It is spring and the harsh winter months are finally over. This is the time for all the birds to return from the tropics and meet their friends. Ah, you are back, Tweety. Long time, Daddy. How have you been? I'm good, I'm good. So, where are you coming from? Oh, you know it. India. India. Again.  Oh, I just love it there. Love it? Really? You've got to be kidding me. I've heard there are just too many of them there. A billion or so or something like that. Yeah, yeah.  Look at that. Those seeds look so thin now. Oh, hold on, Daddy. You need to get your fats right. Well? You need to go to India to know what's happening there. Really? This is the time of year India is most vulnerable to being hit by cyclones. Sealing at least three people uprooting trees and telephone towers and damaging buildings and power lines. Jamun Kashmir has not had a natural disaster on this scale in living memory. This is the worst floods that's hit the state in the last six decades. India's roots, her land, her people are being jolted more than ever before. It's been described as the Himalayan tsunami. Days of heavy monsoon rain have swept away roads and buildings. Thousands of people are still missing. The flood situation in Jammu and Kashmir is very grim and steadily deteriorating. The number of dead in the floods has reached 148. In Srinagar, while the average norm for the 4th of September is less than one millimetre of rain, almost 52 millimetres of rain or 77 times the average took place. One fury after another. Thousands of lives snuffed in moments. Millions displaced. But science says, hold on, there is more to come. The impacts of climate change pile up in the extremes. Extreme high temperatures. Extreme droughts. Extremes of intense precipitation. And extremes associated with high sea levels. In Uttar Pradesh's Hamirpur district, devastated after his standing rubbish crop was lost to the rain, Indrajit committed suicides in his own field. Economists call it the tragedy of the commons. The rich countries that industrialised first overused the atmosphere as a dump for greenhouse gases. It cost them nothing. But the price of their mistake committed over centuries is now being borne by people all over the world. Especially the poor, who have done nothing to cause climate change. In 1992, at the Earth Summit in Rio de Janeiro, all nations of the world, 178 of them gathered to correct this mistake. We have been the most successful species ever. We are now a species out of control. All countries signed the United Nations Framework Convention on climate change. The rich countries agreed to take the first step to reduce their greenhouse gas emissions and further promised to enable poor countries to fight climate change by extending funds and technology. But these were empty promises. Twenty conferences have gone by. The world is expecting us to reach some kind of agreement concerning climate change and not just continuing discussing procedure, procedure, procedure. The rich countries have neither reduced emissions nor have they delivered the billions of dollars they committed to support poor countries in their fight against climate change. I was born in 1992. You have been negotiating all my life. The fact is in Rio there were two parts of the agreement. They will reduce. We will have the space to increase. The second part of the agreement was they would give money and technology so that when we develop, we can develop differently. Now if you look at what has happened since Rio is, annex one countries have not reduced at the scale that they should have. And I'm talking about all annex one countries, including Europe. Okay, okay, I got it. You don't have to go on and on about it. You just love to take up the past, isn't it? That's not true, Teddy. I don't agree. I don't agree with that. Sure, there must have been some oversights, some goof ups. But now these guys in India are making the same mistakes all over again. I just don't get it. Yes, of course you won't get it. Because you really can't look beyond your nose.  Hold on, hold on. What's wrong with that? It's a blessed way of life. It is very... Blessed way of life. Blessed way of life. Your blessed way of life needs five planets. We just have one. A blessed way of life lived by the developed countries has obviously come by spending a good fortune. Science calls it the carbon budget. If the world has to limit warming to no more than two degrees above pre-industrial levels to avoid catastrophic climate change, then it has a limited budget of carbon dioxide to emit. 2,900 billion tons from the dawn of the industrial revolution at the end of this century. Two thirds of this budget has already been used. The United States, the European Union, Russia and Canada together have emitted 50% of the carbon dioxide during this period. In comparison, India has just emitted 2.8%. At the current rate, the world will effectively finish the entire budget in the next 20 years. Leaving nothing for the development needs of the future generations. Let's talk about the United States in particular, which till date has occupied the maximum carbon space and how. America is addicted to oil. The US per capita coal consumption is five times higher than India's. An average American consumes 34 times more electricity than an Indian. In 2013, an American household purchased items 44 times that of India. 86% Americans drive cars in comparison to 10% in India. 40% of total food in America goes uneaten. Currently, India's per capita emissions are at 1.7 tons of CO2, while America's are at 16.5 tons. With its much celebrated climate commitments by 2030, the United States will reduce this to just 14 tons. Whereas India, with its most elevated trajectories, will still remain below the 2005 global average of 4.22 tons. Whatever happened to the promise of equity? The United States became the economic powerhouse of today simply because it emitted and therefore developed economically. But in that, it used more than its share of the global commons. Now, just like financial debt, you should be calling this the natural debt of the United States. The developed world used cheap energy to develop. It meant that there were emissions and they've occupied a large part of the carbon space. Now, when we want to provide our people with energy, there just isn't carbon space for the emissions that will result from the greater use of carbon. The C-word of consumption has to be the climate word as well. Because unless we discuss consumption and we make the American lifestyle negotiable, we will not be able to combat climate change. Let's now look at the inconvenient truths of some other rich countries. Compared to India's per capita emissions of 1.7 tons of CO2, the EU emits 7.2 tons, Russia 12, Korea 12.2, Canada 17.6. So this is equity in the real world that while a few rich countries continue to guzzle energy to live an addictive lifestyle, nearly 1.6 billion people globally do not have electricity. 300 million of these live in India alone. Their children study with an oil lamp. Millions of women here inhale toxic smoke while cooking on open fires. One third of Indians live in extreme poverty without shelter, education or healthcare. They suddenly deserve a better life. With such unfinished tasks at hand, India is investing her scarce resources to adapt to climate change, protecting its glaciers and coasts, making watersheds, building early warning systems, preparing communities for disaster management, training farmers to be climate resilient. India has a lot to do. It needs more carbon space. It is already too late for her people. I get your point. What? That everyone has a right to a good life. Exactly. But then if everyone starts living that life, then I have no hope. It's just going to get worse here. You know, that's the trouble. You're getting old and cynical. Just because a few folks had a party by blowing tons and tons of carbon into the air, it does not mean that it's the only way to go about it, huh? In India, the sun is revered as God. In thousands of far-flung villages that are off the grid, this God is literally helping to light up homes. But for a country where 300 million people still live without electricity, even the God can only do as much. This is Charanka. The rows go on as far as the eye can see. With an installed capacity of 600 megawatt, this is Asia's largest solar park in the Thar desert in India. But because of the limitations of solar technology, it operates at an efficiency of just 22%. Given the scale of India's energy challenge, Charanka is just a drop in the ocean. In Jaisalmer Rajasthan, the wind is turning the turbines of one of Asia's biggest wind farms with an installed capacity of more than 1,000 megawatt. These are some remarkable islands of hope that make up India's current green energy portfolio of 6%. By 2030, India has the potential to take this up nearly four times to 23%. But high capital costs, remote locations and lack of evacuation facilities make green energy costly. So who would bear this high cost eventually? So that cost has to be borne by a common man because in India, industrial tariffs are today the highest in the world. We cannot go on increasing the tariff for industry. They can definitely bear, but then there is a limit, which means that finally we will be looking at common man has to share additional burden. The common man in India is already burdened. Given his average income, he pays one of the highest electricity tariffs in the world. He cannot possibly carry further the weight of global expectations to use green energy. Today, 25% of Indian households do not even have access to electricity. A very large number do not get adequate electricity. So our goal is as quickly as possible provide adequate and affordable electricity to all. Now we are also greatly increasing our renewable energy capacity. But renewable energy even today is more expensive than for example coal energy. As we move ahead, if we want to accelerate the amount of renewables we have, it would imply both financial support as well as support in the transfer of technology for effective acceleration of the renewable energy program. In 2007, the government launched an unprecedented program called HAT, or Perform, Achieve and Trade to transform energy intensive industries in India. Nearly 478 heavy industry units were given specific targets to reduce their energy consumption. The idea was unique. Those units who outperformed their HAT target would be rewarded with energy-saving credits, which they can sell to industries who underperform. Across the spectrum of top energy-guzzling industries in India, HAT has already exceeded the target of 6.7 million tonnes of oil equivalent of energy savings. HAT has been very successful. It has focused on large energy intensive industries who have the capability and the capacity to invest in enhancing their energy performance. But there are millions of smaller units where hand-holding is required, where technological solutions delivered to the door are required, where adaptation of existing technologies are required for them to be meaningful to the small size of these industries. Honestly, all this is fine. I mean, it's not bad. Thank God. But you know it's not easy. You know these guys in India need help. Help? Like what? Well, if your friends lived up to the promises they made, a billion people in India are waiting to change the game. It has been promises galore. In 2010, the rich countries accepted that they would pay poor nations to adapt to the problems caused by climate change. They pledged that by 2020 and beyond, they would pool in 100 billion US dollars every year towards this purpose. This was called the Green Climate Fund. The headquarters of the United Nations Green Climate Fund has opened too much fanfare. The developing countries waited for this pledge to be honoured for the next four years. In 2014, the rich countries gathered once again for yet another round of pledging. I'm delighted with the outcome of today's pledging conference. Close to 9.4 billion dollars of contributions make this the most successful climate finance mobilisation. But eventually, high promises met with closed purses. Pledges need to be promised and to be converted into actual cash. And the signed commitments to date are about 5.3 billion dollars. That's all we have. 5.3 billion dollars that's going to be spread on an average over nine years. Typical project commitments. It doesn't go very far with 130-plus countries, if you think about it. Not even to speak of the scale and needs. So that's where we are with the Green Climate Fund. And it's a long, long way off from the US dollar 100 billion a year. The dishonesty is glaring. And it is often innovative. Here's another one from the OECD countries. So the OECD, as you know, is a club of the rich countries. Just like good clubs, we all want to belong to it. But not necessarily this one. The interesting question is, is these projects really about climate finance or retroactively or retrospectively you just called anything and everything under the sun? Climate finance projects. And when you actually look at the number of specialized climate funds, what is the amount? It's less than 2 billion dollars a year in disbursements from 24 specialized climate funds since inception. So 57 billion dollars, claimed OECD, actual neutral source, much more credible, 2 billion dollars. The ice melts back dramatically, exposing more... As these gimmicks play out on the world stage, climate science is screaming with new evidence. In September of 2012, Arctic sea ice shrank to its lowest extent ever measured in the satellite era. Britain's weather agency says the world has warmed one degree Celsius since pre-industrial times. Scientists are warning the planets now reached a grim climate milestone not seen for two or three million years. As time runs out, the scars of climate change are becoming uglier. But it is only ironic that when it strikes, disasters do not differentiate between borders, ethnicities, or even the GDP of nations. Hurricane Sandy crashing on shore winds now at 90 miles per hour, and this storm is so big, so vast, 60 million Americans will feel its power. Will feel its power. Will feel its power. Oh my God! I haven't seen so much disaster ever. Yeah, you haven't seen much anyway. Just because you travel, you think too much of yourself, Tweety. Anyway, I'm done. I'm hungry. I'm leaving. Your choice. But it's not about you, me or these seals. It's about all of us. We are in the same boat. It's about our planet. It's about our children. Teddy, are you listening? This was not the first time Teddy and Tweety were having this argument. For over three decades now, each time Tweety returns from India, Teddy listens to her stories, agrees, and then goes his own way. Nothing much has changed, except that the ice around is melting faster, and the seals are getting thinner and thinner. Alex, what countries wake up and smell the coffee? It's high time that the developed countries put their money with their power.


So, welcome to module 5 of point set topology course. Last time we introduced the notion of epsilon delta continuity on metric spaces showed that it is equivalent to sequential continuity. That was a major result last time, so today we will use that and see a number of examples basically. So, here I have stated a theorem which is again using sequential continuity. So, first of all you must see what happens to sequences of functions, sequences inside k power n. So, that is the first theorem here. Consider k power n with the Euclidean metric which I have denoted by d 2 u e and I am just recalling it here instead of x and y I am writing u and v does not matter that is what you must be able to do. I range from 1 to n modules of u r minus v i square then take the square root.  So, I am putting a superscript here this is sequence in k power m. So, I have changed this n here that is why I have put m here now it is in k power m. So, this formula is two for all n after all right. So, I have to I cannot fix that one this n I am better I use for sequences.  So, there are m of them m tuples of numbers here real number complex numbers whatever. So, let us say n tuple is a vector. So, it is a sequence of vector. So, this is a notation. Suppose this sequence converges to you under this metric and that u I can write as u and u 2 u n plain vector then and then only. So, this is if and only if each coordinate function here u i n converges to u i less than equal to m 1 for all n okay 1 2 3 up to m okay. So, each coordinate function converges to a point you take corresponding vector that will be the limit of the entire sequence here which is what it is. So, just like a sequence of complex numbers converges different only if each real part and imaginary part you get two sequences both of them converge. So, that has been generalized here for any k power n okay.  Then what does it imply u n epsilon positive choose a k V wrong between such that p because any k implies distance between u p and u is less than epsilon. What is this distance? This is the square root of the sum of the squares okay. So, that immediately implies that each thing here must be less than epsilon because the square root of this whole thing is less than epsilon. The square will be less than epsilon square. So, each must be because these are all positive numbers each must be less than epsilon square. So, square root should be less than epsilon.  So, you have finished the same p we will do the job for all the sequences okay.  So, that is the meaning. Now, conversely you have to work a little hard that is why I have put it here. Conversely suppose each of them converges the coordinate functions given an epsilon I should not produce a k such that this happens now right. So, what do I do? First of all what I get is for each sequence I get a k i belonging to n such that p is bigger than k i will imply modulus of u p i minus u i is less than something at something I am choosing not this epsilon but epsilon by square root of n. Apply it to the convergence for this number okay. So, this happens now you choose k to be the maximum of all these k i. So, I have reached for each i I have a k i take the maximum k i.  So, all of them will be true okay. You take the square that will be less than epsilon square by m. Take the summation there are m of them so it will be less than epsilon square when you take the square root you will get this one okay. So, I have I have not written down then I have asked you to check this one but I have told you how it works alright. So, as a corollary what we get is you get the projection maps pi i the coordinate projection k m to k okay.  How do you get continuous?  So, that is what we have proved already. So, this is a part of corollary here part of that theorem you do not have to use if and only if just one part. So, coordinate functions are continuous okay. Now, we will improve upon this fine. Take a metric space take a function from x to k power m any function in the product is the same thing as giving you m functions an m tuple of an m tuple of functions f1 f2 fm right.  So, condition is if and only if each coordinate functions each of them is continuous okay all of them are continuous. So, how do you prove that same thing start with sequential continuity usually that is easier than finding epsilon delta and so on. Take x n tends to x in x now put u n equal to f of x n then you apply that theorem okay u n i will be what it will be fi of x n all right. So, you see sequential continuity helps you once that is why we converted this epsilon delta thing here into sequential continuity in this one okay. So, so that was the the theorem that you had proved last time. So, you can apply that a function is continuous if and only if each coordinate function is continued.   Therefore, from our theorem to 1.20 the statement of this corollary reduces to the case when n equal to 1 by taking the coordinates okay. But once you put n equal to 1 this is nothing but the theorem 1.20 which you have stated last time since we have only stated and not proved it actually we said that you must have done it in your real analysis course and so on. In any case for completeness let us prove it now okay. Yeah consider the function first the addition which I denote by alpha right k cross k to k given by alpha of x plus x comma y is x plus y. To prove the continuity of alpha at any point say x naught y naught given epsilon choose delta equal to epsilon by 2. Now suppose this x y is in the ball b delta x naught y naught remember what is b delta of x naught y naught is all points x y is a set their euclidean distance from x naught y naught is less than delta okay. In particular if you look at the modulus of x minus x naught is always less than the euclidean distance of x y from x naught y naught because this is nothing but the square root of the sum of x minus x naught square and y minus y naught square. So it will be smaller than individual one square and then take the square root. So this is always true which we have used earlier also similarly y minus y naught is also less than delta right. Therefore what we get is alpha of x y minus alpha of x naught y naught will be less than what is this one this is nothing but the x plus y minus x naught plus y naught which is x minus x naught plus y minus x naught. The modulus will be less than equal to modulus of x minus x naught plus y minus y naught each of them is less than delta. Therefore the whole thing is less than twice delta which is epsilon okay. The proof of the multiplication continuity of multiplication is slightly more complicated okay. So let us go through that so I want to prove this multiplication scalar multiplication is continuous at x naught y naught right. So given epsilon I want to choose a delta appropriately. First of all look at x naught y naught take the maximum of the two okay add one call that number as 1 m m means maximum of mod x naught mod y naught plus 1. Then choose delta to be the minimum of epsilon by 2 m comma 1 okay. I would like I want it to be less than epsilon by 2 m but I also want it to be less than 1 that is why I am taking the minimum of the two okay. Now suppose x y is in the delta of x naught y naught as usual then I want to show that alpha of mu of x naught mu of x y minus mu of x naught y naught is less than epsilon that is what I have to show okay. So as before we have the moment x y is inside this ball x minus x naught modulus and y minus y naught modulus both of them will be less than delta. Moreover now x minus x naught less than delta implies more x itself is less than more x naught plus delta and this delta is less than 1 right so this should be less than m okay so this is less than m. So if you put all these things together what you get is now mu of x y minus mu of x naught y naught modulus of that is modulus of x y minus x naught y naught we rewrite it as x times y minus y naught plus x y naught minus x naught y naught add and subtracted. So this is modulus of x times y minus y naught plus modulus of x minus x naught times y naught okay and that is less than or equal to m times epsilon by 2m plus epsilon by 2m okay that m times comes out both for both of them here this is for y naught and this for x so so this completes the proof of theorem 1.20 that we are stated earlier and along with that the corollary 1.24 is also proved okay so we have the this very important theorem here I have just written corollary that does not matter okay. So as an example of application of this one any polynomial map p from k to k what is a polynomial map polynomial is something like c naught plus c1 x plus cn x power n where c1 c2 cn are scalars right so I want to say that any polynomial map is also continuous constants are continuous the first thing I wish to use that applies scalar the x going to x is continuous identity map so multiply the two of them that will be continuous which means x square is continuous multiply again that will x cube is continuous that means all monomial functions x going to x power n they are continuous so now we can add two of them at a time so c naught is continuous c naught c1 times x is continuous c naught plus c1 x is continuous and so on finitely many of them you have to add that will be also okay we can go one step further namely any polynomial map in any number of variables finitely many x1 x2 xn going to summation c alpha x power alpha mod alpha is less than or equal to d this is the notation if d is 0 this is just a constant that is no choice if d is 1 you can take x1 you can take x2 you can take x3 and all monomials of degree 1 you can take if you degree 2 then you have x square x1 square x2 square all of them not only that you have xi into yj sorry xi into xj so those things will be also there so how to write all of them it is a notation here take n ed which is a positive integer look at all multi indexes alpha which a1 a2 a n they are all integer non negative okay n two poles of integers because I have n variables here okay some total of these must be less than equal to d that is what you are putting the restriction because you want take only finite sum that is all okay then what is the meaning of this x power alpha it is one single notation for x1 raise to a1 x2 raise to a2 xn raise to an so that is the notation summation of all a1 a2 a n that is less than equal to d I write as mod alpha less than equal to d so mod alpha is this one this is like your taxi cab metric here okay and all these c alphas they are inside k they are coefficients they may be r or c more generally any field will do but we are concentrating only on real or complex numbers so such a polynomial is also continuous why because first of all all the xi's are continuous this is what we have proved so x1 into x2 x2 into x3 or x5 square and so all of them are continuous multiplying them by a constant they are continuous then you have to take the sum so instead of one variable you have one more namely here namely all you have to take various xi's and then take the product not just one x and its one power okay so that is all the differences so this is again the argument is similar that will give you all polynomials whether one variable two variable and variable they are all continuous functions okay to be sure you know that they are also differentiable functions right in fact they are more than that they are much more than that they are analytic functions and so on there is one more notion which you want to recall once again from function of one variable real variable or complex variable the definition is exactly the same again this time again you replace the modulus by the distance function that is all take a function from one metric space to another metric space it is called uniformly continuous then uniform continuity is defined on the entire set a there is no point in defining at a single point okay I can define it on some a a continuous x1 also that is possible but now here I am defining for over x1 so it will be true for any subspace is also okay so a uniform continuous function is defined for the entire domain here okay whatever domain you have chosen for the function so what is the definition for every epsilon positive you must have a delta positive such that whenever the points of a domain you know they are closed by delta d1 of y1 x1 is less than delta their images must be also satisfied that same relation but with this epsilon d2 of fx1 fy1 must be less than epsilon so you see there is no reference to given x given x and epsilon there exists delta was the definition for ordinary continuity at a point so there is no reference here this delta will just chip in upon epsilon it will serve the continuity for all points at all points in particular uniformly continuous functions are continuous also you know ordinary sense that is easy okay indeed I have not said anything other than replacing the modulus by delta on the d1 and d2 so you must be all familiar with these things okay so for instance what is the difference between ordinary continuity and uniform continuity in both the definitions this delta will depend upon epsilon okay but in the ordinary continuity it also depends because you start with x for each x and epsilon there is a delta so it may depend upon that x also okay in the uniform continuity there is no starting point at all you do not have to it starts with for every epsilon there exist okay and then the statement is for all points all pairs of points therefore uniform continuity implies continuity there is no problem okay but we will see some examples here that in general uniform ordinary continuity function may not be uniformly continuous so first example is the simplest example namely x going to x square okay you must have checked it if you haven't you should check it right now all right doesn't take much time not uniformly continuous means what again you have to do so given epsilon there existed delta that is the condition right for all t should happen so what is the negation of that there is some epsilon just that no matter what delta you take somewhere something goes wrong that point you can choose freely here that is the point because there is no for every given x x is not a fixed starting point or anything okay so you can take any number one for example and then show that there is no such delta which will give you the continuity for all the points that is what you have to show so having told that much I will leave it to you the same thing with t going to e power t is not uniformly continuous okay on the other hand closely related to that is the the the trigonometry function sin and cosine they are uniformly continuous okay I don't want to reveal there are tricks to see why they are uniformly continuous I don't want to reveal that to you right now you think about them all right if you have problems with this gun you should not hesitate to contact us on the platform namely the discussion form is there okay so there you can ask I tried this way I tried this way but I am not getting it okay please explain so our t s will explain that so let us look at another example here namely tangent and cotangent functions okay they are also not uniformly continuous so this time the domains are finite domains here but but the co-domains are the whole of minus infinity the entire of r okay so entire of r these these are actually homeomorphisms 1 1 mappings here but they are not uniformly continuous okay so uniform continuity is something somewhat funny thing it is not a topological quote end quote topological property at all so in topology you won't much see it at all in general topology there is no uniform continuity concept to bring it you have to do something like a metric space not exactly something like metric say what are they called they are called uniform spaces okay because they can they can have uniform continuous functions so you may you may have many functions which are continuous but not uniformly continuous but look at the look at the thing here it seems to have something to do with the domain and co-domain okay so indeed you have also studied in your real noise course namely every continuous function on a closed interval is always uniformly continuous okay so though I have given you these examples of not uniformly continuous functions if you restrict them to any closed interval they will be uniformly continuous the emphasis here is is not uniformly continuous whole of r similarly equal to equality is not continuous on the whole of r that is the point if you restrict it to close intervals they will be continuous that is one of the theorem that theorem namely a continuous function on a closed interval is uniformly continuous that one we can extend it in some sense and that is that that comes back in topology also definitely in metric spaces later on we will do that so here is one example which you might not have seen in your analysis course at all because this is about metric spaces take a metric space take any non-empty subset okay so the layman's language of distance I am going to use that so I am going to take arbitrary points and then talking about the distance of that point to the set okay so that is what d underscore a of x or d of x comma a whatever notation you want to use you can use so this is defined as infimum of all the distances between a and x where x vary x is fixed at a varies over a look at all these these are all positive or non-negative real numbers okay take the infimum why this is infimum makes sense because this is bounded by 0 below so infimum means at worst with the 0 or it may be some positive number it makes sense this infimum is called the distance of x from a okay so that is the notation d a of x or d of x a this function you can easily check that it is uniformly continuous you do not have to hunt for a delta it is there I will give you that a hint so write down the details yourself okay any doubts we will stop here until next time thank you


Humans can hear up to 20.000 Hz and then only when they are young and unable to afford a good stereo. So why high resolution audio files? Are they snake oil or real audio quality? Not only humans are limited to 20 kHz, most studio microphones are too. There is only a very limited number of microphones that can clearly go beyond 20 kHz and they are normally not used in recording studios. Those big Neumann tube mics even roll off from 13 kHz while all great voices of the past and present are recorded with them. I know there are theories about intermodulation products above 20 kHz but given the level of high frequencies in music, tens of dBs down and the fact that intermodulation products then would be even tens of dBs further down, I think they would not be relevant if they existed. So am I saying that high-res music files are fake? There are many people hearing quality improvements when they use high-res files. Are they right? But let's first see how high-res files are produced. The only way to produce high-res music files is to record them in high-res, for instance in 192 kHz sampling 24-bit depth. Not much of a problem for modern studios, almost all produce in Pro Tools, a digital audio workstation that can record, edit and mix many tracks at that resolution. Still often albums are produced in 44.16, the CD format. The reason for this is simple. Producing in high-res takes considerable more storage space. Recording in 88.224 bits takes three times the storage space compared to 44.116 bit. 192 kHz 24-bit even takes 6.5 times the storage space. Since studios are commercial enterprises as well, they need to charge their larger storage media to the client, in most cases record companies. And it's down to the client to order and pay for the higher resolution. Many of them find MP3 already good enough to make money on. Luckily there are those that do appreciate that they can charge extra for high-res, leaving the consumer the choice. And then there are artists that are in a position just to demand high-res, although they are low in numbers. Another high-res option is to record in DSD, which is usually done using merging technology's pyramid digital audio workstation. But since digital processing in DSD is not a feasible option, it is mainly used for classical music and other music that can easily be published without processing. Editing, pasting pieces together can be done on a pyramid. Then the music around the editing point is converted to DXD, which is 352.8 kHz 24-bit PCM, spliced together and converted back to DSD64. In some cases DSD recordings need to undergo processing like EQ or Dynamics and then the entire file is converted to DXD, processed and converted back to DSD. So apart from the specific and costly recording gear you need for DSD, storage too is more costly than CD quality. By now you might wonder why I tell you all this, for I just told you that the extended frequency range high-res gives you is neither needed nor audible. Well, that is because in audio things are never as simple as they seem. And this all has to do with the filtering needed in digital recording. It is a well-known fact that prior to recording audio digitally, it needs to be filtered at half the sampling rate. So for CD quality a filter has to take out all signals above 22.05 kHz. Normally 20 kHz is taken as a filter frequency that leaves a space between 20 kHz and 20.05 to filter 96 dBs deep, for that is what 16-bit depth requires. I have mentioned in earlier videos that this implies a filter steepness of 96 dBs per single note. Normally filter steepness is expressed in dB per octave, which is 7 whole notes. So we are talking about 672 dB per octave filtering. That is an extremely steep filter and will have severe impact on the sound quality. But there is a solution. Most analog to digital PCM converters use the Sigma Delta method at a very high sampling rate, resulting in a low-bit signal that is then decimated down to PCM at the required sampling rate and bit depth. This way the initial filtering can be very mild given the extremely high sample rate. In the decimating process, where a low-bit signal of 1 to 4 bits is converted to either 16 or 24 bits, the filtering to half the PCM sampling frequency can be done in the digital domain and given sufficient DSP power, this can be done rather good. DSD converters use the same Sigma Delta conversion at one bit depth and simply register the raw DSD data, so there is no decimation. During playback PCM files have to pass the reconstruction filter. Depending on the working principle of the DAC in use, that filter can be analog, partly digital and partly analog or non-existent. Non-oversampling DACs, often abbreviated to NOS DACs, use fully analog filtering after the conversion but might even skip filtering at high sampling rate. Depending on the manufacturer, the filter settings can vary between strict and very loose. Strict filters do 96 dB from 20 kHz. Loose filters start at a somewhat lower frequency and roll off more gradually, which gives a better phase behavior while, when chosen wisely, will not produce audible aliasing products. With the emphasis on audible. Upsampling DACs work differently. Here the digital signal is first upsampled to a higher sampling frequency. In this process the digital signal has to be filtered at half the original sampling frequency too, but this time it can be done digitally. And after the conversion to analog, only a mild analog filter is needed given the now higher sampling frequency. Most modern DACs work this way where the actual conversion can be done with a ladder converter but is usually done with a Sigma Delta converter. Also, here the digital filtering can be done with a linear phase brick wall filter. On paper these filters look almost perfect. There is no phase shift and thus they are called linear phase filters. But they do produce pre-ringing, meaning they will generate sound before the real sound starts. This can be brought down from about 10 cycles pre and post-ringing to about one cycle by having a slower filter slope, comparable to what is done in the analog filters in NOSDAX. This is often called an appetizing filter. But again at the risk of aliasing products that, in a very worst case, can make voices sound like robot voices from early science fiction movies. Fortunately, in audio equipment it affects only the high frequencies while the levels are low enough to be inaudible. Still, the quality of the filter algorithm, for a large part defined by the computational power of the DSP, has enormous impact on the sound quality. That DSP, digital signal processor, can be an integral part of the DAC chip, in which case it is very limited or it can be a separate DSP chip and then can vary from more powerful than the integrated DSP to extremely powerful like in FPGA DACs. And then there is the MQA approach. That is an approach that looks a bit like computational photography. Modern cameras also have one or more DSP's aboard that know the errors in the picture sensor and compensate for them. With system and reflex cameras, where lenses can be exchanged, aberrations can be corrected too, since the lens holds information about its properties. With MQA there is a group of people that focus on the compression properties, but those are irrelevant. It was just a technique they had on the shelf. The important part is the correction of time smearing errors that are specific for a given DAC and the filtering that can repair time smearing in the recording. For the first you need a DAC that is MQA enabled, for the second you just need a player that can unfold the MQA signal. In my set of 1A I have room decode the MQA signals and then play them back over my core DAVE DAC. I more and more prefer MQA files over normal PCM files. Or my set of 1B, whether the MQA enabled MiTech Brooklyn is the DAC, MQA files are almost always the preferred choice. I more and more believe that MQA is a very good way to make affordable DACs sound better than possible otherwise. But if you want to judge MQA and you don't own software that can do this first unfold and you don't own a true high end DAC, you need an MQA enabled DAC. Judging MQA files on an affordable non-MQA DAC gives false outcomes. Ok, now I come to the point I was trying to make. On my set of 1A, using the Grim Audio Mew1 player, the Core DAVE DAC, the Acoustics AX520 amp and the PCM FACT 12 signature loudspeakers, the differences between high res files and CD quality is extremely small, probably more likely due to differences in mastering than due to the sampling rate. That's different with my set of 1B, whether DAVE DAC is replaced by the MiTech Brooklyn DAC with Ferrum Hipsis power supply. Here the time smearing is lower, the pace and rhythm is better, voices are cleaner, the stereo image is deeper and more in focus with high res files. In my set of 2A, the Denofrips Aries II DAC feeds the Marantz Ki Pearl light amp that drives the Acoustic Energy Radiance 1 loudspeakers and Abrell T5 sub for the bottom end. Here the difference is a step greater while with set of 2B, where the Bluesound Node 2 is the player, the difference is even slightly more. My very affordable set of 3 doesn't make the differences greater but the differences still are clear. I have not used MQA files for this test, just normal linear PCM files in FLAC and DSD files in DSF format. They all came from the Green Audio Mew1 that sends the audio files as server to the local players, with the exception of my set of 1 where the Mew1 is the digital player too. I more or less gave away the answer, didn't I? Apart from Jitter, that has also to do with hardware quality, there is one process in the digital player chain that has enormous influence, the reconstruction filter. Chip DACs use integrated chips that do the digital filtering and conversion. These chips are simple and have little processing power and thus poor sounding reconstruction filters. Better DACs than CD players also use DAC chips that use a separate microprocessor to do digital signal processing. And the top DACs and players use field programmable gate arrays, processors that are programmed by the manufacturer with their own code. If you send a 192 kHz PCM file to a simple DAC, it doesn't need to do the upscaling itself with its limited DSP function and thus limited algorithms. On high end FPGA DACs, there is a lot of DSP power and very good algorithms, so the differences are small to non-existent. So to me it is clear that high res files sound better when they work around the limitations of an affordable DAC. If the reason high res files sound better is because they make the work for the DAC lighter, why shouldn't we upscale CD quality files? Well, that's exactly what upscalers also called upsamplers do. Even Cort manages to improve the sound quality of the Cort DAVE if you use its upscaler. See my review. So there's even is a difference in quality with upscalers, for the external one by Cort sounds better than the one inside the DAVE DAC. Still there is a difference with true high res files. The ones that are recorded at higher sampling rates. For since they were recorded at a high sampling rate, the anti-aliasing filter in the analog to digital converter didn't need to be so steep and thus has less time smearing. The quality of upscalers differs greatly. The filter algorithms and dithering have enormous influence on the sound quality. So it's not as simple as downloading free upscalers software and converted all your CD ribs to 192 kHz or even higher. It is also questionable if extremely high sampling rates on DACs have any serious meaning. The 768 kHz sampling coming from a Cort Scaler sounded very fine but the 192 kHz upscaler from the Grim Audio player sounded even better on the same Cort DAVE. There are people that upscale their PCM recordings to DSD. That takes a lot of computational power and might need more power than a music server can deliver. That can lead to losses in audio quality. The same goes for a lesser degree for upscaling to very high PCM sample rates. It's not said that DSD always sounds better than PCM. Some DACs work better in DSD, others in PCM. There are even DACs that can switch between algorithms for PCM and DSD. In one mode PCM sounds better while in the other mode DSD sounds better. Don't forget that any DSP process is lossy. With good DSPs, the loss is very limited while the gain elsewhere is bigger. But if you use your measurement equipment instead of your ears and measure only the scalar, you will find it loses quality. Like bigger tires on cars, increased roll resistance and thus fuel consumption but gives you a better road holding in exchange. For most people high-res files will sound better since they work around the limitations of the reconstruction filter in the DAC. The higher the quality of the DAC or digital player, the smaller the difference between high-res and CD quality. Pop and Rock has limited availability in high-res. Classical and jazz music is more available in high-res, especially in DSD. Please don't look at the numbers but use your ears. Those that look at the numbers only will necessarily dumb down the arguments for audio is rather complex. Or better, audio isn't that complex our hearing is. And treating our hearing as a linear device, as technicians often do, will lead to anything but audio nirvana. And that brings us to the end of this video. As usually there will be a new video next Friday at 5pm central European time. If you don't want to miss that, subscribe to my channel or follow me on the social media so you will be informed when new videos are out. Help me reach even more people by giving this video a thumb up or a link to this video on the social media. It is much appreciated. Many thanks to those viewers that support the channel financially. It keeps me independent and lets me improve the channel further. If that makes you feel like supporting my work too, the links are on the comments below this video on YouTube. I am Hans Beekhuyzen, thank you for watching and see you in the next show or on theHBproject.com. And whatever you do, enjoy the music.


Russian army is an army built on the models of the 18th century, Ukrainian military officer. The Russian army is an army built on the models of the 18th century. It's an army of officers, where a soldier is a cog, meat, trash. Its strength is its mass, and also the vertical, which is capable of killing thousands, tens, hundreds, millions of people. The weakness is that Russians are not able to fight for a long time. All of their wars last 1.5-2 years, and if they don't get help, they lose. This is the way of things, states Oleksandr Alfairov. Ukrainian historian and military officer in an interview with RBC Ukraine, he emphasizes that North Korea, Iran and China are Russia's sponsors. Without their support, Russians cannot fight. The Russian army is quickly running out of steam. It is aimed at a quick offensive, and they cannot fight for a long time without help. And this has already been confirmed. They can no longer fight without foreign equipment, says Alfairov. Yes, the Russian army was feared in Europe, but not for its valour, courage and bravery. They were afraid of it because it was a cattle herd. In Russia, there is not a single ordinary person who is a hero. Their heroes are the senior officers. It was only when Russia lost the Crimean War that heroes appeared. And they were named Shevchenko and Kishka, Ukrainians, says Alfairov.


In the following demonstration, we have a closer look at GitOps for manufacturing edge. We will see actually how we can speed up the software development and release cycles for applications that span from central data center to manufacturing plants and line data servers. This means on one hand the software development and rollout, on the other hand also optimizing the whole lot of configurations across multiple manufacturing plants. All this with an approach that is called GitOps, where we have all the different changes managed in Git and using processes like pull requests and deployments to hold out the right configuration to the right side in a very controlled manner. The context is here a simplified application for monitoring and production environment. The application spans across three levels from top to bottom, the central data center, factory data center, and the line data server. We will see in the first demo flow how an OTOps manager can change the configuration of sensors using a GitOps approach and in the second demo flow we have a look at the developer and especially rolling out software change with a pipeline and doing the correct versioning and doing this controlled within GitOps approach. During the demonstration the dashboard of the sensor can be monitored by the machine operator. Let's first look at the application, you can see the dashboard which is used by the machine operator to observe various parameters and as you can see the metrics are rolling in in real time. The technology beneath is deployed on Red Hat OpenShift and let's have a quick look at the pods running. First you see for example the pod for the line dashboard, for that dashboard actually in one OpenShift environment and a different kind of project. We also see the pods for the messaging that means for the AMQ and pushing the data to the real time UI and on a completely different cluster you see actually the two pods for the machine sensors. Now we are going to change the configuration of the sensor using a GitOps approach. As you can see here we have two sensors but one sensor sending temperature and vibration data and the other sensor only vibration data. We are jumping directly into GitOps for that change and in this directory you see the settings for specific deployment, the deployment is here the production deployment and the settings here are really specific to this production environment. But we can fine tune these because the generic settings are defined in templates. Here you see the templates for machine sensors and for example the properties which are generic and for all sensors and with the approach we have here with the directory structure and with the concepts of using customize to tune the manifests we can only do or we can do the changes really in the fine grain manner without duplicating a lot of configurations. Now let's do the actual change. We are simply putting here this attribute sensor temperature enable and true or make a quick command here temp to true and commit to change and we are committing this here now directly into master and if you were GitOps approach we would create a pull request or do this in a branch and create a pull request but let's do this now directly into master. We can now also jump to ARGUCD and ARGUCD is observing the changes in the regular interval we can force a sync so that we don't need to wait it's already jumping in you see the changes here now it actually wanted to have the change here and then deploys the new configuration to the to the pods this will be picked up pods will be restarted and we will see also here in a second already immediately how these extra lines coming up the extra charts coming up for the temperature data. So that means with this change and the monitoring or the approach of ARGUCD and monitoring the files in the Git repository and forcing that to the actual OpenShift deployment in the production environment we deploy this change automatically. In the second part I'd like to discuss actually the rollout of software changes using OpenShift pipelines this will involve here on one hand the OpenShift pipelines that means the Tecton project to build the software to test the software pushing then containers to Quay and then rolling these containers out again. We assume here that the software change has been already made and we will drill down into the pipeline. This is actually an example or this is the pipeline how to roll out the consumer component it has several steps which I would like to explain briefly. In the first step here the containers are built and then pushed into the local registry. We are using here semantic versioning that means on the next steps we are having then the version file counted one level up and with that also tagging the newly created containers in the local registry. Because this is the GitOps approach we are also tagging now the manifests to declare which image should be deployed. And we are doing this in this step here to actually change the configuration, the GitOps configuration on GitHub. That would be a change like this here where you see here the customized file and then the image and the text that means we are tagging the image here so that the new version would be deployed in this test environment as a first step. And then running actually informing argcd to deploy this change so it would pick up the customized file and deploying new containers and then having that deployed in this testing environment here doing various tests for the sensor, consumer and end-to-end test and if everything runs okay we can now or the pipeline pushes the image to Quay because from the central Quay repository we would feed this into the production environments. So once this is done we also modify the GitOps repository for the production environment that would be the same step like before and this time we can also have a closer look here. It would simply go ahead and change the customer's file with the customization file with the new image tags and then at the last step it would create actually the pull request. The pull request is say look the changes have made correctly and now we can somebody can now say okay I want to hold in this change for production. This is the pull request that can be viewed of the changes of the configuration that means exactly saying which container should run well and approving this pull request and merging that in argcd then would pick that up and then also enforcing the change for the production environment. So we looked at two GitOps use cases for manufacturing edge. One hand rolling out configuration change for software sensors that has been then deployed through enforcing the manifest with argcd to the right location and secondly a tecton pipeline where we build new containers, test containers, put the right versions into the manifests and then rolling out that to the test environment but also rolling that out or creating a pull request to hold this out into a production environment. In this video I'm going to demonstrate one of the many ways you can extend the GitOps model to your machine learning workflow. As part of the GitOps for manufacturing edge demo we have sensors deployed at the edge data centers that are using machine learning to detect when anomalies occur. In this scenario I want to show you one of the many ways in which a data scientist can develop a model at the core data center then update multiple edge data centers simultaneously with one commit to a GitOps repository. Here we are utilizing the open data operator to provide a data scientist with the tools that they need to develop their machine learning models on OpenShift. Here we have a Jupyter notebook with a model that a data scientist has just updated and now needs to make it available for all of our edge data centers. In this cell you can see we have serialized this model so that it can be packaged and deployed in our updated image for model serving. A GitOps repository that will provide the source for our image that will be deployed to the models at the edge. Once the updated model has been committed to the repository we will execute an OpenShift pipeline that will orchestrate our CIC process before we release this model into production. The first task will build the model serving container image locally using a source to image build process and automatically determine the next available image tag build number for the release. The next few tasks will perform our CI test to verify that the model deploys and runs successfully in our staging environment. Once the CI test executes successfully the pipeline will push the new release of the container to an image registry that can be accessed by the edge data centers. Finally the pipeline will update the GitOps repository by creating a pull request that will specify what version of our model needs to be deployed at the edge. Now that the container image and GitOps repository has been updated all of the edge data centers running Argo CD will detect the change and update their models accordingly. This example shows one of the many ways you can extend the GitOps model to your preferred data science workflow. If you would like to learn more or try this out on your own please look for more information on our website at opendatahub.io.


Boston baseball, a longstanding tradition and rich heritage of New England. This year America's most beloved ballpark meets the baseball beanpot yet again. Fenway Park will host the annual college baseball tournament where four teams will vie for the coveted beanpot title. UMass Boston College, Harvard and Northeastern. Fantastic, fantastic idea. I think it's great. I think we'll have a big turnout and it's nice weather, especially after this winter. I think it'll be fantastic. Some believe Fenway Park is the perfect fit. Everything will be good to be surrounded by the baseball, the history of it and everything during the tournament. The money raised through the tournament will act as a donation towards Pete Freight's cause, an athlete who participated in this exact tournament just nine years ago. The former division one college athlete who was a captain of the Boston College baseball team was diagnosed with Lou Gehrig's disease and has since then become the face of ALS. Tickets will go on sale for $10 each. The net proceeds from those will go directly to the Pete Freight's number three fund. At Fenway Park for BUTV10, news at noon, I'm Christina Loeb.


John Kaye is one of Britain's leading economists, well known in this part of the world for his articles in the Financial Times, not to mention the occasional court appearance. Economics, Finance and Business, an interesting mixture, which occasionally blended with statistics. His career has spanned academic work, think tanks, business schools, company directiveships, consultancies, investment companies. Today, these days, his main focus is on writing. He has been a Fellow of St. John's College Oxford since 1970 and has held chairs at the London Business School, the University of Oxford and the London School of Economics. He has been a member of the Scottish Government's Council of Economic Advisers and chaired also the well-known review of equity markets and long-term decision making, which reported to the UK Government's Department of Business Innovation and Skills. Since the outcome of the referendum on membership of the EU in 2016, he was appointed a member of the Standing Council in Scotland and you're appointed by the First Minister, Nicola Sturgeon. He's the author of many numerous articles and has contributed to the Financial Times for over 20 years. His many books, I won't list them, but there are several of them. One of them titled Obliquity in 2011, he's fond of that term because he also has a separate article titled Obliquity as well, which is an interesting phenomenon and he has his own particular definition of it. His definition is the process of successfully achieving complex objectives indirectly. But it also can mean deviation from moral rectitude or sound thinking, which is an interesting contrast I thought. Anyway, Professor Kay has been honoured in the Queen's New Year's Honours List of 2014. He's an honorary fellow of really too many bodies, bodies which are too numerous to mention and with that I'm going to hand over to him for today's talk in the exciting times that we live in. Thank you. You asked me here a few months ago to talk about Social Security and Welfare Reform. I wondered whether I might substitute a talk about Quantitative Easing and the Zero Lower Bound in monetary policy, but I suspect none of these are what we actually want to talk about today. I think there's probably only one subject on our mind. Now, consistent with a broad title I took for this talk, you might want me to talk about what's going to happen next. You know what our President Trump's economic policy is going to be? How will the global economy respond to all of this? Well, I'm bound to say I don't know the answer to any of these questions, and I'm pretty sure that President-elect Trump doesn't know the answer to any of these questions either. So I think we should perhaps postpone for a little speculation about what's happening there, although these are subjects which we are going to have to come to. But I want instead to talk about the broader phenomenon of which this is part, that the election yesterday in the United States follows the Brexit referendum in the UK back in June. We are going to have before the end of the year a rerun of the presidential elections in Austria, a referendum in Italy. We're going to have next spring an election in the Netherlands in which the party led by Geert Wilders is currently the largest polling party in the opinion poll. We're going to have a French presidential election in which it seems highly likely that Marine Le Pen will at any rate be the candidate and one of the two candidates in the second round of that particular election. And of course we have an election in Germany later next year in which Alternative for Deutschland is gaining share. Most of these things will turn out the way I think most of us would wish them to. But if we think that all of them will turn out the way we would wish them to, we have not learned the lessons of the Brexit referendum or yesterday. What's going on? Why do we have this rise of what seemed certainly in the two cases where it's gone the way we would mostly not have voted for? Why is it that we have this populist upsurge? And the standard as it were, liberal minded story about what has been happening, runs something like this that is really primarily an economic phenomenon, that it's the product of globalization in large part, that what globalization does is it influences the economies of Western countries by widening the dispersion of earnings in these countries. There are quite a lot of people then, even if people are aggregate in these economies have gained, there are quite a lot of losers for this. And what the populists, whether they're Trump or the Brexiteers or Wilders or the opponents, the Bepo-Grillers-Chinkus-Teller movement, what they've been able to do is to pick up these kind of sources of discontent. My view is that that story isn't completely wrong. There is something in it, but it's only quite a small part of the story. And I'm also worried by that approach because it points to me what are the widely advocated solutions to it, which I think will not be enough. That is the story is that if these are the causes, what we need to do is actually to spend more on easing the transitional problems of disappearing manufacturing industry and go back to the subject I might have talked about, which is social security and tax reform, how we can do that in order to reduce the distribution impact of these developments. So I think we should actually be looking at this in a much broader context. Firstly, we should realize that not all, as it were, the newcomers who are winning large shares of votes or making a large impact on the political scene, not all of them are, as it were, these kind of right-wing populists. Not all of them are xenophobes. We've also had the phenomenon of Corbyn emerging as Labour Party leader in the UK. We saw the startling fact that Clinton's main rival for the Democratic nomination was Bernie Sanders. Obviously it's extraordinary that there wasn't a mainstream Democratic contender of any serious kind. But it's also even more extraordinary that in 2016 a highly successful US presidential candidate would be someone who was a self-declared socialist, even if his brand of socialism is not necessarily one that Lenin would have recognized. We have in Podemos in Spain, now potentially part of that government, we have Syriza in Greece, which has been the government. That is we have the emergence of new movements tackling into all kinds of sources of political support, not just these xenophobic parties of the right, those xenophobic characters on the right, on which we're focused in the moment. Secondly, people have rightly drawn attention to the fact that Trump, according to today's polls, won by four to one among white, non-college educated men. And we're identifying that as the Trump phenomenon. Let us be clear, however, that there are not so many white, non-educated men, non-college educated men in the US population. Most of the people who voted for Trump did not fall into that category. And while it's true that what pushed Brexit over the edge in the UK and made it successful was the extent to which they won over naturally Labour voters in the north of England. That was not where the bulk of the support they obtained came from. We know, in fact, that people who voted for Brexit are not poorer than people who voted for the UK to remain in the European Union. And we also know that polling evidence suggests that people who voted for Trump on average have higher, not lower incomes than people who voted for Clinton. In the Brexit case, and I suspect we believe much is the same true in the Trump election case, in the Brexit case, the two most powerful indicators of propensity to vote for Brexit were age and education. So these are not actually simply people who have been economically depressed by what is going on. One has said of referenda that you can frame the question you ask the people, but you cannot frame the question the people will answer. And in the UK case, I think the question was framed, as do you think Britain should remain within the EU, but the question which was answered was, I think, are you happy about what's going on? And that is roughly the question which I think people were voting on in the US presidential election as well. Thirdly, what has happened to inequality in Western economies is not as simple as the generalisation that what we've had around the Western world has been increasing inequality would suggest. What has happened to inequalities is actually rather complicated. And I'm sure many of you will have bought, if not as many have read, the Piketty book on inequality, which has been extraordinarily successful by pandering to people's impression or their desire to believe that inequality has been increasing and that is a bad thing. Well, these things may be true, but the totality of the very large amounts of evidence on that in that book in general is not that clear cut. First of all, we need to distinguish between inequality of income and inequality of wealth. And if one looks at inequality of income, what has happened across Western economies differs radically from country to country. For example, in both Britain and the United States, the share of the top 1% has increased very markedly over the last 30 years, which in my view is primarily a phenomenon of what has happened in the financial sector and related developments in the corporate sector, which have led to small numbers of senior executives being paid a great deal more. In both countries, we've heard rather a lot about what has happened to the median wage. Now, that's a rather subtle observation because one thinks of the median as being what happens to the representative household in the economy. But it's not because the median household, who are the median household, does not remain unchanged when the makeup of the population is changing. And the makeup of the population has, in most countries, been changing. So the result of the formation of new households, smaller households, in many cases, the arrival of immigrants who are distinct units. So that what is happening to the median income is not in fact representative of what is happening to people in the middle of the income distribution. And these statistics have been simply misleading in the way they've been quoted in relation to that. And then there is the issue which preoccupies Piketty, which is about what has happened to the distribution of wealth. Now, the truth is in modern economies, in modern developed economies, the most wealth is either housing or pension rights. It's also unfortunately true that the best data we have in distribution of wealth comes from data which is obtained at death. And at death, the value of people's pension rights is by definition zero. So that what we get is in that sense a fundamentally misleading picture. But also the main thing that has happened to wealth over two centuries that Piketty talks about is that wealth has shifted from being in agricultural land to being in urban land. And most of the wealth in urban land is actually in unoccupied housing. And from that perspective, there is now a distribution of wealth which is unequal because the percentage of a housing that is in unoccupied although well above 50% in Britain and Ireland is also well below 100% in both countries. But that has actually produced a dispersion and a relevant sense of wealth much greater than was true before. But what is also true is that the number of people who enjoy wealth outside significant wealth outside pension and retirement saving wealth and housing wealth is in fact very small. Everywhere around the world. These are in my view the main facts about wealth distribution. And although they lend a little bit of support to the thesis I'm describing about the causes of populism, they don't in my view lend very much. It isn't then a simple matter of rising inequality doing it. And finally, the policy prescriptions which are arising out of this now that we tinker a bit more with the tax system and we spend rather more on structural adjustment in industry. Well in most countries we spent quite a lot of money on structural adjustment in the industry, basically trying to prop up manufacturing industries on the way out in order to delay this kind of decline. That has proved in the main not to be money very well spent and has done little or nothing to relieve the long run effects of these kind of regional maldistributions. So I think the policies prescriptions are not in a sense very persuasive. I think the explanations of what's happening have to go well beyond economics. And what we're really seeing is a collapse of the legitimacy and structure of existing political institutions and structures. And that is the essence of what is happening. And this is true not just of the conventional party political structure. It's also true having a debate yesterday about the collapse of authority and above all respect for the two institutions which even 20 years ago everyone would have regarded as a model of technocratic independence, the judiciary and the central bank. These no long, there was essentially until quite recently almost a taboo on public or media criticism of the activities of these bodies. Yet we had in Britain last week when the Court of Appeal ruled on some of the Brexit processes that famous headline that said enemies of the people in the Daily Mail with pictures of the judges concerned. Helpfully pointing out that one of them was Jewish and another of them was gay and this is something that not only seems unacceptable in any democratic society but is something that one simply could not have imagined happening a few years ago. So that is where we are in terms of this loss of confidence in political institutions. And if we ask what are the origins of that, I think we can find quite a bit of it by going back 25 years now to the end of the Cold War, the collapse of socialism, the collapse of socialist regimes and moving into the world, which Francis Fukuyama famously described as the end of history. With the idea that a combination of likely regulated capitalism and liberal democracy was not only something that was prevalent in many western economies then but was essentially the model which was there for good and which most countries would over time learn to move towards. I think we've now learned that the kind of hubris that surrounded that had in it many of the seeds of its own destruction. And I want to pick out two themes from that. One which I will mention only briefly because I've written quite a bit about it elsewhere is to say that the idea that the model of likely regulated capitalism which should prevail was one in which you basically welcomed individual greed, encouraged people to be as selfish as possible within a limited framework of rules, encouraged companies to focus on shareholder value and believed that the growth of an economy was facilitated by the speed of growth of trading and financial markets. That was a model of capitalism which actually was a comprehensive misunderstanding of what the strengths of a market economy were. And if we didn't learn about that within the collapse of the new economy bubble in 2000, which is when I must say I thought we had learned about it. We had to learn about it again in the global financial crisis of 2008. And we will unfortunately have to learn about it again in the global financial crisis of some time or other, which may be rather more imminent today than it was even 24 hours ago. We pursued a misunderstanding of how markets worked that actually undermined the legitimacy of the market system itself. There was a second significance of that development, which was if one asked how European politics had mostly been organized for the century that preceded the going down of the Berlin Wall in 1989. The answer was you typically had a party of the left, which a loosely socialist ideology, which certainly favored a relatively large role for the state, and which worked in combination with a largely unionized trade union movement that produced much of the vote and some of the leadership for these particular parties. These parties were opposed by parties of the right, which consisted of coalitions of the group of people who felt themselves threatened by the parties I've described. That is, they were conservatives of various kinds, social conservatives, Burkian conservatives who thought that nothing should change very quickly. People with religious views, people, social conservatives, with religious values and the like. And that formed the basis, essentially, of European parties of the right. The collapse of socialism, I'm suggesting, destroyed a very large part of the rationale of these parties of the left. And what a characteristic European party of the left now consists of is a kind of well-educated elite whose views on important issues are mainly concerned with things like discrimination, the environment and the like, combined with a traditional working class base for whom that agenda does not really resonate at all. And these parties have, in this sense, lost that kind of coherence and both groups are peeling off in order to find roots elsewhere. What the left in Europe has failed to do is find a coherent narrative to reconcile their kind of progressive views with acceptance of the primacy of a market economy. And if that's created problems on the left, it's also created problems of the right. Because if you're a coalition to fight an enemy and the enemy disappears, there is not very much you have left in common to pursue. And that's how we've seen in Britain the internal battles within the Conservative Party that have resulted in the Brexit referendum and equally in the United States, the ructions in the Republican Party which have ended in the most improbable possible way, improbable way imaginable, with Trump being elected as Republican president. So that we've had, in this sense, the collapse of traditional political structures on both left and right, and it's into that vacuum that people like Trump, the Brexiteers, Corbyn, Podemos, all these other fringe parties from around the world have moved. And that is the story and large part of this collapse of political authority. At the same time, this has been supported by changes in the media. I've already described the abandonment, essentially, of social restraints on what it is you can say, both about institutions, central banks and judges, and about people, so that everyone is aware of the phenomenon, the trolling and abuse through social media that simply enables dialogue to progress outside the traditional, rather constrained structures of our traditional media. That's created the world that favors derision of experts, has this concept of truthiness, a nice word I've rented by Stephen Colbert, to describe the observation that something is true, if you feel it is true, independently of the objective facts, which might be relevant to a traditional assessment of whether something is or is not true. And that's what takes us to the ability to identify judges, which is to slow a process down, or indeed throw it back to Parliament as enemies of the people. So what I've been trying to do is describe the rather, in my view, complicated explanation of what has brought about the situation in which we're finding ourselves today and a situation which is probably not going to get better, but may in well-important respects get worse over the next year, because one of the things I think we are likely to learn is that there is an element of contagion in these populist movements that Brexit probably made the election of Trump a bit more possible, and the election of Trump makes these improbable events around Europe more probable as occurring in Europe. Is there any hope in all of this? Well, there may be some hope in the idea that we're having a wave of destruction through our political system, which in the long run may actually enable us to create something that is more stable and more relevant to the 21st century. It may be, for example, that it will enable us to have a meaningful and effective attack on the excessive role of corporate interests in dictating political issues, which has been one of the problems that we have in getting sensible policies adopted today, most of all, I think, in the financial sector, and which is behind quite a lot of the popular dissatisfaction with the way in which the political system is operated. The fact that Hillary Clinton had been earning $225,000 per time for speeches to Goldman Sachs was significant and by no means properly the relevant event took public attitudes to her. I regret that the institute is unable to pay $225,000. But perhaps in a different world, they might be able to. What is going to happen around Europe might well waken us up to reconsider the realities of the European project to recognise that it was going down a route in which the answer to every problem was, as it were, more Europe, which was taking it further and further away from the popular legitimacy and popular desire for more Europe, which brought the European Union into existence in the first place. There are many better unions. In fact, there are almost no better European unions which we could create, which would not, in many respects, be better than the present European Union. And perhaps there is some hope that actually Brexit might be one of the catalysts towards a more fundamental consideration of what it is that Europe is really about. But one finds it difficult, standing today, to feel any optimism about what is going to happen in the three or four years ahead. And that is a note on which I fear I should sit down and let you express your views. Thank you all.


Welcome to the 2016 NCHA Ferturity. I'm here with the winner of the unlimited Amateur Final, Wade Smith, who rode metallic candlelit and marked a 223. Congratulations to you Wade. Thank you very much. Tell me what did that run feel like? That was the most fun I think I've ever had. After that run I was ready to do it again in the second go. The merit was just spot on and the cattle were so good and my help was so great. It helped me find the perfect cows and I just felt like I could do anything. So do you remember much about the run itself? What was it about the run that really felt good? Describe it to us. You know my number one priority was to go in and make my cuts clean and in the middle of the pen and get pushed way up and the mayor pretty much just showed herself. It's probably one of the easier horses to show that I've ever been on and absolutely one of the easiest three year olds that I've ever been on. She's so mature and I don't really have to worry about too much. If I can just get her put on the cow right and she takes care of her. So you were along for the ride? I was and it was so much fun. I loved cutting ever since I was a little boy. I remember I think I was like 13 or 14. I went to Terry Riddle, Bill Freeman cutting school at Terry's place when smart little Lena was two. Bill Freeman would give me a hard time because the horse would fall down and start whacking on a cow and I'd be smiling while I was doing that. He'd wipe that smile off. This is serious. He was giving me a hard time and I've just always loved cutting. What do you think he'd say today about your win? I think he'd probably say good job. I wish he was here for me to talk to. Yeah, I bet. Your horse, tell us a little bit about metallic candlelit. When did you come by? I had sold a three year old that Clay Johnson was training for me to Alana Chalmers and she made the limited non-profinals and the non-profinals on her. He called me in October towards the end of October and he said hey I've got one that you need to come try. I told him keep an eye out for something and he's like come try this and it took me a couple of weeks to... Jail with us? Well just to get to his place to try it. With logistics I was showing at the app world and then I went home for a couple of days. And then he was in Catoola at a pre-work at his in-laws and it took me a little bit. But looking back at it now I wish I would have just dropped everything and just drove straight away just to lock it up. But I went and I tried her and I worked two cows on her and I knew she felt so special and I said is she like this all the time? Oh yeah and I said well let's make the deal. And you have actually competed a few times here in the Will Rogers before. You've got a second tell us about that. Yes first time I showed here was in 1985 when I was 16 years old.  There was a question on the review. I have never forgot this. I marked a 214 and two of the judges got me for it and one of them didn't and it took a 214 and a half that year to go to the second go. And I have replayed that run in my head. It's one of those where you wake up in the middle of the night in a cold sweat wondering why didn't you do it like that? I haven't shown every year at all since then. I showed two times 85 and 86 and didn't get to make it to the second go. And there wasn't any amateur then. I was competing against Shayla Welch and Mary Jo Milner and Carol Rose and everybody who was just winning everything in the non-pro all the time. And I still felt very fortunate to be in the arena with those people. And now we have the unlimited amateur and it's probably where I need to be. And I'm glad the NCAA has this class. Now you've got a box here that I'm assuming is filled with family and friends who got to watch you win tonight with a great score of 223. How does that make you feel? Blessed. My mom's 85 years old and she got to be here to see it. My wife, I haven't been home for like six weeks and she's at home with my younger children helping them get to school and my sons in college. And all of my horse family, my trainers and their wives and the people who helped them and my people, it still feels like family. And I bet this win kind of makes up for that. That just narrowly missing out when you're 14. Yeah, yes it does. But I still wish I had that run back. That would have been a dream come true but tonight it's been a dream come true. It still hasn't sunk in. Well congratulations, great job. Thanks for joining us. Hey, thank you very much.


How are you getting along? Well, fine. I didn't know whether on this day we're, you know, and I know how hard you've been going. But it would make a big help, I think, in Long Island. You know, the day that you're coming in, I think it's the 31st. Yeah? If perhaps you could come in a couple of hours early and we could take a trip through, you know, arrive at the airport out of Long Island and take a trip through Nassau County, they think they could get a couple of hundred thousand people out. Well, if it's not already blocked out, it'll be done here. Jack Belendi is not here. Wait a minute, maybe he is. Well, let me see if he is now. That's the 31st. And I speak that. You're supposed to come in for the rally. You were going to come in for the whole day. And I think the day's been canceled. I speak that night at Madison Square Garden. Yeah. And if it could come in so that you could maybe arrive at one of those fields out in Long Island and just take a motorcade in through. Say it, three o'clock or four o'clock. Let me ask you. Let me ask you. Bobby? Hi. Is this important? He would really be a big help. We are trying to beat Williams very confidentially.   So I told him to put in my schedule that we would be in Wilmington at 3.30 and Dover at 5 o'clock before we went to New York. Now I've told Marvin Watson, who's in charge of my schedule, Jack Blenty's gone, that if this is important to tell them in Delaware, we'll be there at noon and we'll try to get through at 2.30 at Dover and leave at 3 and get up there by 3.30 at 4. Well, that'd be terrific if you could do it. If it's that important, we'll do it.  And if, well, now if I do this, you get some Negroes, you talk to Roy Wilkins and get him to send one or two of his organizers into Dover and Wilmington. They got a lot of people registered, but they say they won't vote. You know who's good? That's Charles Evers from Mississippi. Yeah. They could get him up there. All right, well, now, I can't do that. Well, do you do that for me? Yeah. I'll give you, I'll give you, I'll give you three hours. I'll get the people. I'll give you three hours before the Madison Square Garden. I'll be in New York not later than four o'clock. OK, and I'll get there after the game. And you just do it quietly and call on anybody in the federal government you need, but do it where they don't catch you. But we want all the money, and I'm putting some money in there, but we just want to keep him from hounding us every day for four years. And I'll be there, and you just set the schedule of what you want me to do. Is there anything else I can do? No, that's terrific. Give it, when you turn over at night and put that effle on your arm, give her a hug for me, will you? I'll do that. Good night.