Thanks, Lee and thank you everybody. It's an absolute pleasure to be here and especially to be able to talk about the weather Which is one of my favorite things to talk about Not just the weather. I'm also going to talk to you a little bit about the future But before I do let's talk about the past. It's it's autumn now, right? It's the first first few days of March, which means summer is over and some of the data is in Here's a quick wrap-up of what we saw for summer behind you and Overall, Australia saw the sixth warmest summer on record Rainfall was not too far from from average. We were 2.6 percent below the average. That's averaged across Australia again I have the the top map is the mean temperatures So that's the average of the maximum and minimum temperatures averaged then across the summer to see How we ended up and what parts of the country were especially warm And I also have the rainfall deciles before that for the for the three months of summer So what's been driving our climate? Why why do we get the ups and downs that we get and why has our Winter spring and summer been the way that it has and probably the biggest reason that I'll flag with you is El Nino Which most of you've probably heard about by now Here I've got this the latest sea surface temperature anomalies Across the Pacific Ocean. This is for the week ending the 28th of February and that big area Does this have a laser pointer on it? Yes So this area across the Central Pacific that's very pink on this map This is areas where the ocean temperatures is warmer than it usually is for this time of year and this is This feature of warm water is what we call El Nino. We like to watch the oceans and ocean temperatures because they change Relatively slowly in comparison to other atmospheric features or atmospheric features that we have So it gives us a bit of predictability about what the upcoming months and seasons might look like by watching changes in the ocean We have This region in the Central Pacific we call it the Nino 3.4 box You know with a name like that that a scientist named it that Really doesn't mean anything except that it's this area in the middle of the Pacific and we average the sea surface temperatures there And we use that for an index of how strong El Nino is and I have the time series of how this has progressed up on the top left And the ocean temperatures are peaked in about November and have started a steady decline Back to more average or neutral for this time of year temperatures And so that's that's the progression of El Nino Everything in the shaded region is it is areas where the temperature of the ocean has exceeded a threshold that we've set to help us diagnose El Nino events The ocean temperatures aren't the only thing that we watch for when we're measuring this this slow change in our climate variability We also look for an atmospheric pattern and the the one that we look to most often is the southern oscillation index which is The essentially it's this the difference in the mean sea level pressure between Darwin and Tahiti which I've labeled as stars on this map and When we get a strong El Nino you get more low pressures happening over Tahiti and more high pressure over Darwin There's an old saying that what goes up must come come down And that's really what we're measuring the air over this central part of the Pacific is rising into the upper parts of the atmosphere It spreads out and it has to come down somewhere and it's coming down over northern Australia so we take the difference of the sea level pressures there and it gives us this southern oscillation index and I have this map or this time series of where that's been tracking recently and It's still even though it has a lot of wiggles in it. It goes ups and downs just like all the rest of us It's been in the El Nino territory for a while And I want you to remember this southern oscillation index and what it is and and how we can use it because I'm going to come back to this later on in my talk But before I do let's keep talking about the sea surface temperatures These are model forecasts for the ocean temperature in that Nino 3.4 box The white line is what we've observed All of these other very colorful lines are different models that run a similar projection forward But give us slightly different answers the dotted lines are our history so that's the the pink dotted line is the 97 98 El Nino the Yellow dotted line or the orange I suppose is the 82 83 El Nino and we can compare. How is this El Nino? Behaved in comparison with recent El Nino or recent comparable El Nino's and they all are giving us While not an exact answer some idea of what might happen in the future that as we look forward to about May or June We crossed this El Nino line into neutral territory And then beyond that we have three models in the La Nina space by July or August With all of the rest of the models in a neutral space So when you have the question of well, we're in El Nino now what comes next? This is the best guidance. We have to give you now that three out of the Seven models are saying a weak La Nina is possible. Whereas four of those seven are saying that That that neutral a neutral condition neither El Nino nor La Nina is possible We use the ocean temperatures to give us that bit that predictability because they do change slowly But we've got a bit of a problem that I'd like to raise with you and that's that the ocean temperatures have been changing so here here I have just a snapshot of January's ocean temperatures around Australia and These dark orange areas are places where the ocean is warmer than it's ever been on all of our records going back at least to the The late 70s when we've had good satellites to measure these things and using that same data We have a time series of how ocean temperatures have progressed not only using satellites But also using ship tracks ship measurements and boys across the Indian Ocean To give us an idea of how the ocean temperatures across the Australian region I don't label the region. This is just this Australian region on this time series How those have changed over the last century and the oceans are warming So here's the problem are we if we're using the oceans to try to predict the future But the oceans are now like we've never seen them before What does that tell us about our predictability of what's to come and how variable our climate is going to be? That brings me to the climate outlook and I'd like to take you on a bit of a journey about how we predicted climate variability Over the last several years and we'll start in June 1989 for those of you who remember June 1989 And a few big events that happened that year or that in that month was the Tiananmen Square Massacre in China Ghostbusters 2 was my new favorite movie and and the Bureau of Meteorology released our first Seasonal outlook and it was a little different than the seasonal outlooks. You might see today. Now. This is it It was issued in June for the months of June and July and it was it used the southern oscillation index as a predictor Which I've talked about already and it used just April and May and it found which parts of it with it The climatologist at the Bureau found which parts of Australia correlated well with rainfall and the SOI with a correlation coefficient of at least 0.4 or higher and With that correlation they were able to make this prediction of what the next two months We're going to look like and these were the only parts of Australia that we provided a forecast for because that was the only places that we had confidence in this outlook for and From there things improved quite rapidly. I'm not going to go through all of these But these are all of this step improvements that we had in our forecasting methods from 1989 until 1997 and What I will point out with all of these is that they all still used the southern oscillation index as the predictor of rainfall across Australia So it's basically using the El Nino pattern and the atmospheric response to that in October 1998 we took a Step forward in our technology of predicting rainfall We stopped looking at the atmospheric response and we stopped using the southern oscillation index alone and we started using Sea surface temperatures similar to what I showed at the beginning of my talk on the top I have a thing called SST 1 which is sea surface temperature 1 and on the bottom is sea surface temperature 2 SST 2 Remember that that'll come up again in a few slides But these are temperature patterns across the the oceans that we knew Or that we still know how Rainfall across the state Australia responds when the oceans look like this So the top one is a very well-defined El Nino pattern. The bottom one is warm Oceans off to our west coast and what we what we did is we had a statistical model that compared the The sea surface temperature patterns at the current or at the time with with these sea surface temperature patterns and using Mathematical methods empirical orthogonal functions, which will not be on the test. We were able to Basically compare how how do how do the current oceans compare with this and what does that mean for rainfall? And we were able to use that as a predictor This was also when we were able to issue our forecast two weeks before the next month Which was another step forward in our our predictability Going forward a little bit farther. We had we came to February 2000 which was the first time that we issued a forecast for minimum and maximum temperatures So I've got minimum temperatures on the left with all of these beautiful rainbow colors and maximum temperature on the right And this this was the first seasonal temperature forecast that we were able to give so at this point We're getting rainfall max and min temperatures in our forecast still using a statistical correlation with ocean temperatures to provide that outlook In September 2010 we took a little bit of a change again instead of using SST 1 which I showed earlier We began using the Nino 3.4 box as a predictor in its place that box I drew on the earlier slide We still use SST 2 in the Indian Ocean But we were able to show that using just that Nino 3.4 as a predictor gave us just a little bit better skill in our outlook So we started using that then and Then let's come to 2013 the dawn of a new era is what I labeled on the slide I'm probably making that a little bit more dramatic than it needs to be but it's a little bit fun in April 2013 was the last time we used a statistical model to forecast the climate variability for the next three months and Beginning in May 2013. We started using a dynamical model or a physics based model Which takes in initial takes in observations as an initial condition and runs the physics of the atmosphere ocean ice soil vegetation all of the physics that come into play in our climate runs that forwards for several months and Looks at how the how how will the climate be changing it just for the next three? What sort of variability can we see from that? and There was something else. I wanted to say about this, but a little bit a little while later the next year We used this new model. Oh, I remember what I was going to say was that this was the dynamical model is called Poemma, which is the predictive ocean and atmosphere model for Australia And it had been in development for almost a decade up to this point at which and it was when we were able to measure It had measurably better skilled in this statistical model is when we we moved over In August 2014 we updated our services in our website Of new a new and much improved website. It was interactive. It had more explanations. It had some monthly It provided monthly forecast in addition to the three monthly forecast It also had explanatory videos on it and it was mobile and tablet friendly and it was a It was a great step forward in addition to providing odds of being above or below the median rainfall or temperature It also provided a few other probabilistic Tools so the first one on the left is an outlook scenarios where you Can tell you you can say that I'm not really cared. I don't really care about the rainfall If there's only like a 25% chance that's gonna come let's look at the 75% chance mark And how much rain am I likely to get above that and it will give you that answer on the left I have a chance of at least where you can flip that and say I want to know How likely is it that I'm gonna get my 100 millimeters for the season or something like that and you can change that around They're all probabilistic based forecasts and for good reason too There's a quote by Wilkes who wrote a book about statistics and he said probabilities is the language of Uncertainty and none of us really know the future. Do we it's quite uncertain We take a model and we run it 33 times every week and we can overlay three weeks to get a 99 member ensemble Model outcome and they're all telling us something a little bit different and we can use that model output to give a probabilistic forecast But what are we supposed to do with a mop with a probability? What is a probabilistic forecast and how do you use it? Let's consider stacking a roulette wheel for a minute if we could If they're an equal number of red and black squares and you were to make a bet It wouldn't really matter if you picked red or black because there's an equal odds of landing on red or black But what if we were to stack the odds toward one or the other and we were to say there's more red than there are black You're not guaranteed to land on red But the more that you gamble the more likely you are to win if you keep voting or keep betting red every time So a probabilistic forecast is one That that predicts the odds of something that's going to happen here. I've got another example where we really stack the odds very high There's a 80% chance of red only 20% chance of black. We you can still land on black There's a 20% chance that could happen But I'd still I'd still recommend you you bet red with that because the odds would be in your favor and the more that you Bet the better off you'll be so what are you supposed to do with that? What do you do with a probabilistic forecast? Instead of red or black, let's switch that to above the median or below the median Here's an example from several years ago where the model was telling us that there was a 60% chance of having above median rainfall in southern WA, but what does that mean? It means that if you were if you were looking at a roulette wheel There would be 60% of the squares would be wetter than normal whereas 40% would be the drier normal than normal squares and So that's how you're supposed to use these probabilistic forecasts They're supposed to help you analyze the risk and understand how likely an event is going to be Although it doesn't guarantee that that event will come to fruition So with all of that in mind, I was going to show you the most recent climate outlooks. These were released only a month Oh, I'm sorry a week ago on the 20 27th of last month. No, that wouldn't have been right 25th These are the odds of exceeding our median maximum and minimum temperature with maximum on the sorry maximum on the left and minimum on the right and the the model is telling us that across the tropical north and Around the far south far south coast odds are favoring warmer than normal conditions for the next season for the autumn season This is looking at March April and May whereas This is that's for both maximum and minimum temperatures Whereas across the middle of Australia, there's nearly equal odds of exceeding or not exceeding the mean the medium This is now rainfall and we're able to break apart rainfall into the two next months And then the next season the three-month period odds are favoring drier than normal conditions across the tropical north in March and Odds are slightly in favor of drier than normal conditions across the south for the same month with near equal odds across the center when you look at April odds are Increased toward what are the normal conditions across the south sort of the eastern end of the Great Australian Bight I've had some discussion with people asking is that forecasting an autumn break and it's I'm not gonna say for sure because this is a probabilistic forecast remember But it is likely that we'll see that autumn break in March at least that's what the model is telling us Then you can look at the three months together together to get an idea of how likely you are to exceed your median rainfall for For the season below each map I have little green maps and these are these are hit rates. That's it basically a Measure of how consistent has the model been if we say that we have more than a 50% chance of exceeding the median and We really did exceed the median in that spot for that time then that would be a hit But if you didn't then that would be a miss We're able to run the model backward for the last 30 years to get an idea of how often we We hit or missed and we're able to show that statistic in these green maps where green is good and the white is not as good It's places where the model is essentially missed So what's next in the space of seasonal forecast? We want to understand the climate. What's what do we what do we see on the horizon? Well, there have been two major developments over the last year that Are interesting and will provide some great skill for us. The first was in the July to any 15 release of the Agricultural competitive white paper. There was Granted to the Bureau within that three point three million dollars for improved seasonal forecast You may have seen a media release from From minister Joyce about a month ago about this very thing so This is giving us the three point three million dollars to help us improve the seasonal forecast to give us better skill And a better service in addition to that we've received some government investment into a new super computer and This will be the new computer will become will come online later this year The the current system that we're using was last updated in 2013. It had 104 teraflops The new computer will begin with a 1600 teraflops and with a planned up upgrade in 2019 taking us to 5,000 teraflops And if you had to if you don't know what a teraflop is it's up here. I had to look it up It's big. It's how many How many calculations the computer can do every second in a teraflop is a trillion calculations, so This upgrade will give us five thousand trillion calculations per second. And what does that mean for? What does that mean for our seasonal outlooks? Well with with both the the infusion of funding and the better The improved super computer we're able to develop a new seasonal outlook model We're calling it access s which is an acronym for something the a is for Australia and we're life acronyms So the old model is poama 2 and the new model is going to incorporate some aspects of poama 2 as well as some aspects of the UK Met Office seasonal model and with both of these together We're going to be able to increase the model resolution from 250 kilometer grid to 60 kilometer grid and With with this higher resolution the the big step forward is we'll be able to better Resolve Australian topography, so things like the great dividing range and Mania Will now be will not be picked up in the model Just because we have a higher resolution. We're able to pick up that higher grid In addition to being able to resolve the topography better We also are able to pick up observations better. This is just an example of Australia of Across Australia the August mean rainfall in millimeters per day I have the observations in the middle with the old poama 2 model the one that we're currently using on the left and the new access s model on the right and you can see how well the new model is able to pick up the fine detail and on the Observations of rainfall that we have across Australia We estimate that this increase of resolution alone will increase the skill of our model by at least 10% In addition to the improved model will also be able to provide improved Services a few that that I'd like to point out Our goal with all of this is not just to have a shiny new model We want to provide you with the best information that we can possibly provide you and when you need that information So a few things that we're offering Pushing too many buttons is some tailored information for and briefing for your business and that includes training so if any of you are interested in Tailored briefing for your business. You can come and get a business card from me later And I'd be happy to talk to you about Taking some information that's just right for you. We can also provide a webinar service This is a screenshot of me providing a webinar If you have people spread out around the country and you'd like us to provide some weather and climate information to them directly We can provide that for you. We have informative videos and of course the new services will be mobile and tablet friendly We are promising to deliver a more accurate model and with the new model We'll be able to fill in a few of the gaps that we currently have so our weather forecasts end After seven days, but our climate forecast doesn't pick up until the next month And that gives you this gap between seven days and about four weeks that you really don't have any information to work with Well with the new model and the new improvements We're going to be able to fill in those gaps with some multi-week Forecasts and weekly updates of those to be able to fill in that gap during that very crucial decision-making time What else is possible? These are these are things that we could do but currently aren't Currently are not planned to do but there are things that we certainly have thought about in if resources allow We would like to go down this path and the the first one is providing other weather elements Rainfall and temperature are great But a lot of people want to know about things like humidity and evaporation Extremes when we're going to get a really hot spell come across the new model because it's not a statistical model It has all of this information in prison Intrinsic it's already built into the the physics of the model and they're there We just need to be able to pull them out and package them up in the right way This is my summary slide and it is identical to a handout that we have at the Bureau of Meteorology Booth if any of you want to take this summary slide back to your office with you with these improved Outlook detail on it come by the the booth and pick this up To summarize I'm gonna leave most of this for you to read, but I'm gonna tell you what my vision is Of our new of our new model My vision is that someday in the not too distant future probably beginning in early 2017 with rollout several months Following that is that a farmer will be able to go to one website and look at Forecasts exactly and exactly in line with the decisions that that farmer needs to make I'll be able to look at the day-to-day weather forecast to know if the rains are going to come How much and and where the winds will be and how much temperature will be? We'll be able to go and look at seasonal Sorry the multi-week forecast to be able to make strategic decisions about purchasing fertilizer and putting things down before a big deluge of rain or Protecting the crops against a massive heatwave. That's about a week and a half away We're able to look at the seasonal forecast and be able to make a strategic decision about what crops to plant over the next season because It will be good accurate information at the seasonal time scale And he'll be able to go to one spot and get all of that information and be able to make the decisions that he or she needs from that I'll leave it at that. Thank you very much


10. For the second consecutive fiscal year, St. Lucia is on course to register double-digit GDP growth of 18.1% in 2022, a marked improvement when compared to the 12.1% GDP projection in the previous year. Prime Minister Pierre has successfully nursed St. Lucia's economy from the sharpest GDP decline to the second-best-performing economy in the entire Karakom region. 9. For the first time since 2010, the national unemployment rate dropped to 19% by the end of 2022 and youth unemployment declined to its lowest levels in 13 years. 8. More than EC, $130,000 was disbursed to six St. Lucia entrepreneurs and business owners during the first official check-hand-over ceremony under the newly-minted micro-small and medium-sized enterprise MSME loan-grant facility. The government has demonstrated its understanding of a major challenge faced by our MSMEs and it is addressing this issue via financial inclusion. 7. The recent donation of equipment to the Opikos Seamos Farmers Association and Seamos Farmers in Salons Bay is a tangible demonstration of the government's commitment to this burgeoning industry of drying tables and flotation devices, essential tools that will help them maintain proper standards and elevate their Seamos farming operations to new heights. 6. The meeting of stakeholders within the Sphere of Food Safety and Policymaking was held at the public service training room in April. The consultative session focused on food safety legislation informing and directing policy and strengthening food safety systems. 5. Fellow St. Lucia, as we move into the final term of the 2022-2023 academic year, I take this opportunity to address our stakeholders. We enter into this final term of the year with a commitment to build on the gains of last term, despite the many challenges we currently face. 4. Words of the Boy's Training Centre BTC covered its students of the new beginnings transit home have embraced the creative art of mural painting following hands-on training from artist-affiliated in the French embassy in St. Lucia. 3. St. Lucia, like other small island developing states, is working assiduously to achieve the United Nations' 2030 Agenda for the Attainment of Sustainable Development Goals or SDGs. UN Resident Coordinator for Barbados and the Eastern Caribbean, D. D. Trebek, says the UN is pleased with St. Lucia's space with SDG achievement. We have done a lot of strides in our collaboration here in St. Lucia. We have a country implementation plan that focuses on, of course, responding to the various crises the country and the region have gone through recently. 2. The Ministry of Health, Wellness and Elderly Affairs this week joins its counterparts in the observance of the 24th Vaccination Week of the Americas. This observance coincides with the World Health Organization 12th Anniversary of World Immunization Week, emphasizing the protection that vaccines provide to individuals and their loved ones, and stressing the importance for a long and healthy life. 1. Despite the rise in modern technology, Karu, who once worked as a library assistant overseas, thinks libraries still have a place in building young lives. 2. Books have allowed me to see past my reality and in many ways to manifest my future.


The only thing we really know about any of this situation is what insiders say, whether it's James Jones who says he thinks it could get fixed, A.J. says he thinks it could get fixed. And then we saw on TV, Maz Ioano broke on ESPN, the lower third said, there are people around the NFL who don't want this Aaron Rodgers situation to be successful for Aaron because they don't want the NFL to turn into the NBA where the stars get to pick and choose what they do and everything like that. Here's the thing. Here's the thing. If you're in the NFC, man, you're hoping this thing gets, it implodes and they get them traded. Every NFC coach you talk to go, what's going on with the Aaron situation? Man, I hope that thing blows up. You're sitting there going, man, I really hope they can put it together. So just be careful who you talk to. I know he still wants out without a doubt. Absolutely. Still wants out. Put it on the ticker. Put it on. Hey, Jay, we got to put it on the ticker. Hey, Jay, we have to put it on the ticker what you just said. Go ahead. Of course he still wants out. They didn't suddenly come out and insult him and go, okay, now it's fixed.


did see the video last time right, you remember now. So, given n atoms in a molecule each one has 3 degrees of freedom if you are in 3 dimensional space, 3 n degrees of freedom and then the center of mass of the molecule will remove how many? 3 of the degrees of freedom right which is the you can move the whole molecule from place A to place B, center of mass is what center of mass of the molecule is what is moving and that is not going to change the vibrational degrees of freedom. So, 3 translational degrees of freedom associated the center of mass of the molecule is not playing a role in vibrational motion. Other thing is to rotate the whole molecule if it is linear the rotation about the axis of that linear molecule will not do anything. So, only you will have 2 rotations if it is linear molecule if it is non-linear molecule you have 3 axis of rotation. So, you have to remove the rotational degrees of freedom also from the system. So, totally 3 n minus 6 where n is the number of atoms in a molecule that plays the role for vibrational degrees of freedom if it is non-linear molecule. Is that clear? Atoms 3 n degrees of freedom is total and then 3 degrees of freedom is for translations translational motion 3 for rotational motion. So, 3 n minus 6 is the vibrational degrees of if it is linear, linear molecules. So, I am looking at all these molecules in 3 dimensional space ok. So, linear molecule in 3 dimensions again 3 n to start with this one will be again 3 this one will become 2 degrees of freedom because one about its own axis it does not give you for a linear molecule like carbon monoxide nothing happens. So, the number of degrees of freedom vibrational degrees of freedom for a linear molecule will be 3 n minus 5 degrees of freedom will be the vibrational degrees of freedom. Suppose I tell you that you are in a hypothetical situation that you are going to move only in the 2 dimensional plane then what happens? Suppose I say that 2 d space is where you can move around ok then what all modifications will happen 3 n will become 2 n and so on ok. Translational degrees of freedom will become 2 degrees of freedom. Let me look at non-linear hypothetical molecule ok. How many rotational degrees of freedom? 1. So, totally vibrational degrees of freedom for a molecule with atoms on a plane let us say will be non-linear molecule what I am taking it. So, on a plane, but not lying along a line it is on some equilateral triangle or on a square, but it is just confined to the x y plane or ok. And we have seen various things pictorially or in the video. The relative motions of the atoms without altering the center of mass of the molecule are the ones where we have to also rotation does not add to the rotations. Those are the ones which is going to tell you exactly whether there is stretching, bending which are called breathing modes, asymmetric stretching, symmetric stretching you saw some of these pictures on the video. Can we understand this from your character table, projection operators, reducible representations, tensor product of representation that is the theme of today's lecture. So, assumption is you have not forgotten character table, you know tensor product, you know how to get from the reducible representation the irreducible representations. And then we will see whether we could get the asymmetric stretching, symmetric stretching all these things we would like to understand. On the plane you will have about the point rotation that is all. No, but you have to keep it on the plane you are looking at in three-dimension. Just confine that I am on this floor all the atoms are nothing beyond this floor, no going up or down. But still if I can on the plane like if particle is fixed like one can rotate like this or the other can rotate like this. No those will be the relative motions. The whole molecule you can you cannot rotate relatively different atoms in the molecule that is what you are looking for. You take the whole molecule, rotate the whole molecule, the system is intact. Take the molecule, translate the whole molecule, the system is intact. So, those two are the three, those two are the three degrees of freedom which you have to worry about for translation which is like center of mass of the molecule. Similarly, you have a rotational. See whether this works. Is that clear? Not the relative rotation. All those relative motions are like you know displacements about its mean position which will give you the vibrational degrees of freedom. It will not give you the total rotation of the molecule. If you have seen the video it is just at the axis on which the whole molecule is rotating. Not relative atoms in the molecule. Is that all right? Fine. So, now I am going to try and do a little bit of warm up on classical mechanics to tell you how difficult or how cumbersome it is to solve equations. And then I will lead you to group theory to show how simpler it is. It can work for many complex polyatomic molecules. This is the theme on which I am going to pitch today's lecture. So, this is a warm up which we did last time also for a complex system. Anyway, I have said this. There are a number of degrees of freedom and that degrees of freedom will depend on your number of atoms and all these things have explained on board. So, given that there are s degrees of freedom. So, you just take them x 1 till x s are deviations from the mean positions of the atom. So, it gives you displacements of the atom about its mean position in a molecule. So, those are what we call it as excursions of mass points. And typically you will have a Lagrangian which is dependent on x 1, x 2, x s which I put it as a column vector and row vector in between there will be a matrix. So, that this whole thing will be some kind of a number or is that right? So, you have a matrix, a column vector multiplying the matrix here, x dot is the time derivative of these s degrees of freedom and x dot transpose is the column vector. And then sorry row vector this is a column vector and this is a s cross s matrix ok. And similarly you will have a kinetic potential energy term where it is only on the positions. So, displacements of the mean positions which I call it as excursion. This is the formal Lagrangian which you can write. It will be coupled set of you know if you try to find the equations of motion for this, there will be a coupled set of second order equations to solve right. You might have done this. The only way you can make it into uncoupled equations like this is by doing a suitable diagonalization matrix and then find the basis eta for those diagonal Eigen values. Diagonal Eigen values are the frequencies. I am sure you would have done this. If you have not done it, just take a 2D or a 3D system which is coupled, try to diagonalize the matrix, find the Eigen values then try to use the matrix which allows you to diagonalize such a matrix and that will define for you the position excursions over the etas. Etas are what we call it as a normal modes is that clear? So, with this in mind let us look at an example non-linear molecule. So, I said over all transition molecule is eliminated by imposing that the center of mass of the molecule does not get displaced. So, you put that to be 0 origin. So, you have remember an example like a water molecule right. The two hydrogen atoms and this is the oxygen atom and we have this equation for center of mass of the molecule does not get displaced. So, you can determine what is I have given the bond length in the undisplaced situation as L and the angle made with respect to the oxygen molecule I am calling angle subtended by the two hydrogen on the oxygen molecule is 2 alpha clear. So, location of the center of mass of this molecule can be written down you can find that the x is 0 and y will have this sorry z I am taking this to be in the x and z coordinates. So, now rotation this will clarify your question rotation of the molecule can be eliminated by putting angular momentum about center of mass of molecule to be 0 and if you try to use these two equations you can simplify and write this constraint which has to be satisfied. So, basically what do we see? You have 6 degrees of freedom you have 1, 2 and 3 constraints clear. So, essentially how many degrees of freedom you have with you which will be the vibrational degrees of freedom is 3 degrees of freedom. So, translation and one rotation puts 3 constraints on the 6 degrees of freedom what are the 6 degrees of freedom you have x 2 z 2 capital x capital z x 1 z 1. So, I am looking at it in this the y coordinate is remaining the same. If you take this then you find that there are essentially 3 degrees of vibrations possible and we are interested in looking at the 3 degrees of vibrations. So, I am also trying to show you how systematically you can solve these situations in classical mechanics. So, that you appreciate when I do the group theory that this is doable from group theory. So, for non-linear triatomic molecule. So, we have to have which preserves are the vibrational modes subjected to these 3 constraint. So, the only motion where you are allowed the freedom of displacement or excursions of these atoms in the molecules are either the bond length this length could change this length could independently change and you can also have the angle 2 alpha could also change because of the relative displacements of the atoms in the molecule clear. So, these are the only possibilities which I can pictorially see here which may not be visible when we go to complex polyatomic molecule, but let us understand in the simplest case and map it to group theory. So, that you can believe in group theory for complex polyatomic molecule ok. So, bond length changes this is one possibility which will be 1 vibrational degrees of freedom and then you can also have the bond angle changing ok. These are the 2 possible deformations of the molecule without altering the center of mass of the molecule and rotational degree of freedom ok. So, how does bond length change? You can make this length to change for example, here which I call it as delta L 1 is the change in length of the bond length between capital M and small m for this case and delta L 2 is the change in bond length for the mass with coordinates x 2 z 2 and the capital M with x and z ok. And you can also have a rotational constraint ok. So, in fact, this is given explicitly in Landau-Liftz mechanics book in case somebody is I am only giving the final equations here if anybody is interested to derive these things you should go back and look at Landau-Liftz mechanics ok. So, the rotational deformation delta 2 alpha this is given by these changes in which involves x, x, z all the 6 degrees of freedom and the angle alpha ok. So, so far so good looking at these constraint of center of mass angular momentum being about the center of mass being 0 you can try to rewrite the Lagrangian this looks ad hoc at present, but let us just make a change of variable to a new variable q 1 which is the sum of x 1 plus x 2, q 2 is the difference between x 1 and x 2, q 3 is the sum of z 1 plus z 2 and you will also see that the center of mass of the molecule and the angular momentum about the center of mass being 0 will put in some kind of a condition here between q 1 and z 1 minus z 2. So, I am basically trying to say that if you had two coordinates you could sum up the two coordinates and take the difference they are two linearly independent objects, but when it comes here to z 1 the other one is actually related to q 1 and the angle alpha. So, it is not going to be a new degree of freedom ok, z 1 minus z 2 should not be a new degree of freedom it is going to be constrained. So, q 1, q 2, q 3 are essentially the 3 degrees of freedom which can capture the vibrations of this non-linear molecule made of 3 atoms to find the normal modes or actual vibrational degrees of freedom it could be a linear combination of 1, 2 and 3 that I am not really looked at it right now. I just made a change of variable and then I can write for this system the Lagrangian. So, the Lagrangian will have a potential energy there will be potential energy due to vibrations which involves delta l 1 squared another vibration with delta l 2 squared and that could also be a vibrational mode due to delta of the angle change ok. So, you will have those terms added into it. So, this is what I am saying you will have a spring constant solve simple harmonic.  So, they will all be simple harmonic and let us take the spring constant due to change in bond lengths to be kappa subscript l and the spring constant due to change in bond angle as another kappa alpha and in terms of q you can write the Lagrangian for the system ok. So, try and redo this rewriting it for the system of 3 masses you have 2 masses and a capital N. So, try to write it out explicitly ok and you will find that you have equations where you have a Lagrangian with q 1 dot squared you have a Lagrangian with q 1 squared sin squared alpha and kappa alpha kappa l is the spring constant for the change in bond length ok. And similarly for q 2 also you will have a piece which depends on kappa l, but you will also have a kappa alpha and so on. So, you have this what do you do next given a Lagrangian you try to find the equations of motion for q 1 q 2 and q 3 this is what you will do right. Everybody is bored looks like everybody knows. So, good if you know it is good if you do not know do not worry, but this is the cumbersome process in which a mechanic students classical mechanic student works out the normal modes in and I am sure they would have got problems in exams and for linear molecule finding the normal modes yes or no yes ok. So, equations of motion for that Lagrangian interestingly you see that this first equation is completely decoupled it has no coupling to q 2 or q 3. So, straight away from here you can read off that q 1 which was defined to be x 1 plus x 2 should be 1 vibrational mode with this frequency and again this equation has a coupling between q 2 and q 3 and this one has between q 3 and q 2. So, they are coupled set of differential equation and you know how to solve it what do you do you write the determinant you try to find a normal modes by diagonalizing such a matrix right. So, I leave it you to check this I will put this slide I want you to check because it will help you to understand the group theory way of doing it right now it is still mechanics whatever I have said. So, you see the steps I have gone through I have gone through systematically, but it is a little tedious you need to literally do these things to figure out that q 1 is a normal mode with coordinate x 1 plus x 2, but what we will see is from group theory we can actually get x 1 plus x 2 and then because we have done this hard work you can appreciate x 1 plus x 2 is a normal mode I get from group theory is that clear. So, some of the steps of math I am not going through right now here because it is not a mechanics course, but anybody is interested you can come and bother me if you are not getting in between steps, but you can look at Landau-Liffschitz and you will be able to get these steps ok. So, I am not doing the diagonalization of this coupled set of two equation to determine what are the normal modes which will be a linear combination of q 2 and q 3 and an orthogonal linear combination involving another mode ok. So, this I am not doing it now and when you diagonalize set you will find two eigenvalues the two eigenvalues are different then only you call it non degenerate right. Do you expect it to be different or do you expect it to be same for this molecule which we are looking at? C 2 v is a symmetry the character table tells you that you should have only 1 D reps. So, you better get all these eigenvalues to be different ok. It has to be different it cannot be degenerate ok. Check it out I am sure you can take this and diagonalize it and find the frequencies ok. So, three vibrational degrees of freedom will involve q 1 q 2 q 3 turns out that q 1 itself is a vibrational mode which is one frequency what is the frequency? Frequency is going to involve this factor times this one is omega square. So, this is non degenerate one normal mode or one vibrational mode which is straight away q 1 q 1 is not talking to q 2 and q 3 linear combination of q 2 and q 3 what linear combination you have to diagonalize this and find out and what are the frequencies ok. I am trying to tell you that you will find each one to have a distinct frequency you cannot have the same frequency. If you are doing other molecules like methane which was shown in the video you will start seeing if you do this rigorous exercise there will be some frequencies which will occur three times because there is a 3 D wrapped in the character or if you had a C 3 v symmetry you will get two times which is associated with the frequency should repeat twice and you should be able to find two distinct normal mode sharing the same frequency. That is why they start doing that mixing and joining together you know you remember and you can see that in the methane molecule there are three degenerate vibrational modes and they combine together and so on. When will you get degenerate comes from the symmetry of the molecule. I hope you are you know appreciating what I am trying to drive in how simple looking how complex looking where group theory can play a very important yeah. You can treat it to be a two dimension or you can also treat it to be a three dimension but then you have to remove the translation along the y direction and the rotations which is involving the other yeah I will come to it. C 2 v in the sense that this is an example of a water molecule and I know that the two I put it as two identical m's if you do a C 2 about the z axis you do see that this hydrogen goes into the other hydrogen and vice versa. It will be still if you treat the z axis to be the C 2 axis it is still true and sigma v to be like the x z plane it is still true ok is that clear. So, I am just looking at it from purely from the action of the group theory also and you can treat it like a 3 D problem but then you have to remove those I have to put the center of mass coordinate for the y also. So, basically I could have given x 1, y 1, z 1 uncomplicated the situation. Instead I thought anyway y is not playing a role with all these symmetries of this molecule I can look at it as a C 2 axis on the z axis which takes the two hydrogen atoms to each other. So, I thought it is better to confine to a simpler 2 D situation but you can extrapolate it to 3 D.


Nobody is gonna hit as hard as life, but it ain't about how hard you hit It's about how hard you can get hit and keep moving forward. How much you can take and keep moving forward That's how we did it start Look, I'm home Yo, this is what I do I told you so So other people to my home, and then we have like Group stuff together. It's great. It's great. All right. Where do we meet anytime and do it So what is this way of righteousness you're gonna teach us about? I was just getting to that. Thank you, Willie the way of righteousness is The righteous travel upon the road and And it's great. It's great. There's so much I can teach you from the Bible. I just don't know where to start You're holding the Bible upside down So I have this question is it wrong for us to kill animals because when I go hunting and I kill my deer You know, I just don't feel guilty But the Bible says that we shouldn't kill yeah It's simple like in the book of Of Makita Yeah, yeah, like in the book of Makita give us commandments that we shouldn't kill deer because deer have feelings and And we hurt their feelings. We will make them cry and And Jesus won't be happy Are you making things up? I'm not making things up. I'm a homeroom leader Reads it starts here somewhere and Matthew and Genesis you are tripping first comes Genesis then Matthew. That was the Old Testament. They changed it in the New Testament Anyways, new topic. I don't understand scripture where it says if we take up anything deadly a shot Like I don't get it. Yeah, it says that even if a snake were to bite us it wouldn't kill us. How does that even work? Thanks, I'm not belly.  Are you a real homeroom leader who will show us the truth about the scriptures? Give me I'll show you just kidding. Let's catch up


What is going on guys, welcome back to the channel and I appreciate you being here today, I am back with another Destiny video and today I want to showcase to you guys this animal other weapon and it's called the Three Graves, this is the old school dead orbit push rifle and it absolutely slays in PvP. I mean it's so good I just made it a master work version and I don't do that with weapons quite really to be honest and I got range on it as well and I got 20 kills in my last game. It's ridiculous people and it easily, it easily outgoes the vigilance wink if you start shooting, well obviously there's many weapons out if you start shooting first you'll do it but I'm telling you to me it seems like it kills quicker than the vigilance wink. I'm not even kidding you guys, it's got outlaw on it as well which really helps out, I mean it's got kind of a slow end end sight. Outlaw really does help out with the murilloes, instead of the murilloes people so we're going to get into it, we're going to play a bit of Iron Bedirana and I hope you guys enjoy it. Now if you do leave a like truly does help me out, remember guys if you have any weapon you want to see me use we're going to PvP let me know what it is down below in the comments section but let's get into it people. Now this is a range weapon people, don't think you're going to be using that close range unless your opponents absolutely shockingly bad such as me. You probably ain't going to do too well but at range, mid to long range it's quite decent it really is people and you'll see you'll witness the power of the three draves. What was hitting me then from wherever that was a post gun head was that Hilly Hilly, I didn't see that. I didn't see that. So I'm getting shot at, I can't even see it already. Anybody else want some of this? Anybody else want some of this? Are they coming from every angle? That's destroyed.  Where do you think you're going? Give me that heavy, give me that heavy. Yeah, I love you. And I need a hundred heavy kills altogether.  This map I get so confused. Love this gun, it's so good. So I'm still getting hit by some of the gun head.  I need heavy. I'm pleased.  Don't know what that was then. I don't think so, I don't think so. It's heavy in there everyone.


ᴄ ᴗ ᴗ ᴛ ᴛ ᴛ ᴛ ᴰᵇ run, WW80 ᵍᴥᵁᴉ ᴏᴶᵊ, ᴛ channel ᴇ ᴛ ᴗ ᴏ ᴛ ᴛ ᴖention 62 ᴈ ᴏʀʀᴜᴛ ᴝ ᴌʁ ᴓ, L̬ Ó W würden construction ᴇ ʀ ᴛʀ�клад ᴷ– ᴜᴜʔ ᴜʔᴎ ᴏʀ. ᴏ� rotten ᵈ ᴛʔ�龍 ᴾ ᴛʀ ᴜʔ ᴜʔ ᴛʕ ᴃʔ ᴓ and eigen the global reference centre for giving families the answers they deserve after humanitarian crisis. The activities of the centre would be to impart training, to start some educational programmes to do research in this area and see that we promote this in a big way and see that we provide these services globally. This is the purpose with which the centre has been established. With the kind commitment of Indians to institutionalising humanitarian forensics I think there is a very long and productive way to go. So, am I excited? There is a lot of anticipation and I think there is something that could come out of this in the service of humanity. We are proud of it. Disaster means it is a national calamity, not the calamity of that particular state alone. So, if such a centre is there we can seek the help at any time. That is the main importance of such a centre in India. First of all, we will be taking the curriculum for training the trainers. Then we will be introducing some of the short term training programmes which will be exclusively for the purpose of humanitarian forensic action in the scenario. I am also very excited about this collaboration because it is a little bit a model of what humanitarian assistance can look like in the future. And I think we are really entering a new era when it comes to humanitarian forensics and its action across the world in terms of bridging the operational response and the need for research and development. And I think that this centre will be at the forefront of defining the field in that respect. So, I think a very institutional response would be able to give from the Police Department. Right now, you know, it is not an institutional response. And it will pave the way for a lot of cooperation and partnership around the world. That means not only India, but not only the region but this will have a significance worldwide for the field of forensic humanitarian action. The key of the future is international networking because there are no boundaries in the forensics like this centre that will allow training, teaching, exchange of ideas and also be there to work in an international environment. This is very important I think because I never knew this was even possible. I never knew there was a branch called humanitarian forensics before. Being international, bringing all the countries together is more important. This is just the beginning. The journey has just begun. We hope that the next feedback will be that ICHF is striving and meeting the expectations and the objective for which it is set up to be a beacon of hope for families and communities that want that answer after tragic incidents.


The liars of CNN are at it again. This time, one of their DNC operative, Jim Shudo, a guy who used to work for Barack Obama as a political appointee, chose to attack Republicans as hypocrites for not opposing Trump's national emergency to secure the border. Shudo's rationale for calling Republicans hypocrites is that when his boss, Barack Obama, was president, Republicans, and specifically this Republican, opposed him in declaring a national emergency to pass new strict gun laws. Listen, you've done your homework. You've done it wearing the uniform. You went down to the border. I respect your position. I do wanna note that you, like many Republicans, when President Obama used executive authority without congressional approval, you opposed him. When has CNN or any of the other networks ever called Democrats out for their hypocrisy? Or for that matter, when has the media ever called themselves out for their blatant hypocrisy? Of course, CNN nor anybody else in the media outside of Fox News ever opposed Obama's national emergencies. I actually found a CNN article about Obama's national emergency to pass stricter gun laws, and the headline reads, emotional Obama calls for sense of urgency to fight gun violence. The first paragraph goes on, President Barack Obama grew emotional Tuesday as he made a passionate call for national sense of urgency to limit gun violence. That's a pretty far cry from what we're seeing from CNN now in regards to Trump's national emergency. If you read the article, and I'll link it in the description, there's not a single negative critique about Obama's use of the national emergency. Of course, CNN didn't oppose Obama's national emergencies, nor did anybody else in the media outside of maybe Fox News. In fact, their negative coverage was reserved for critics of Obama's executive order on guns. But this guy, Shudo, gets to operate in a bubble where he never has to answer for his apocracies or the apocracies of the Democrat Party. Luckily, Illinois Rep Adam Kinzinger was having none of it. Quote from you in 2014 when the president was considering executive action on guns. You said, time and again, the president, this being Obama, has chosen to push his authoritative agenda with little regard for constitutional process. Why is the president not doing exactly what you criticize President Obama for? Because you can't change a law on guns or immigration with the stroke of a pen. If somebody was trying to change a law, that would be a very different situation than a president saying, I'm declaring a national emergency on the border. I'm not appropriating new money out of thin air. I'm actually switching resources from things like DOD counter drug to actually fighting drugs on the border through this emergency order. As Congressman Kinzinger correctly points out, the reasons for opposing Obama's national emergencies were completely different. They're not at all comparable. Obama can't just pass laws with the stroke of a pen, especially laws that are spelled out in the Constitution. As anybody who took a civics class knows, law started out as a bill and then they had to be passed through the House and the Senate. The president's pseudo must know this, but he's using his position as a DNC operative to try and discredit Republicans who might still be supporting Trump. He wants Republicans to come around to his point of view and oppose the national emergency. These are not the acts of an objective journalist. These are the acts of a propagandist. President Trump is actually using the national emergency for what it was meant to be used for, in this case to defend our national borders. With news breaking today that in February, more than 76,000 illegals crossed our border, it's kind of hard to argue that there isn't a crisis. I mean, even the left-wing news outlets like the New York Times and the Washington Post are now admitting that, quote, the system is well beyond capacity. It's focused on things that are a threat to the American people. Is there always consistency among Republicans and Democrats? No, that's something we have to accept. But in terms of what I say and what I see, I think it is consistent to oppose a president that would attempt to change a law versus a president that would attempt to take existing resources and enforce a thing like border security. Congressman Adam Kinziger, thanks for joining us. What, he didn't have anything to say and retort? Well, that's probably because his little attempt to discredit this Republican just blew up in his face. I'm not even sure why he would attempt to make this comparison when there are clearly two different situations. The simple answer is that, that's just his job at CNN. He's a Democrat, he's a left-winger, and a former Obama political appointee. His job is to advance a DNC agenda and to torpedo any opposition. I think that's pretty clearly what we're seeing happen here. Hey, thanks for watching. Please like, share, and subscribe. If you're interested in some open discussion and debate, check out my Discord channel. You can find a link in the description and the pinned comment. Hope to see you there. Thanks.


Okay, we're back here live at the Stratoconference O'Reilly Media's Stratoconference in Silicon Valley in Santa Clara, California. This is the epicenter of big data innovation, startups, businesses, growth, a lot of competition, a lot of news happening. We're here on the ground covering at SiliconANGLE.com and wikibon.org. I'm John Furrier, the founder of SiliconANGLE.com. Join with my co-host. I'm Dave Vellante, wikibon.org, and we're here with Ed Dumbbell, who's a longtime CUBE guest principal analyst at O'Reilly Radar. And of course, for Stratoconference, one of the co-chairs of the conference. Ed, welcome back, always good to see you. Thanks, it's great to be here. So we know you're super busy, we'll get right to it. A lot of action quickly. What are you seeing? What's the vibe? What are the quick highlights from the top of your head right now, and then we'll do a drill down? Sure, well, as I said at the beginning of the show, you know, the death of big data, as referenced in that venture beat article, I'm sure you read, has been greatly exaggerated. And you know, the fashionable company is wearing a Hadoop distribution this year. Big data's dying, but yet the big money players are actually investing millions into growing the market. That's interesting, right? Absolutely, you know, the reality of it is that we're just getting started and getting down to business and finding out how to make this stuff sustainable and how to make it really work. So we talked with Roger yesterday at O'Reilly, and we talked about essentially a concept, we just kicked out a term, applied big data, and Greg Sands, who's a VC, just brought a post on it today about it. But this, we're at the beginning of now, the applications are coming in, analytics are out there, Mike Olson said a while ago, oh, it's application, but they really haven't come on. So analytics really was the only killer app and the platforms are being developed. So what are you seeing here at the show? And talk about some of the keynotes this morning, and as you put the program together, how do you make a decision between all the greatness of what you can showcase? Well, you know one of the key things for me is transferrable knowledge. So we really do give a lot of preference to people who can walk the wall as well as talk the talk. And I think Gail Garten from LinkedIn and the keynotes this morning really showed how they use a data-driven approach to their product development. And she was very insightful, had a lot of hard information about what she did. So that to me was just in a nutshell, exactly what we're looking for. So Intel brought up this user experience angle, and then when they talked about their distribution on theCUBE, and a lot of people tend not to think about that, they think about the speeds and feeds, but what LinkedIn I think points out, and what you're essentially alluding to is that there's a huge user experience component that needs to be in the design side of things. Can you comment on your point of view of that and then how companies are thinking about big data in terms of a user experience, whether it's data as code to applications? Yeah, it is absolutely critical. That's one reason we renamed our UX and Vistrac as design this year, because we think it's not just about the pretty graphic that comes out of the end, but also about the design of how you collect the data, how you iterate and work with the data. And frankly, we're at a very early stage for even understanding that right now. But I had this thing about really data being the lifeblood of a digital nervous system that we're building out because tech is everywhere now. We're kind of post this phase of instrumenting paper activities, and now we're in the situation where companies are producing 100% digital solutions in their business. And so with the data being kind of this blood that goes through, there are different parts of the body and it runs everywhere. So every time it touches people, it really matters how that's right. You have to have a good heart and don't have a heart attack. Don't have the clogged arteries. No, big data, that's a good analogy. Big data is the blood, it has nutrients, it can feed a value proposition. What we're doing is building a model, frankly. It's a big data about building a model of the world. And we start with small things like users, what they're doing on mobile apps and so on, or maybe your customers. But that really is the task which we're about to model in the world with data systems. And so the world is about people. Therefore, it's obvious that the people factors should be very important to people. You talked this morning about some of the hard problems. Last couple years we've been doing some of the cool stuff and now we're really starting to attack some of the harder problems. We were at the startup showcase last night and we were talking to some folks from Berkeley and they said, our problems we can't find problems hard enough to solve. So of course we threw at them the speed of light and they explained how they solved that algorithmically and put us in our place. So talk about, maybe elaborate a little bit on what you were speaking of this morning and maybe give us some examples of some of the problems that this industry is trying to solve. Yeah, actually I don't think that the hard problems are necessarily the algorithmically hard problems. I think they're the organizationally hard problems. How you use data in an organization and make decisions around it. But if you want to go down to the technical level and the trends we'll see. It's great.  Where did it come from? What have you done to it since? Who's allowed access to it? Is Dave the same as Dave two or Dave three? All these things that the BI and data warehousing world made some effort towards. They all still apply in big data. And if you're going to start using it for real you need to be able to manage it and track it. And they're some of the problems that the data systems need to grow up and people need to understand how to use those too. I spoke to somebody recently building out an architecture for big data and they're very large enterprise and they're saying, if you don't accompany your data with descriptions of what the fields mean, where the data come from, who touched it. It's not getting in to HDFS. We're not going to put it in. So you need to, they're the hard problems, right? How do you do it so you get best value beyond the pilot? Being able to automate that in a way that can scale. So there's also, Ed, obviously we're big in the design. In fact, yesterday we were talking about the data science piece talking about the art and science of data science. There's an artistic and creative side as well as the geeky side. But let's not forget, there's two other issues going on with security. Tim just tweeted five minutes ago, Tim O'Reilly expects some black hat. That's data scientists soon. Joe Turian also made a comment on that as well.  And Tim said that on theCUBE here. But we also just had Peter Wang on from Continuity and Analytics, which brings a physics mindset, the machine learning or I would say the instrumentation. So there's some science involved, high performance computing. So it ranges from the sexiness of design, user experience, but down to the alpha geeks of math, science, everything and everything in between. Right, so I mean, where are we? What's one side floating up? I mean, how do you view the marketplace right now? I mean, you know, you look at the range of what we've got in the conference. That's pretty much my mind, right? That we have to include all these things, that we have to look out for the bad actors.  What is spam, right? Spam is data crafted to get through a system and infect us in adverse ways and spamming email is something we all deal with. But imagine this is like that problem, but a thousand times greater. Evil genius, I just tweeted back to Tim. I said, you know, it brings back the notion of the word evil genius. And in order to fight the bad actors, we have to actually think like evil geniuses to combat that. So, you know, it's just evolution. And but with that regard, what technology are you seeing here? Obviously, besides the competitiveness thing, I mean obviously the big money players are coming in that shows the growth of the market. Big data is not dead. Venture beats really wet on that and really should rethink their editorial. But more importantly, there's tech involves, right? So you have real innovation going on, disruptive technology around databases, tools. What are you seeing outside of the competitive thing around the tech? Well, I think one of the things that is going to be important that will come out this year is an agreed data architecture, right? So great, we have this tech, we have fast streaming data in through Storm and so on online analytics. We also have Hadoop and whatnot. Where do these pieces fit together? It's a really important problem.  Yeah, we just had it. The app was just on, just in show last year for SQL Hadoop. Now EMC comes out, so again, to your point. Exactly, you know, Impala was faster than Hadoop, now we're faster than Impala. But that's really just a side show and these guys need to be working harder at building up vertical applications that people can put to use. So some of the technology is architectural in that sense. That said, I think there's great scope for companies who can apply machine learning in a way that doesn't need too many experts to really automate more of the analysis and the decision-making process. You see Eric Coulson's keynote this morning talking about Stitch Fix and the way they use machine learning and analytics to still involve humans, but make it so they have to weigh less of the grunt work and they can bring a personal touch where the machine has done most of the things. Yeah, he's coming on later. That was like IBM Watson for apparel. You know, that's such a great story, that's not bad. You know, when Tim was on the queue, we had a great conversation and we'd love to talk, as he around, if he comes on, we wanted to have him back on, but one of the things we talked about, I think last year was that the user shouldn't have to work as hard. And one of the things that was really innovative about Web 1.0 was with Search Engine, especially Google in particular, they reduced the time it takes to do things. They reduced the steps and made it elegant and simple and reduced the steps to do something, make it simple and elegant and fast. And you win. So users shouldn't have to be entering in data. So we're moving to a world of adaptiveness. Absolutely. And this is why you need to think about it vertically, right? Why just coming up with a faster map reduced now or something isn't really helping people. Frankly, I don't think it's a great business model. I think you need to look at the problem and work it back. And if you're in any doubt that the problem, you know, really affects things all the way down, you should listen to Facebook. I was listening to a talk by Jay Parikh who's their VP of infrastructure. They talk about their photos, right? You think photos go up on Facebook? Well, it turns out, you know, after a couple of hours, most of them never get looked again, they just go through the stream and then they get old. So Facebook have got these data centers where everything's replicated seven times on instant, you know, high power availability for the photos. 80%, 90% of that never get looked again, it's a total waste. So they had to architect low power racks for these, you know, what they call cold photos. They even built data centers. They built a data center just for cold photos, right? And that's all software driven. If you think the software you write doesn't matter all the way down to the buildings you're building, you're wrong. So this stuff, you need to look up and down, not just at one level. Well, this brings up a theme we brought up yesterday in the show here is performance, right? So, you know, how they do it is because they're scale, they got to do their own, they're doing open compute on the hardware side. So Facebook is really a good indicator, but we're talking about performance. I mean, that's one thing that Intel, I give them props for is they come out and say, hey, you know, we want to increase the performance and security. And so that's their approach. Yeah, that's a great announcement. You know, I think it validates for people exactly what we're doing here.  But before that, it was the chip manufacturers that were making the compilers. And if you see Hadoop as kind of the compiler of the big data space, it's not surprising that Intel would want to come out with that. IBM made a similar play with their power series about the chip helps and the fact of the matter is it's got a lot of un-chip cash. So all these kind of in-memory stuff can make much faster. Oh, Dave and I were talking last night after the show, we were commenting around the growth curve of this marketplace and it feels so explosive but you're always in a market where how much bigger can it really get? So we're really debating on where we are on the growth curve. If it's going exponential and going straight up, are we in the bottom of the curve? Because right now it feels like it's going up but we don't even know where we are on the bottom of the curve. So I want to ask you, where do you think we are on the curve?  You know, we're reporting that it's early. We're saying top of the second inning. But what's your take on that? You know, I totally buy the top of the second inning thing. And that's why I talked about architecture being very important. We don't have an accepted general big data architecture right now. And that's going to be one of the things that will really unlock growth where people know where to put it. The second thing is when people know a bit more about how to use it and their business and their organizational structure. So I agree, top of the second. One of the things we brought up with Intel and this is Dave and I were trying to tease this out and we're trying to get our arms around it but it's not so much Intel. First of all, it's validation. I agree with that 100% there. But it's not Intel competing with other people. What they're doing is they have interests in the data center. They have the interest in the internet of things. These are all instrumentable devices that have data. So it's not so much big data is about analytics. It's a huge range of use cases. And you know, if you think the battles between Hadoop distributions, that's not really what big data is about or where the opportunity is. It's frankly, I'm a little bored of the bickering between the Hadoop guys and I'll say it to their face if they come up to me. It doesn't look good. And it's not really helping the problem that we're trying to solve. So, great, more of the merit at this level. I'm bored about Hadoop battles. Let's look at the next level up.  I mean, there's a whole new security model needs to be put in place. Well, value creation, we were teasing out today saying, hey, we had Green Plum on a particular, well, we'll name names. We say, hey, look at, you know, be aggressive, put a stake in the ground. But remember, you're in the data warehousing space. It's a bigger world out there. And the point is, there is a lot of value creation on the table. There's not, you don't have to fight for scraps in a growing market. Well, to Ed's point about business value too, and we, ironically, we keep on, we size the market and we still got a little vendor revenues. That's fine, but so much more value is being created by the practitioners than is being created by the vendors, which is, you know, we asked Michael Dell about that at Dell World in the company. He said, that's always been that way. But in a way, in our industry, it has it.  You don't see those kind of massive valuations exploding in more, okay, Apple notwithstanding, but so much more value is being created, you know, within the end user community. So it's interesting, I think there are three places that it's really good to be in this market. First one is down on the metal side, right? Yeah, right. Cloud are making metal, making chips, great. You know, the second one is at the data side. If you data owner, then you can really turn that into business value. The third, I think, where there's value, and this is the difficult one to tease out, is around the interaction of data with people. So this is the analytic tools, the group ware tools. I was saying, one of the most important things that we're creating is an agile data platform. And the best of breed I've seen is enterprises building right now. They're building something that enables their staff to get on and do their job without asking permission, without going around a three month BI cycle to get a new report up, without having to requisition kit from IT. And so that's where the users are really going in there, building the agile stuff out. One thing I... You talked about that this morning, starting off with smart data and agile data, where the two sort of examples that you gave, that's right out. For businesses, they want to make the smart use of the data, not just reports, they need to understand it's a lot more to have big data than reports. And for the IT side of the house, you need to be creating infrastructure that enables your colleagues to be agile. Yeah, one thing we find, we obviously we track the IT market pretty aggressively, and it's evolving from decades of consolidation, cost reduction now to an enablement model where growth is on the table. And so there's a lot of transitions going on, but we were joking this morning, we were on a tweet chat with IBM throughout the notion of data as code. And then we just said, hey, what do developers do with unstructured data? Because data quality came up. And we were talking about, there's no one data mart anymore that you can have a data mart that evolves into multiple data marts, integrate third party data marts, so the data mashups. So that was one concept. The other one was shadow IT has really enabled some innovation, even though it's been kind of don't ask, don't tell, you're seeing enterprises saying, hey, let's do the innovation, it's been the R and D, okay, let's adopt that. So we talked about shadow data. So the data equation is different. I want to get your point of view on this because the question is, companies have to store the data. There's also compliance issues and legal issues. So there seems to be a shadow data market emerging. And what do we should take on this? Well, this is really the hard problem I was referring to in my keynote remarks. Finding the data, keeping track of it, making sure people don't do too much duplication. I think there's this kind of, as you say, this iterative cooperation between the IT organization and the rest of the business needs to be in play.  They can't do that. But as vendors, there's a huge opportunity for the market to really take advantage of some web technologies. What is the web, right? But a large shadow data network where you don't know where everything is, there's things multiple places. All that stuff, you can turn inside. You can use search, great. And here's my controversial bet, all the stuff that's been built up with the semantic web technologies over the last 10 years, and people go, ah, that's a failed project. No, it's a 20-year project, we're year 10. And a lot of that stuff about cataloging and organizing things is going to be very important. It enables that, you're right. You've seen it with Google now, the knowledge graph, they know it's important. Someone who figures out how that can work in a scalable way in enterprise, it's going to be a very happy person. Well, we're trying to do our chair on that with our little tools that we're building. But again, add your thought leader, final comment here on the show. Obviously doing a great job. You guys run, this is an amazing show and certainly it's going to have a lot of legs. Final comment, what are you expecting for the rest of the day, the next two days? What are you looking forward to? How much sleep have you had? You know, have you checked email at all? You know, I'm just very happy. These three days make it all worth it, you know, like throwing a party. I'm just impressed people's energy and their imagination. I love the data stack spot I pub into the expo hall. And it's just great to see everybody coming together and recognizing this is a place where work can be done. And Dunnville program chair here at Strata. He runs the concert with Alistair Crawl. Fourth show, I believe, right? This is the fourth one. You know what, this is our third seven part. It's our seventh Strata all together. Seventh Strata. We're looking forward to doing a memoir with you guys, great show. Stay here on siliconangle.com for all the exclusive coverage with O'Reilly media. This is theCUBE. We'll be right back with our next guest for the short break.


Okay, welcome to our practical approach to one thing and one thing only today, menisci. So I'm starting out with exactly what I said I wasn't going to do, a slide. You know, this is not meant to be didactic. It's meant to be an interactive experience so that you really understand how to talk about, not talk about, menisci. But I have to have some just basic framework of anatomy and here it is. So I made this simple diagram and on your left is a kind of a broader half circle and on your right is sort of a tighter C-shaped circle. The one on the left happens to be the medial meniscus, your left. The one on your right is the lateral meniscus. This part of the meniscus actually attaches down into the screen. That's called the root ligament. We can't see that. But this is the meniscus root. Here's the front root. There's the back root. And then the rest of this is the anterior horn and we'll keep it simple. The front third is the anterior horn, the middle third is the body, the posterior third is the posterior horn. Once again, these are the roots attached by ligaments. The menisci are also attached out peripherally by the capsule. Some tighter than others. In fact, the medial side has a tighter attachment than the lateral side. That's why it's more prone to certain types of menisco-capsular injury. And the same rules apply here. A third, a third, and a third for anterior horn body and posterior horn with attachment on the outside. Now on the inside, the free edge of the meniscus is not attached. It's like the wing tips of a manta ray. It's just floating and synovial fluid and sometimes it'll get a little bunched up or squished. And when it does that, it looks a little funny, especially when there's synovium. That is the normal phenomenon and pitfall known as meniscal flounce and we're going to see it. Now the meniscus is also divided up into thirds. An inner third, a middle third, and an outer third. And in every meniscal tear, we want to comment on that because the tears that occur here, you should almost never ever operate on. They're all going to heal well enough on their own, better than they would do if somebody manipulated them or cut them out. The ones in the middle, kind of maybe yes, maybe no, but usually not surgical candidates. The ones on the inner free edge, those are the ones that are more likely to require surgical intervention. And these areas are also known as the red-white zone in the middle, the red-red zone on the outside, and the white-white zone on the inside in orthopedic parlance. Now this next slide, and this will be the last slide before we go into cases, demonstrates the meniscus in cross-section. And you might have noticed in the last slide there are some different colors in there and I don't really care about those too much. But the bottom line is within the meniscus there is specialized anatomy that conducts synovium from the joint to the outside. So there is a pathway of flow, I can draw it for you, see if it'll let me. There's a pathway of flow that goes this way. Notice it goes right along this purple and yellow anatomy and that persistent flow along these bands of collagen that live inside the meniscus represents the normal intraminiscule signal, which you now see is not present in the inner third as depicted by this purplish area. It starts around the middle third depicted by the yellow and then kind of breaks off into two bundles, one here and one there. It kind of makes like a little fork or a couple of bunny ears if you turn it straight, right side up, and those bunny ears are normal. They should be relatively faint. They should never be equal to or brighter than a highland cartilage. They should never go all the way back to the capsule. They should never go up and down. They should never have complex character. They should have exactly what I've drawn here, this gently sloping character. Now, a lot of your colleagues will refer to these signals in different ways.  And each one of these has an appropriate setting where it's to be used. But let's give an example. You're fresh out of training and you call the signal in the meniscus in a 32-year-old otherwise healthy girl that just ran three miles meniscal degeneration, but the rest of her knee looks fine. Why in the world would you use the term degeneration? She has no DJD, her meniscus is of normal size, she just ran three miles. It is a silly term to use in that setting. Or if I hear degeneration in the 13-year-old, what 13-year-old has a degenerated meniscus? Nobody, except maybe somebody with a discoyed meniscus, this is silly stuff. This is like saying, let's give all the banks any of the rules they want. That's silly stuff. Let's stop doing silly stuff. And your job, your primary job is to save the whales, save the menisci. The slightest amount of trimming in the meniscus changed the knee dynamics forever for that person's entire life. It is a total game changer. So the worst thing you can do is call something that is not there.


Why your hard work doesn't lead to your success? Our forefathers were hunters-gatherers. The men hunted animals while the women gathered them. They were also nomadic. They had to move from one place to another to hunt and to pick their foods. About 10,000 years ago, however, for the first time, human beings made a great discovery and that was that we can actually grow our foods and so we started growing our foods. Prior to this era, our fathers had to be extremely strong physically because they woke up every day to fight with animals, many of which were wild animals. They also had to protect their family from the predictors so physical strength was the number one thing that mattered. No, things didn't change when we became farmers because farming was still hard work. Though we can now stay in a place and build ourselves some homes, we still had to work extremely hard to teal the land, plant and nurture our foods. Soon after we started settling down, we noticed that we will need leaders. These leaders will have to lead us, put things in order and defend our village. Not against the wild animals alone, but against our fellow humans from the next village. So these kings have to be strong, they have to be warriors. Again, the physical strengths were the only thing that mattered. Because we didn't sleep, we started inventing tools to make our works easier. We invented cutlassies and holes to farm and arrows and swords to fight. Now we have technologies to make our works easier. But don't be deceived, it was still not as easy as you would imagine today so physical strength was still the most needed skill. About 200-250 years ago, however, we discovered even more advanced technologies we could use to farm. Now we have tractors and other technologies that could allow a few of us to produce the food for thousands of people. We call this the agricultural revolution and it should make us work less. But again, right in the corner was an industrial revolution. We now discovered how to mass produce everything. The smart guys among us created the industries and every one of us had to work there. Though you needed a lot of brain power to build a company, you don't need 1% of such thinking to work in the industry. Just show up and be part of the machines. Again, it's about physical strength. It was around this time that we figured out that we must make public education compulsory. Not really because we cared about giving education to people but because we wished to train them to be machines, to work for our industries. We wanted them to work in our industries and because the industrialists were rich and powerful, they influenced how the school was structured and what you can learn there. You really won't learn anything except how to obey others. Some experts agree that the mid-80s was the end of the industrial age and what does that mean? Well, that we are no longer in the agrarian age means that we no longer need your physical strength to farm. That we are no longer in the industrial age means that we will no longer reward you for your ability to work 14 hours a day in physical labour. What is the implication of this? Very simple. If in the 21st century, your strengths were physical, we've got no market to reward you handsomely for it. Yes, we can give you a job and employ you to be part of the machines we use, then pay you a token to keep you alive.  This is the number one reason why most people are poor, even though they work very hard. The world has changed. You just need to get this right. The world has changed. We are no longer where we used to be, so we do not appreciate what we used to appreciate. Take for instance when you were a baby. Your favourite gift could be candy or toys. Today if I give you these two things, would you appreciate it? Probably no. But why? Because you've moved on and you can only appreciate something else now. So it is when you're trying to offer the old service to the new world. You get it? That's what school taught you to do. That's what the society taught you to do.  What the new century wants? Now the market no longer appreciates the strong bones. What the market is willing to pay for now is the strong brain. Stop being physically hard working. Start being mentally hard working. Here are some real life examples. How much physical work do you think it took to build PayPal? Maybe some hard work at the beginning but that company was sold for $1.5 billion after 3 years and about 6 months the company started. Can you work hard enough to make $1.5 billion in 4 years? Facebook was invented about 16 years ago and today it is worth over $100 billion. Can 100,000 people work hard enough to make $100 billion in 16 years? YouTube was sold to Google in less than 2 years it started. It was sold for $1.65 billion. Can you work hard in your entire life to get such money? Above are a few obvious and big examples but they are not the only examples that exist. All over the world, there are millions of people who are making good money by using their brains, not their bones. I know what I'm talking about. I'm running 3 businesses. I don't do the hard work. I employ people who are trained to do the hard work. My work is to think and create. That's the only way to be rich in the 21st century. Stop living in yesterday. Stop being in the 19th century. Stop thinking that hard work will make you rich. Napoleon Hill wrote arguably one of the best books on money. Hill did not call that book work and grow rich. Even though he published the book in 1937, he called that book think and grow rich. The key word here is think. Henry Ford built one of the biggest companies in his generation. When he wanted to give advice, he didn't say that hard work is the secret of success. Thinking is the hardest thing therein and that's why most people don't do it. Thinking that's the hardest work of the century. But as Ford said, most people don't do it. Some helpful tips If you want to be a creative thinker and become rich in this age and time, I suggest you do the following. 1. Consume a lot of creative and educational materials. If you like reading, read good books. If you love videos, watch meaningful and educative videos. If you like audio, listen to helpful and challenging audio programs. This is important because your mind is like your body. You have to feed your body nutritious meals to make it healthy. You have to feed your mind with healthy meals to make it healthy and functioning. 2.  This will be offensive to some people because everyone thinks that they are using their brains but that's not true. Think. Ask questions. Be curious. Challenge that status quo. Let your brain work and it will work better each time. 3. Spend time with yourself. Ours is a very noisy world. We are busy with work and even when we leave the office, the social media is waiting for us. Because of this, we don't have time to be with ourselves. Just as you can't know other people until you spend time with them, you can't know who you are if you don't spend time with yourself. 4. Hang around creative and positive thinkers. You are not you. You are your friends. If you hang around people who don't use their brains, you won't use yours. In the past, what determines whether you'll be rich or poor is how much of physical energy you have. Today, the game has changed. It's no longer about bones, it's now about brains. Thank you very much for watching our videos. We'll like to give you another interesting video for you to enjoy next but before then, our team will be very happy if you can like this video and share it with your friends on social media. If you're new here, don't forget to subscribe so you won't miss other interesting videos like this. 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