property we have proven just only in L2, we assume that h is equal to 2. So g is bounded therefore. So there exists a subsequence of cn subsequence. Sorry. There exists a subsequence in the sequence so that cnk converges. And there exists a point. And there exists a point. Let me call it x into h equal to L2, unfortunately, because of our such that cnk converges weakly to x. Now, the problem is that now there are two problems. First of all, one problem is the following. What about h minus x? So I claim that h minus x is less than or equal than the limit for sk of. So this is the following statement, more general statement. You have a bounded sequence, weakly converging to something. Then the norm is lower semi-continuous, but not continuous, just lower semi-continuous. Because your convergence is not strong, is weak. Therefore, you cannot pretend to have strong convergence. You cannot pretend to have strong convergence of the norms of the difference of the strong convergence. But at least the norm is weakly lower semi-continuous. So how to show this? Well, you take the scalar product h minus x, h minus cnk, h minus s, h minus cnk. And then you know that this is less than or equal than h minus x, by the Cauchschwarz inequality cnk. Then you know this. However, cnk is weakly converging to x. So by the weak convergence implies that this converges to h minus x, h minus x. So this converges, since the weak convergence is enough to say that this converges to h minus x, h minus x. Because this against this, so this is an element of your space, and this converges against all elements of your space. Remember, the definition of weak convergence says not that the components, but more, not only all components, but all projections on any vector of the space. Therefore, this converges to h minus x square. So the limit of this, therefore the limit of the four with what we find, we find that the limit of this is equal to this, so h minus x square less than or equal than, here there is the limit, because we don't know also the limit. So h minus x limit as k goes to plus infinity h minus cnk. Before, now h and x are different, and this implies that this implies this. So we have observed also that this converges so we have observed also that there is weak lower semi-continue of the norm, and so for the moment we are in a good shape. Now the point is unfortunately that we would like to say that x is in c, because this is just a weak limit, x is a weak limit. C is strongly closed, so it's not clear, because if you take a sequence converges strongly, then the limit sequence of elements of c converges strongly, then the limit is in c, but the sequence converges weakly is not clear. Well, this is a result that we will prove, so we have already a self-contained proof, the parallelogram proof, so that is a proof. Now I say that this is true. So general fact that for the moment we don't prove c convex in Hilbert, then c weakly, sequentially closed, weakly closed, if and only if c strongly closed. It is clear that if it is weakly closed, then it is strongly closed, because the sequence converges strongly converges also weakly. But the converse is not trivial. So this is easy, the more difficult, much more difficult, but this is a result. So if you accept this result, then you have also that c is in c, x is in c. So this proof is not self-contained because of this point here. Now, how we can conclude? Well, now we have that h minus x by just the lower semi-continuity and not the continuity is less than or equal than the limit over k of h minus c and k. But this is a subsequence of cn and the whole cn, so this is also the limit along the whole sequence, x minus cn, right? Because this is just a subsequence, this was already converging. So this was converges to the h capital c. And this is enough because this shows that we have shown the following, is this clear? So this proof is maybe more general, but for the moment it is not self-contained because of the result of strongly and weakly close. Okay. So now let us go back to our geometric intuition. So remember, so the proof is clear to everybody. The proof is okay, it's not okay, but the first proof is okay. The first proof is okay. So remember, we are in the following situation, this is h and this is our point of minimal distance. Why this? Because I am taking a strange unit ball. Maybe let me take this isotropic unit ball. But you have to think about a strange projection point. I mean you don't know how is the ball. So let us do a completely Euclidean picture, which is not the case, but just to understand. So this is x, this is h. Now there is the following result. We would like to say essentially that is reasonable to say that now, let me take a point out inside c, let me call it small c. Now I can consider the scalar product between h minus x and c minus x. So I can consider the scalar product between this vector and this vector. So h minus x and c minus x. Well, in R2, with this picture it is clear that we have a sign, there is a sign that this scalar product has a sign. Well, this is true also in infinite dimensions. So the theorem says under the previous assumptions, if x is a solution, so under the previous assumptions, the solution x of the minimum problem satisfies the following inequality. So this is, so it is inequality, why there is an inequality? Well, there is an inequality because this object c is not flat, it is not a hyperplane, it is just convex. So even in finite dimension you cannot pretend that points of c have zero scalar product. Even in finite dimension you cannot pretend to have a quality here. You are just saying that this has scalar product non-positive. You cannot say more than this. You could say it if c was a half space, but this is just convex. So you cannot pretend so you cannot have more than the inequality. Right? This is the so-called Euler Lagrange equation of the minimum problem. So when you have a minimum problem, you solve it, you find the solution and then the minimizer usually satisfies, not d e, p d e, something like that. This is the analog, usually in physics called Euler Lagrange equation. If you have studied mechanics, you know that if you have a Lagrangian, you minimize it, then you find a system of these Lagrange equations. This is the analog. So we have conversely also, maybe. Conversely, if x in c satisfies this, let me call star, this family of inequalities, then x is a minimizer. So here there is something more, because usually in calculus of variations, what do you do is the following. You have a functional, you minimize it, you find the solution and then if you are lucky, the solution satisfies a p d, or not d, which is the Euler Lagrange. That is, a minimizer is a stationary point, in other words. This is obvious. If everything goes well, it is obvious, even in one dimension, right? A minimizer is a stationary point. Namely, a minimizer, here you have zero gradient. In final dimension, ne? Here it is written something else, it is written. If you have a stationary point, then this is a minimizer. If x satisfies this, then it is a minimizer. This is completely different stuff. It is not true in this case. So why one can hope that this statement is true? Because of the convexity. Actually, you don't have this picture, but you have a picture like this. If you have a stationary point, strictly convex, stationary point means minimizer, unique. This is the principle behind this theorem and these kind of things. Convexity here is really a very strong assumption. If you now remember, if you have seen at least once how you pass from being a minimizer to writing the Euler Lagrange equation, then you make a variation. You make the so-called first variation. You choose a direction in which you do a variation. And then we have to choose the direction to vary our. So we take a number that we denoted by t, t a number between 0 and 1. And then we take, so h is given. We have h in h, outside, say. And then we have x minimizer. And then we consider the following competitor. Let me denote it by v, 1 minus t h, 1 minus t, 1 minus t times x, x plus t c. So if you want, if you are confused by this, maybe it is convenient to think, since everything actually is invariant for translations, for the moment you can think that x is the origin, if you want. Just think that x is the origin. So you have to show that the scalar, so if x is the origin, then you have to show that the scalar product of h against c is less than or equal to 0. Thinking of x as the origin. Now, what do you know? Now you are here, I mean you have, now x is the origin. And then you take a variation in the sense that you compare, you compare the value of your functional with the value that you have if you move along this direction. But you are convex. So you can move in this direction only with t positive and not with t negative. Because if you take t negative, then you go outside and you cannot compare. So I have denoted this by v, right? So what does it mean comparing now? We know that h minus x is the minimum possible distances of the form between h minus c, right? So, ok, this is an element of c, right? Because I am taking a convex combination of two elements of c. Actually, so this is v as a competitor, say? And therefore now I know that this is the minimizer. v is a competitor, is a good competitor, so I know this. Competitor belonging to c. This minimizes the distance between h and all points of c. This is one of the points of c, therefore this is less than or equal to. Ok? Maybe it is better if I square it, because then I... Let me square it, ok? Ok, so this is equal to h minus 1 minus tx minus tc, square. H minus x plus t. So h minus x plus tx minus... Correct? H minus x plus tx minus c. So this is less than or equal than this. Ok? Now I expand this square. I have the scalar product I can do. So this is h minus x square plus t square x minus c square. And then finally there is what I want to show to be non-positive. So plus 2 t scalar product h minus x. The sign is correct. Yes. X minus c. Ok? So now I can... So this is less than or equal than this. Now I can cancel this with this. And therefore I find that 2 t h minus x x minus c is less than or equal than t square x minus c square. Now t is positive. And therefore I can divide by t. Sorry. And there is plus. That is not equal than 0. Larger than or equal than 0. Larger than or equal than 0, ok? Now t is positive. And therefore I can divide everything by t. Ok? And then I find that t x minus... So I find that t x minus c. Larger than or equal than 2 h minus x c minus x. Now, because this goes on the other side of the equation. Now t is positive. It is sufficient. This is true for any t positive between 0 and 1. Let t go to 0. Let t go to 0. And you end up that this necessarily must be less than or equal than 0. Ok? So sending t to 0 plus. This implies that c minus x is less than 0. And this is our Euler Lagrange inequality. So you have to be very careful here because what you have done is to compare this distance h minus x with the distance of... You take any point in this half line, which is not a line, it's just half line because t is positive. T is in between 0 and 1. But if you fix any c, then you move a little bit inside. So between 0 and c, essentially, if x is the origin. And then you compare the distance... You compare the distance... This distance, you know that it is smaller than the distance between h and 1 of this point. But your variation is unilateral. It's only from this side and not from this side. And therefore, you cannot hope to have an equality but just an inequality. If this would be linear, then the situation is different. But then we will go to this. So there is still something missing here because there is a claim also that if a solution of the inequality is a minimizer. This is more difficult. So to take a solution... So let x be a solution of that. So let x solve star. We have to show the following that this is a minimizer. So we take the difference here. We have to show this. Actually, it's more convenient to show again with the squares. It is more convenient. So let us do this. And we expand this. The idea is we have to show this. We expand this at some moment. If you are lucky, we will use also this after the expansion in the scalar products.  Therefore, we can delete h2. So we end up with x2 minus c2 minus 2 hx plus 2 hc. Now we want that maybe we can write a equal x2 minus c2 minus 2 hc minus x2 hc minus x. Now we add and subtract here. Agree? x minus c. Yes, yes, yes, x minus c. My prefer c minus x, so I put the plus here. Now we have to use this. This is not present here, so we add and subtract. x here. So this is equal to x square minus c square. Then what? Plus 2 h minus x c minus x plus 2. So minus x plus x2 x c minus x. Hoping, is it correct? x square. So let me, let me expand this now. So, okay, yes, yes, probably is correct, yes, because then I expand this. So this is just equal to minus 2 x square plus 2 x c. C, yes, is correct, because now this everything becomes this minus 2. It's this and so it remains minus x square. Then minus c square. Then there is the object that I want to estimate. C minus x, and then there is this plus 2 x c. Okay, okay. So our assumption is that this is less than or equal than zero. So I hope that the computations are correct. I go here, it is more safe. So at the end we find that the different that we want to. So this difference is actually equal to what we have. This is by assumption is known. This is less than or equal than zero by assumption. And then there is a double product. Actually, I mean, there is a perfect square because this is a minus x minus c square, which is also less than or equal than zero. And therefore everything is less than or equal than zero. Okay. So we have shown that if a solution of the Euler Lagrangian, solution of the Euler Lagrangian equation is actually minimizer, due to complexity. Now we can give another proof of uniqueness of minimizers. If you don't like the proof that we have made before, now we can do another proof of uniqueness of minimizers. So let me erase everything, so I can erase. Therefore, now the initial problem, the original minimum problem, so x is unique, minimum problem has a unique minimizer. Unique minimizer is unique solution. So, well, assume that you have, assume that let me call x1, x2, maybe, yes, x1, x2, 2, so 2, minimum, 2 solutions, 2 minimizers, 2 solutions. Then they must solve the Euler Lagrangian equality. The statement, this, the original minimum problem, remember we have written that the statement was c non-empty closed complex, closed, there exist unique x in c, such that x minus h is equal in femon h minus x, maybe. This was the claim, given a point h there is a unique projection point nearest to c. This means that this is a minimum, of course. This was the claim, we have shown existence, we have said that it is unique by strict convexity. Now we give another proof of uniqueness of this x. Is it clear the statement? Problem, original problem, sorry. This is the original problem, this is the original problem, minimum problem. So, this infimum has a solution that is this inf is a mean. We have shown that this if is a mean and now we show that x is unique. So, now assume that you have 2 minimizers, two solutions of these two points in c. Namely, we have that x1 is in c and it satisfies h minus x1 scalar product c minus x1 less than or equal than 0 for any c. So, since it is a minimizer, we know it satisfies the Euler Lagrangian equality. Now x2 also is a minimizer by the contradictory assumption and therefore now we have also this for any c in c. So, we have this, is it okay? So, we have at our disposal now two inequalities and we want to find that at the end these are equal. So, what do we do? You see we can test, we have the freedom of testing this for any c but we know that x2 is in c. So, we can put x2 here and similarly x1 here because x1 is in c. So, this we can do. Okay? This must be true for any. So, in particular true for one of them. So, and therefore in particular we have h minus x1 x2 minus x1 less than or equal than 0 and also h minus x2 x1 minus x2 less than or equal than 0. Now, we add the two inequalities so that we find what we are adding the two inequalities we have. So, x2 minus x1, scalar product this actually minus this, right? So, h minus x1 minus x2 minus x1. Is it okay? Do you agree? No, you don't agree? Okay, so this is just the norm square and therefore this is necessarily equal to 0 but we know that this is a norm and therefore x1 is equal to x2. This implies so this is so you have now a complete proof in various ways of the result. Now, this projection on convex set is very, very useful in general in functional analysis. So, please remember and also is the base to show the Ritz isometry. But we will go through this but first let me say something on this. Maybe this is a coroll. Yes, coroll. Assume something more on c. Now assume that so let h be an inverse space and let m be something more be the subspace which is in particular convex but much more. So, let m be subspace. However, we need to the not all subspaces of an infinite dimensional not all subspaces of an infinite dimensional hyperspace are closed. Therefore, you have to add that this is closed if you want to closed. So, in particular we know that m is convex and closed non-empty subspace convex and closed. So, in particular we know that we have our family of inequalities but this is more now. Can you imagine what is it? I mean we are in this situation. Now we have a subspace. So, here there is our h. If the picture is Euclidean, really complete Euclidean then what happens? It happens that h is essentially orthogonal to m. Sorry, if you take this point here then this h minus x is orthogonal to this. Right? This is what happens in finite dimension. Or remember that this picture is Euclidean. If your ball is strange then this is orthogonal to this. Apart from this remark so this is m. So, given h there is a unique x by the previous result. We know that h minus x, c minus x is non-positive. Ok? But actually you can say much more here which is exactly the following. Then h minus x c let me use the symbol c now is equal to zero for any c. Sorry for the symbol c. Maybe we could use small m. I don't know what to use. So, this is, I would like to leave you for homework and we will do this tomorrow. I prefer to leave you this as home. This will be the first thing that we will do tomorrow. And then I would like also to leave you another exercise for tomorrow that we will do together. And so exercise, homework. So take h equal to l2 of zero, one. So we are slowly going outside the small l2 and going outside any ill-be space. Consider the closed subspace b of h. Consisting of all polynomials polynomials of degree 2. Compute the point of v m. Well, m and v are the same in this sense. Compute the point of v. Let me call it m. Consisting of all polynomials of degree 2. Compute the point of m of minimal distance from t-cube. So, you have, this is your h. This is a point in l2. Well, you want to find, so now your closed subspace consists of polynomials of degree 2. So you want to find the point the polynomial of degree 2 to this polynomial of degree 3 with respect to the l2 norm. This is the problem, homework.


Okay. I almost renamed S lady to razor. Go ahead Pete. I'm listening and all she would do was listen. She would not respond. It was really bizarre. No matter what I did, I had that little floating ball at the bottom of my iOS screen and S lady would listen and listen and listen and never give a response.  Disable Siri. Oops. S lady. Disable her. Reboot the phone and then you're going to have to set her up again and say, you know, all the 10 phrases that it asks you to say to set it up. And then it worked great again. At first I thought it was, I bought one of those little car play modules, wireless car play. And I thought, well, that's just not connecting right, but I'm like, no, it's I've got the little ball there that says it's listening and it wouldn't respond. So I thought that was the issue at first. And then I realized, no, it's every time I try to use it, it's not working. So disable Siri, reboot the phone and re re enable, reset it up and things work great. I have no idea what stray bit got in there to turn off the response. Yeah. So if you're having listening issues, go ahead. I'm listening.


With the departure of the 30 Cuban medical workers, 83 remain on island, aiding in the COVID-19 fight. More in this report. The Cuban medical practitioners deployed here to assist with the COVID-19 fight are members of the Henry Reeve Brigade. The brigade specializes in medical assistance in cases of disaster or emergency. A total of 113 doctors, nurses and biomedical engineers made up the first group that arrived in St. Lucia on March 27, 2020. They are among more than 1,000 healthcare workers that Cuba sent to 18 countries on three continents since the start of the deadly pandemic. The largest groups of Cuban medical workers were sent to Jamaica at 140. St. Lucia received the second largest at 113, and Barberos received 101. Smaller groups traveled across the eastern Caribbean, St. Vincent and the Grenadines received 16 members, Antigone-Barbuta 29, Dominica 35, Sinkits and Nevis 34, and Grenada 5. Other health workers sent to Barberos and Grenada, mostly women, are nurses. Other countries received a combination of physicians, nurses and technicians who are members of a Cuban international brigade that specializes in disaster situations and epidemics. From the Government Information Service, Lisa Joseph reporting.


It's The Cube. Here is your host, Jeff Crick. Hi, Jeff Crick here with The Cube. We are on the ground at Silicon Valley at the Anita Borg Institute Women of Vision Awards 2015, and are really excited in this next segment to be joined by a 2015 award winner, Tiffany Schlein from Webby Awards and Moxie Interactive. Welcome. Thank you for having me. And congratulations on the win. Well, you know, I don't know if I'm actually, I'm the keynote speaker. Oh, you're the keynote speaker. Do you want to redo that? No, that's all right. Okay. We like the keynote speaker. So you got to carry the whole thing. No, I mean, I'm very excited. I'm doing a new talk, which I've never done before, which I like to do. And it's all about kind of my experiences running, founding and running the Webby Awards, and I'm going to be talking about what I've learned about negotiation. Well, that's funny because we had Maria Claveon at Grace Hopper, and she was talking about helping people negotiate higher salaries. So that's a good topic. It's interesting. I mean, I'm not. I mean, it's interesting about it's a higher salary because I'm kind of getting metaphysical about like life as a negotiation, like every, if you think back on your day, you've negotiated like 20 times and some strategies that I've learned about negotiating. And I kind of, from the beginning of when I was a young child to today. So I'm excited because, you know, I do do a lot of speaking and for me to tackle a new talk and really try to understand it and present it in an engaging way. I use a lot of images in my talk and video and so I'm excited about it. But that's funny because I would imagine... It's like a talk premiere. It's a talk premiere. If you ask most people if they're good negotiators, I'm just guessing that most would say probably no. And yet you're saying that we negotiate over and over and over all day long. And I think if people think about it, it'll probably become less scary when they're in a situation where they don't feel confident negotiating. And there are situations where I mean, where I get nervous. It's not like I know everything, but I've learned strategies along the way that have made it better. And I am a filmmaker and make a lot of films, but so much of filmmaking is also being a business person.  And I think those skills are equally important, especially for women. I mean, there's a lot of women in the audience tonight. I think we need to be asking for more in general. So give us a couple of tips for the folks that aren't going to be in the keynote tonight. Some of the things you're going to share. Or can you? It's a little top secret. Okay, I'll give you one that's kind of deep in the talk. And at my film studio, we call it the love sandwich. Okay. Now the love sandwich can be applied to any situation when you're giving critical feedback on something or in a high level negotiation with millions of dollars. So here's how it works. You start with love. You tell the person what they're going to get. Then you say what you need. And then you end with what they're going to get. So it's a love sandwich. A lot of people go into a negotiation like I want this, but that's all wrong. You have to start. What is that person going to get? And so you have to kind of create a love sandwich in many situations, but that's my negotiating tip for today. Well, that's a good one because it's interesting. Positive coaching alliance, who's all about helping youth coaches, sports coach or kids and stuff have this very similar concept in terms of the criticism sandwich where if you're trying to give somebody advice, criticism, no, I forget what they call it, but it's the same thing, but it's lead with the positive, come in with what you're actually trying to communicate and then come out with the love. People just, everything is received better, negotiations, feedback, everything is better with love, basically. Okay, so this is a huge techie conference. It's all about CS. So what does filmmaking have to do in negotiation with the tech side? I have spent my life very engaged in technology. I founded the Web U Awards, and I spent my life looking at how the good, the bad and the potential of technology. So I love being in a space and a room full of people that are thinking about these ideas. And so I think just as someone who's studied and experimented a lot with technology, that's where I'm coming from. So you've obviously got kind of a social angle. You study people, you pay attention to people. What's kind of your perception in terms of everybody walking around like this now? And kind of how that's changing the dynamics of communication. I mean, I'm going to talk about this in my talk tonight too, but I was so worried about what you were saying that about six years ago, my husband and I, with our kids, we have one day where we turn all screens off and we've been doing it for five years now. We call it our technology shabbats. And it's totally changed my life because I was worried, I was like, people are not paying attention, they're just not paying attention to anything, not the people they love in front of them, not the sunset, not anything. And I mean, it's terribly unattractive to everyone's walking around with double chins and like hunchbacks and they straining the neck. There's all these things that are wrong, but mostly it's about not being present. So probably one of the best things I've ever done in my life was really negotiating with my husband, who's a professor of robotics. He's super into tech. We all are. And I was like, could we really turn them all off for a day? Could we just try it as an experiment? And it was so profound that we've now we're on our sixth year of doing it. Awesome. So tips to young women out there getting started in their career. They want to go into film. They want to go into tech.  What do you tell them? Ask for more. Ask for more. Just a big blanket. That is my talk tonight. I love it. Ask for more. It's pretty simple, right? And guess what? You might just get it. You'll only get it if you ask for more. Absolutely. Well, that's for sure. You won't get it if you don't ask. Well, Tiffany, thanks for stopping by. Good luck on the keynote tonight. Thank you. My premier talk. I'm sure it'll be fantastic. We won't watch it. Unfortunately, we'll be doing more interviews. But that's OK. We'll knock it out of the park. Thanks for stopping by. Tiffany here with Jeff Frick here on theCUBE at the Anita Borg Women's Division Awards in Santa Clara, California. Thanks for watching. Thank you.