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[Assistant] Otherwise, we get the comparator value with the value we're trying to insert against the current node to determine if we should go on the left or the right subtree.


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[Assistant] After that, on the recursive callback, we call the update method, which updates the bounce factor and height values for this node. And lastly, we rebalance the tree with a bounce method. Now let's take a look at the update and bounce method and what they're actually doing.


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[Assistant] The update method updates the balance factor and height values of our node. So to calculate the height of the node, we get the maximum height of the left and the right sub trees and then add one


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[Assistant] Notice that I initialize the left and the right subtree heights to be minus one. This is because it will cancel out with a plus one with a max function in the case where the node has no sub trees, giving the correct height of zero for leaf nodes.


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[Assistant] Lastly, I update the balance factor for this node by finding the difference between the right subtree and the left subtree heights.


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[Assistant] The balance method is slightly more involved, but not too crazy. Here we check if our balance factor has an illegal value of minus two or plus two. If the bounce factor is a minus two, then we know that the node is left heavy.


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[Assistant] And we dig further into the left subtree to determine if we're dealing with a left left case or a left right case.


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[Assistant] We do a similar thing if the bounce factor is plus two, except we're dealing with the right right or the right left case.


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[Assistant] If the bounce factor is not plus two or minus two, then we know that the bounce factor is going to be either plus one, zero or minus one. And in either of those cases, we don't need to do any


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[Assistant] Inside the four cases we might run into, notice that all we do here are calls to the left rotation and right rotation methods that we saw in the last video.


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[Assistant] Also notice that the left right and right left cases call the left left and right right case methods respectively, since they reduce to those cases after a first rotation.


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[Assistant] In the last video, we looked at this right rotation method. But since we're dealing with an AVL tree in this video, we actually need to augment that method to update the height and balance factor values for the nodes we're moving around when we do rotations.


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[Assistant] This is a subtle detail you must not forget. Otherwise, your height and balance factor values will be inconsistent.


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[Assistant] The left rotation case is symmetric to this one. So you should be able to figure it out pretty easily. And that is all for AVL tree insertions. In the next video, we'll look at how to remove nodes from an AVL tree. And in the video for that, we'll look at some source code.


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[Assistant] However, if you're keen to look at some source code right now, you can always check out my GitHub repository where I host all my data structures at github.com


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[Assistant] Welcome back. Today's topic is going to be on an efficient way to solve the longest repeated substring problem.


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[Assistant] The longest repeated substring problem is another one of these fairly common problems in computer science. Lots of problems can actually be reduced to this problem. So it's important that we have an efficient way of solving it.


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[Assistant] The naive approach requires n squared time and lots of space.


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[Assistant] What we want to do instead is use the information stored inside the longest common prefix array to yield a faster and also space efficient solution.


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[Assistant] Let's do an example. What is the longest repeated substring of the string abracadabra? Feel free to pause the video and figure it out yourself.


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[Assistant] The answer is the substring Abra, which is the longest substring that appears at least twice in the string. So we call it the longest repeated substring.


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[Assistant] Here you can see the first instance of Abra on the left.


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[Assistant] And now you can see the second repeated instance of ABRA on the right. Although these substrings are disjoint and do not overlap. In general, this is permitted for the longest repeated substring.


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[Assistant] Now let's solve the problem using a suffix array and an LCP array which I have generated on the right hand side. I'll give you a moment to pause the video and inspect the LCP array in case you notice anything special in relation to the longest repeated substring now that you already know what the answer is.


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[Assistant] Effectively, what we're looking for in the LCP array is the maximum value. intuitively, we want to do this because we know that the suffixes are already sorted.


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[Assistant] So if two adjacent suffixes have a large longest common prefix value, then they share a good amount of characters with each other.


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[Assistant] We also know that if the LCP value at a certain index is greater than zero, then the string shared between the two adjacent suffixes is guaranteed to be repeated, because it is common between two suffixes, each of which start at different locations in the string. So here again is abracadabra.


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[Assistant] Since our LCP value was four, we know that the first four characters from the suffix abracadabra forms one part of the repeated substring.


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[Assistant] Next, we know that the suffix above it, which shares the LCP value of four also shares four characters present in that longest repeated substring.


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[Assistant] Well, if you did, you would find out that you not only got one longest repeated substring, but two longest repeated substrings since there can be ties.


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[Assistant] In a case like this, you're not looking for a single largest value, but all largest values that might exist.


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[Assistant] For the first maximum, you can see that we'll want the first three characters from the suffix a, b, a, b, b, a, a, b, a, a. And for the second maximum, we'll want the first three characters from the suffix b, a, b, a, a.


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[Assistant] Visually, for this first longest repeated substring, we have a BA which appears at the start, and then a BA again closer to the end.


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[Assistant] The other repeated substring is found using the second largest common prefix value. And its first occurrence is found here and the second one just next to it.


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[Assistant] That is all for repeated substrings. Pretty easy once the suffix array and the LCP array have already been constructed.


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[Assistant] Here is a practice problem on caddis if you want to tackle a longest repeated substring problem which requires you to have an efficient solution. Thank you again for watching and I will catch you next time.


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[Assistant] Moms do so much. What does your mom do?


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[Assistant] And that is the longest common prefix array, also known as the LCP array. The LCP array is an array where each index stores how many characters to sorted suffixes have in common with each other. Let's have a closer look.


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[Assistant] Perhaps the best way to show what the LCP array is, is to do an example.


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[Assistant] The first thing we'll want to do is construct the suffix array for our string to find out what all the sorted suffixes are.


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[Assistant] Notice that the very first entry that we placed in our LCP array, that is the middle column is zero. This is because this index is undefined. So we'll ignore it for now.


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[Assistant] To begin constructing our LCP array, let's begin by looking at the first two suffixes and seeing how many characters they have in common with each other. We noticed that this is two, so we place two in the first index of our LCP array.


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[Assistant] Now we move on to the next two suffixes notice that they also have an LCP value of two.


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[Assistant] And the next two don't have anything in common so we place a zero.


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[Assistant] And the next two only have one character in common, then three characters in common. And lastly, only one character in common.


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[Assistant] In summary, the LCP array is an array which tracks how many characters to sorted suffixes have in common with each other.


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[Assistant] Another thing worth noting is that the very first index in our LCP array was undefined.


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[Assistant] Since we store the LCP array as an integer array by convention, we usually set this first index to be zero, so that it doesn't interfere with any operations we might want to perform on the LCP array. And this is fine for most purposes.


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[Assistant] Lastly, we saw what the LCP array was, but not how to construct it very efficiently. There are other algorithms than the one I showed you to construct the LCP array, which run in a much better time complexity.


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[Assistant] That is in n log n time, and even in linear time, I will cover one or more of these methods in a future video. But next up, I want to talk about some actual applications of suffix arrays and LCP arrays. So thank you for watching.


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[Assistant] Ice can form on a wet house.


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[Assistant] Ice can form on a wet car.


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[Assistant] Ice can form on a wet road.


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[Assistant] Draw a picture of the season and label it. Science.


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[Assistant] What dates are you planning on taking off? I'll need at least two months notice so that I can plan for your absence.


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[Assistant] If you want to quit your job, make sure you give enough notice. You'll need to tell us four weeks in advance.


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[Assistant] Sure. Liv, what can I do for you?


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[Assistant] You wanna take some time off, is that right?


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[Assistant] What dates are you planning on taking off? I'll need at least two months notice so that I can plan for your absence.


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[Assistant] So I'll dream until I make it real And all I see is stars He's not into you for life


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[Assistant] Can we put off our meeting until next week? I'm too busy right now.


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[Assistant] I called this meeting today in order to discuss our manufacturing plan, as I'm sure you're all aware, with the credit crunch and the global financial crisis.


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[Assistant] We're obligated to look for more cost-efficient ways of producing our goods. We don't want to have to be looking at redundancies, so we've outlined a brief plan to implement the just-in-time philosophy.


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[Assistant] Right. Production lead times can be reduced by moving workstations closer together, reducing queue length like, for example, reducing the number of jobs waiting to be processed at a given machine, and improving the coordination and cooperation between successive processes.


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[Assistant] Delivery lead times can be reduced through close cooperation with suppliers. Possibly by inducing suppliers to locate closer to the factory, or working with a faster shipping company.


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[Assistant] I called this meeting today in order to discuss our manufacturing plan as I'm sure you're all aware with the credit crunch and the global financial crisis.


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[Assistant] We're obligated to look for more cost-efficient ways of producing our goods. We don't want to have to be looking at redundancies, so we've outlined a brief plan to implement the just-in-time philosophy.


[User] Please transcribe this text

[Assistant] Right. Production lead times can be reduced by moving workstations closer together, reducing queue length like, for example, reducing the number of jobs waiting to be processed at a given machine, and improving the coordination and cooperation between successive processes.


[User] Please transcribe this text

[Assistant] Delivery lead times can be reduced through close cooperation with suppliers, possibly by inducing suppliers to locate closer to the factory, or working with a faster shipping company.


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[Assistant] That's right. How many times around the house was it Mummy Pig? Three times?


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[Assistant] Okay Pepper, let's get you back to bed.


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[Assistant] What keeps us healthy and happy as we go through life?


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[Assistant] If you were going to invest now in your future best self, where would you put your time and your energy?


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[Assistant] There was a recent survey of millennials asking them what their most important life goals were.


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[Assistant] And over 80% said that a major life goal for them was to get rich.


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[Assistant] And another 50% of those same young adults said that another major life goal was to become famous.


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[Assistant] We're given the impression that these are the things that we need to go after in order to have a good life. Pictures of entire lives, of the choices that people make and how those choices work out for them, those pictures are almost impossible to get.


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[Assistant] Most of what we know about human life, we know from asking people to remember the past.


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[Assistant] We forget vast amounts of what happens to us in life. And sometimes memory is downright creative. But ...


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[Assistant] What if we could watch entire lives as they unfold through time? What if we could study people from the time that they were teenagers all the way into old age to see what really keeps people happy and healthy? We did that.


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[Assistant] The Harvard study of adult development may be the longest study of adult life that's ever been done.


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[Assistant] Year after year, asking about their work, their home lives, their health, and of course asking all along the way without knowing how their life stories were going to turn out.


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[Assistant] Because too many people drop out of the study or funding for the research dries up.


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[Assistant] Or the researchers get distracted, or they die, and nobody moves the ball further down the field.


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[Assistant] But through a combination of luck and the persistence of several generations of researchers, this study has survived.


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[Assistant] About 60 of our original 724 men are still alive, still participating in the study, most of them in their 90s.


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[Assistant] And we are now beginning to study the more than 2,000 children of these men. And I'm the fourth director of the study.


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[Assistant] Since 1938, we've tracked the lives of two groups of men.


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[Assistant] The first group started in the study when they were sophomores at Harvard College. They all finished college during World War II, and then most went off to serve in the war.


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[Assistant] And the second group that we followed was a group of boys from Boston's poorest neighborhoods.


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[Assistant] Boys who were chosen for the study specifically because they were from some of the most troubled and disadvantaged families in the Boston of the 1930s. Most lived in tenements, many without hot and cold running water.


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[Assistant] All of these teenagers were interviewed, they were given medical exams. We went to their homes and we interviewed their parents.


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[Assistant] Climb the social ladder from the bottom all the way to the very top. And some made that journey in the opposite direction. The founders of this study.


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[Assistant] Every two years, our patient and dedicated research staff calls up our men and asks them if we can send them yet one more set of questions about their lives.


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[Assistant] Many of the inner city Boston men ask us,


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[Assistant] We interview them in their living rooms. We get their medical records from their doctors. We draw their blood. We scan their brains. We talk to their children. We videotape them talking with their wives about their deepest concerns.


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[Assistant] What are the lessons that come from the tens of thousands of pages of information that we've generated on these lives?


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[Assistant] Well, the lessons aren't about wealth or fame or working harder and harder. The clearest message


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[Assistant] Good relationships keep us happier and healthier. Period.


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[Assistant] We've learned three big lessons about relationships.


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[Assistant] The first is that social connections are really good for us, and that loneliness kills.


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[Assistant] It turns out that people who are more socially connected to family, to friends, to community are happier.


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[Assistant] They're physically healthier and they live longer than people who are less well connected.


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[Assistant] Their health declines earlier in midlife, their brain functioning declines sooner, and they live shorter lives than people who are not lonely.


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[Assistant] So the second big lesson that we learned is that it's not just the number of friends you have, and it's not whether or not you're in a committed relationship, but it's the quality of your close relationships that matters.


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[Assistant] It turns out that living in the midst of conflict is really bad for our health.


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[Assistant] High conflict marriages, for example, without much affection turn out to be very bad for our health, perhaps worse than getting divorced. And living in the midst of good, warm relationships is protective.


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[Assistant] Once we had followed our men all the way into their 80s, we wanted to look back at them at midlife.


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[Assistant] And to see if we could predict who was going to grow into a happy, healthy octogenarian and who wasn't. And when we gathered together everything we knew about them at age 50,


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[Assistant] It wasn't their middle-aged cholesterol levels that predicted how they were going to grow old.


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[Assistant] It was how satisfied they were in their relationships. The people who were the most satisfied in their relationships at age 50 were the healthiest at age 80.


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[Assistant] And good, close relationships seem to buffer us from some of the slings and arrows of getting old.


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[Assistant] ...reported in their 80s that on the days when they had more physical pain, their mood stayed just as happy.


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[Assistant] But the people who were in unhappy relationships on the days when they reported more physical pain, it was magnified by more emotional pain. And the third big lesson that we learned


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[Assistant] About relationships and our health is that good relationships don't just protect our bodies, they protect our brains.


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[Assistant] It turns out that being in a securely attached relationship to another person in your eighties


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[Assistant] Is protective that the people who are in relationships where they really feel they can count on the other person in times of need, those people's memories stay sharper longer.


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[Assistant] And the people in relationships where they feel they really can't count on the other one.


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[Assistant] Those are the people who experience earlier memory decline.


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[Assistant] Good, close relationships are good for our health and wellbeing. This is wisdom that's as old as the hills.


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[Assistant] Well, we're human. What we'd really like is a quick fix. Something we can get that'll make our lives good and keep them that way.


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[Assistant] Relationships are messy and they're complicated and the hard work of tending to family and friends, that's not sexy or glamorous. It's also lifelong. It never ends.


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[Assistant] The people in our 75 year study who were the happiest in retirement were the people who had actively worked to replace workmates with new playmates.


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[Assistant] But over and over, over these 75 years, our study has shown that the people who fared the best were the people who leaned into relationships with family, with friends, with community.


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[Assistant] Let's say you're 25, or you're 40, or you're 60. What might leaning into relationships even look like?


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[Assistant] Well the possibilities are practically endless.


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[Assistant] It might be something as simple as replacing screen time with people time.


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[Assistant] Or livening up a stale relationship by doing something new together. Long walks or date nights.


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[Assistant] We're reaching out to that family member who you haven't spoken to in years because those all too common family feuds take a terrible toll on the people who hold the grudges.


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[Assistant] And today we're gonna be bringing you another great sports lesson.


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[Assistant] I know we have a lot of listeners from Russia, so this is a very popular sport in Russia, Czech Republic.


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[Assistant] And this is actually kind of like the ball that you use in hockey.


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[Assistant] And this is what the players do. This is what they...


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[Assistant] So in basketball you have a ball, in hockey you have a puck. Okay, our next word.


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[Assistant] Key goal, okay. So let's take a look at our last word now. Finals.


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[Assistant] Finals. Finals. The finals. So the finals are the last games.


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[Assistant] Okay, for example, in the World Cup in soccer,


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[Assistant] There's only one game played in the finals. So after everyone gets eliminated, there's one game where the winner is the champion.


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[Assistant] So now we're ready to listen to our dialogue, and it's gonna be a little bit faster than usual.


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[Assistant] So let's take a look at some of the vocabulary that we heard in the dialogue in Language Takeaway.


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[Assistant] It's a noun, exactly, and it's... So in the beginning of a match, the two players will stand face to face, right? That's why it's called kind of a face-off.


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[Assistant] Okay, let's take a look at our next word.


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[Assistant] Yeah, it's really interesting because it's different from the way that you would say check or revise, right?


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[Assistant] This is actually kind of a violent move.


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[Assistant] So what do you do? So basically in hockey, you take your body and you hit another person with it.


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[Assistant] With your body, right. You can't use your arms or your legs or your hands. You can only hit them like with your shoulder or your, or your hip. Yeaah. Or the hip check.


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[Assistant] Our next word, goalie. Goalie. Goalie. Goalie. A goalie is a person. Right.


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[Assistant] And probably the bravest of the hockey match.


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[Assistant] A goal. Okay, so the goalie prevents the goals. Alright, very interesting. Now, our fourth word is related to goalie.


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[Assistant] Makes a save, right? Okay, we have some examples so we can understand this form of using save.


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[Assistant] Now let's take a look at our last word, breakaway.


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[Assistant] Okay, so you have two words there that we know already. BREAK.


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[Assistant] Right, right, so he's going away from the other players by himself. Okay, so break away.


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[Assistant] Alright, so we've looked at a lot of hockey language here, and I think it's time now to listen to our dialogue again. This time we're gonna slow it down a little bit.


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[Assistant] Exactly, they are, because some actions are happening in that moment, but we notice something a little bit strange.


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[Assistant] Okay, let's listen to this sentence that we previously heard in the dialogue.


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[Assistant] Exactly. So you don't really have enough time to say for example, he is shooting.


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[Assistant] Yes. Because it's only one quick action. He shoots the puck very fast.


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[Assistant] Right? Or for example, you wouldn't really say, he is passing.


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[Assistant] Right. It's just one quick action. He takes it and passes it and the action is finished.


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[Assistant] Exactly, if you pay attention, most sporting events are in the same way, right?


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[Assistant] They would describe the actions that are happening in the present simple, not present progressive.


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[Assistant] Well, first of all, when we say he's flying down the ice it's not that he's literally flying.


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[Assistant] Right? So we kind of exaggerate and we say, oh, he's flying down the ice. But he's actually skating.


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[Assistant] So, this is a progressive action. He is doing it.


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[Assistant] Unless it was like really really really fast. Yeah. Okay.


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[Assistant] Makes it much more exciting if we just use the present simple.


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[Assistant] Okay, let's listen to this exciting dialogue one more time and we'll come back and talk a little bit more.


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[Assistant] I heard that, uh, some Canadian children learn how to skate before they learn how to walk.


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[Assistant] Well it is a great sport, very very exciting, it's very fast paced.


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[Assistant] Well, what do you guys think about hockey? We'll post some, some videos and some pictures of hockey on, on the comment section so you can more or less see a little bit more about this really interesting sport and tell us what you think about it.


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[Assistant] Exactly, and also if you have any questions or doubts about the lesson, you can leave your questions on the site.


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[Assistant] Yeaah, some phrases you can use when you welcome someone to your house. Alright, well, we've got some language to preview, so let's turn now to vocabulary preview.


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[Assistant] When you have an appetite, you, you're hungry or you, you have a desire to eat food, right?


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[Assistant] Exactly. So when you poison someone, uhm, you put something in their food or maybe in their drink, uhm, that makes them really sick and maybe even makes them die.


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[Assistant] Yep, and the noun is actually the thing that you put inside the food or drink.


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[Assistant] Or maybe this perfume has the aroma of roses and lavender.


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[Assistant] Yeah, and sometimes red wine can be quite bitter.


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[Assistant] Uhm, it means faint or become unconscious.


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[Assistant] So imagine someone, you know, they're standing up and then suddenly they start to move around and then fall over to the ground.


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[Assistant] Maybe, sometimes also when maybe you're pregnant, you might pass out.


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[Assistant] Marco and I have a couple of examples of this word for you.


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[Assistant] We've got four phrases for you that are great to use when you want to welcome someone into your house or into your office or anywhere really.


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[Assistant] It's like, make yourself comfortable, relax, sit down.


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[Assistant] And then a good host would always offer a drink, right?


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[Assistant] So they would say, can I offer you a glass of wine?


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[Assistant] Yeah. So, can I offer you a glass of wine?


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[Assistant] Alright, and then I would use our next phrase. Here you are.


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[Assistant] You know what? This is a really, really great phrase. A lot of people who are learning English don't say this, but it's really common, really natural, and if you use it, it'll sound really great.


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[Assistant] Uhm, and Merlot was actually the great variety.


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[Assistant] Yeaah. Well, right now, uhm, I'm really liking to drink Campanillo, which is a Spanish wine.


[User] Please transcribe this text

[Assistant] Yeah, uhm, you almost never find it outside of Canada, but there is one region in the western part of the country that makes really, really good wines, especially some nice, uh, Pinot Noirs and some good white wines. Uhm, Okanagan Valley, check it out.


[User] Please transcribe this text

[Assistant] Yeah, so visit our website, EnglishPod.com. Leave all your comments. Tell us about how you welcome people into your house.


[User] Please transcribe this text

[Assistant] Your house is lovely, Armand. Very interesting decor. Very... gothic.


[User] Please transcribe this text

[Assistant] It's a bit bitter for my taste. Almost tastes like... like...


[User] Please transcribe this text

[Assistant] Haha, you're so clever, boss. Hahaha. Okay, shut up.


[User] Please transcribe this text

[Assistant] Haha, you're so clever, boss. Hahaha. Okay, shut up.


[User] Please transcribe this text

[Assistant] I finally got a Nintendo Wii! Come on, help me hook it up to the TV.


[User] Please transcribe this text

[Assistant] Well, good advice, Marco. And, and our last word in vocabulary preview, malfunction. Malfunction. Malfunction. Malfunction. Malfunction. Let's break down this word. Alright. Function.


[User] Please transcribe this text

[Assistant] Okay, more or less, it's not working properly.


[User] Please transcribe this text

[Assistant] Okay, well why don't we listen to the dialogue and find out what isn't working properly.


[User] Please transcribe this text

[Assistant] Alright, three words for you here in Language Takeaway, and we heard all of these in the dialogue.


[User] Please transcribe this text

[Assistant] So this guy needs to get a copy ASAP.


[User] Please transcribe this text

[Assistant] So it's an acronym and you can say it like ASAP or


[User] Please transcribe this text

[Assistant] Yeah, uhm, but something crazy. Crazy, right? For example, when I was in university, uh, there was this guy in our, in our building, and we took all of his bedroom furniture, so his bed, his desk, everything, and put it down on the football field.


[User] Please transcribe this text

[Assistant] Yeah, this is a, you know, this is so common and I think it would be helpful to understand how it's used. So let's hear some examples.


[User] Please transcribe this text

[Assistant] Yeah, so if you break into a house maybe you break the window and climb in. Okay. What about break out? The opposites. Right.


[User] Please transcribe this text

[Assistant] So for example, you might break out of jail.


[User] Please transcribe this text

[Assistant] You are much, uhm, better at computers and technology than I am.


[User] Please transcribe this text

[Assistant] That's right, you can find us at EnglishPod.com and Marco and I are always around. Alright, so we'll see you guys there. Yep, we will.


[User] Please transcribe this text

[Assistant] Okay guys, thanks for listening and until next time. Bye.


[User] Please transcribe this text

[Assistant] First time.


[User] Please transcribe this text

[Assistant] Well, in a professional kitchen, uhm, this is the boss of the kitchen, or the leader of the kitchen.


[User] Please transcribe this text

[Assistant] Well, uhm, we're in a restaurant, uhm, and it's a really busy night, and so we're going to listen to what is happening in the kitchen.


[User] Please transcribe this text

[Assistant] Alright, well we've got five words for you today, uh, and the first one is peel.


[User] Please transcribe this text

[Assistant] Potatoes, like in the dialogue. Uh, what else can you peel? I don't know, carrots.


[User] Please transcribe this text

[Assistant] It means to cut food into pieces.


[User] Please transcribe this text

[Assistant] You move the spoon around in circles. So you're stirring the pot.


[User] Please transcribe this text

[Assistant] Again, the past participle of the verb butcher.


[User] Please transcribe this text

[Assistant] I know, uhm, normally we all know the noun butter, but here it's acting as a verb. Okay. So when you butter something, you spread or put butter on it.


[User] Please transcribe this text

[Assistant] And hey, I noticed that there's a lot of really great kitchen words in here, like words that you commonly hear in a professional kitchen.


[User] Please transcribe this text

[Assistant] Alright, we've got three phrases. Uh, and the first one is in the weeds.


[User] Please transcribe this text

[Assistant] So when you're in the weeds, you're so, so busy and you can't do all the work you need to do on time.


[User] Please transcribe this text

[Assistant] So here, they're running low on wine, so basically


[User] Please transcribe this text

[Assistant] Doing really well. So this seems to be like a pretty simple structure. I mean, we know all these words, right? So why is it special?


[User] Please transcribe this text

[Assistant] But in this situation, in the dialogue, what's doing really well?


[User] Please transcribe this text

[Assistant] So when he says we're doing really well, uhm, business is...


[User] Please transcribe this text

[Assistant] Alright, well, let's listen to the dialogue, uh, one last time, and we'll be able to hear all of these great words and phrases we just talked about.


[User] Please transcribe this text

[Assistant] So Marco, do you think this chef had a rat under his hat?


[User] Please transcribe this text

[Assistant] Me too, actually. You know, if I'm in a bad mood, I go home and cook something to eat and the world seems a happier place.


[User] Please transcribe this text

[Assistant] Yes, uhm, to test out your recipes as well as answer questions.


[User] Please transcribe this text

[Assistant] We will demonstrate the concept of machine athleticism and a research to achieve it with the help of these flying machines called quadricopters or quads for short.


[User] Please transcribe this text

[Assistant] The reason that they're so popular these days is because they're mechanically simple.


[User] Please transcribe this text

[Assistant] By controlling the speeds of these four propellers, these machines can roll, pitch, yaw, and accelerate along their common orientation. Onboard are also a battery, a computer, various sensors, and wireless radios.


[User] Please transcribe this text

[Assistant] Quads are extremely agile, but sagility comes at a cost.


[User] Please transcribe this text

[Assistant] They are inherently unstable and they need some form of automatic feedback control in order to be able to fly.


[User] Please transcribe this text

[Assistant] Cameras on the ceiling and a laptop serve as an indoor global positioning system.


[User] Please transcribe this text

[Assistant] It's used to locate objects in the space that have these reflective markers on them.


[User] Please transcribe this text

[Assistant] This data is then sent to another laptop that is running estimation and control algorithms, which in turn sends commands to the quad, which is also running estimation and control algorithms.


[User] Please transcribe this text

[Assistant] The bulk of our research is algorithms. It's the magic that brings these machines to life.


[User] Please transcribe this text

[Assistant] So how does one design the algorithms that create a machine athlete? We use something broadly called model-based design.


[User] Please transcribe this text

[Assistant] We first capture the physics with a mathematical model of how the machines behave. We then use a branch of mathematics called control theory to analyze these models and also to synthesize algorithms for controlling them.


[User] Please transcribe this text

[Assistant] For example, that's how we can make the quad hover. We first capture the dynamics with a set of differential equations. We then manipulate these equations with the help of control theory to create algorithms that stabilize the quad. Let me demonstrate the strength of this approach.


[User] Please transcribe this text

[Assistant] Suppose that we want this quad to not only hover, but to also balance this pole. With a little bit of practice,


[User] Please transcribe this text

[Assistant] It's pretty straightforward for a human being to do this. Although we do have the advantage of having two feet on the ground and the use of our very versatile hands. It becomes a little bit more difficult.


[User] Please transcribe this text

[Assistant] When I only have one foot on the ground, and when I don't use my hands.


[User] Please transcribe this text

[Assistant] Notice how this pole has a reflective marker on top, which means that it can be located in the space.


[User] Please transcribe this text

[Assistant] You can notice that this quad is making fine adjustments to keep the pole balanced. How do we design the algorithms to do this?


[User] Please transcribe this text

[Assistant] We added the mathematical model of the pole to that of the quad. Once we have a model of the combined quad pole system, we can use control theory to create algorithms for controlling it.


[User] Please transcribe this text

[Assistant] Here you see that it's stable, and even if I give it little nudges, it goes back.


[User] Please transcribe this text

[Assistant] We can also augment the model to include where we want the quad to be in space.


[User] Please transcribe this text

[Assistant] Using this pointer made out of reflective markers, I can point to where I want the quad to be in space a fixed distance away from me.


[User] Please transcribe this text

[Assistant] The key to these acrobatic maneuvers is algorithms, designed with the help of mathematical models and control theory.


[User] Please transcribe this text

[Assistant] Let's tell the quad to come back here and let the pole drop.


[User] Please transcribe this text

[Assistant] And I will next demonstrate the importance of understanding physical models and the workings of the physical world.


[User] Please transcribe this text

[Assistant] Notice how the quad lost altitude when I put this glass of water on it. Unlike the balancing pole, I did not include the mathematical model of the glass in the system. In fact, the system doesn't even know that the glass of water is there. Like before, I could use the pointer to tell the quad where I want to be in space.


[User] Please transcribe this text

[Assistant] Okay, you should be asking yourself, why doesn't the water fall out of the glass?


[User] Please transcribe this text

[Assistant] Two facts. The first is that gravity acts on all objects in the same way. The second is that the propellers are all pointing in the same direction of the glass, pointing up.


[User] Please transcribe this text

[Assistant] You put these two things together, the net result is that all side forces on the glass are small and are mainly dominated by aerodynamic effects, which at these speeds are negligible.


[User] Please transcribe this text

[Assistant] That's why you don't need to model the glass. It naturally doesn't spill, no matter what the quad does.


[User] Please transcribe this text

[Assistant] The lesson here is that some high performance, uh, tasks are easier than others and that understanding the physics of the problem tells you which ones are easy and which ones are hard. In this instance, carrying a glass of water is easy, balancing a pole is hard.


[User] Please transcribe this text

[Assistant] We've all heard stories of athletes performing feats while physically injured. Can a machine also perform with extreme physical damage?


[User] Please transcribe this text

[Assistant] Conventional wisdom says that you need at least four fixed motor propeller pairs in order to fly, because there are four degrees of freedom to control. Roll, pitch, yaw, and acceleration.


[User] Please transcribe this text

[Assistant] Hexacopters and octocopters with six and eight propellers can provide redundancy, but quadricopters are much more popular because they have the minimum number of fixed motor propeller pairs. Four. Or do they?


[User] Please transcribe this text

[Assistant] If we analyze the mathematical model of this machine with only two working propellers, we discover that there's an unconventional way to fly it.


[User] Please transcribe this text

[Assistant] We relinquish control of yeaah, but roll, pitch, and acceleration can still be controlled with algorithms that exploit this new configuration.


[User] Please transcribe this text

[Assistant] Mathematical models tell us exactly when and why this is possible. In this instance, this knowledge allows us to design novel machine architectures.


[User] Please transcribe this text

[Assistant] Or to design clever algorithms that gracefully handle damage, just like human athletes do, instead of building machines with redundancy.


[User] Please transcribe this text

[Assistant] We can't help but hold our breath when we watch a diver somersaulting into the water, or when a vaulter is twisting in the air, the ground fast approaching. Will the diver be able to pull off a rip entry? Will the vaulter stick the landing?


[User] Please transcribe this text

[Assistant] Suppose we want this quad here to perform a triple flip and finish off at the exact same spot that it started.


[User] Please transcribe this text

[Assistant] This maneuver is going to happen so quickly that we can't use position feedback to correct the motion during execution. There simply isn't enough time.


[User] Please transcribe this text

[Assistant] Instead, what the quad can do is perform the maneuver blindly, observe how it finishes the maneuver,


[User] Please transcribe this text

[Assistant] And then use that information to modify its behavior so that the next flip is better.


[User] Please transcribe this text

[Assistant] Similar to the diver and the vaulter, it is only through repeated practice that the maneuver can be learned and executed to the highest standard.


[User] Please transcribe this text

[Assistant] Striking a moving ball is a necessary skill in many sports. How do we make a machine do what an athlete does seemingly without effort?


[User] Please transcribe this text

[Assistant] This quad has a racket strapped onto its head with a sweet spot roughly the size of an apple, so not too large.


[User] Please transcribe this text

[Assistant] The following calculations are made every 20 milliseconds or 50 times per second. We first figure out where the ball is going.


[User] Please transcribe this text

[Assistant] We then next calculate how the quad should hit the ball so that it flies to where it was thrown from. Third, a trajectory is planned, uh, that carries the quad from its current state to the impact point with the ball. Fourth, we only execute 20 milliseconds worth of that strategy.


[User] Please transcribe this text

[Assistant] 20 milliseconds later, the whole process is repeated until the quad strikes the ball.


[User] Please transcribe this text

[Assistant] Machines can not only perform dynamic maneuvers on their own, they can do it collectively.


[User] Please transcribe this text

[Assistant] These three quads are cooperatively carrying a Skynet.


[User] Please transcribe this text

[Assistant] They perform an extremely dynamic and uh, collective maneuver to launch the ball back to me. Notice that at full extension, these quads are vertical.


[User] Please transcribe this text

[Assistant] In fact, when fully extended, this is roughly five times greater than what a bungee jumper feels at the end of their launch.


[User] Please transcribe this text

[Assistant] The algorithms to do this are very similar to what the single quad used to hit the ball back to me.


[User] Please transcribe this text

[Assistant] Mathematical models are used to continuously re-plan a cooperative strategy 50 times per second.


[User] Please transcribe this text

[Assistant] Everything we have seen so far has been about the machines and their capabilities.


[User] Please transcribe this text

[Assistant] What happens when we couple this machine athleticism with that of a human being? What I have in front of me is a commercial gesture sensor


[User] Please transcribe this text

[Assistant] Mainly used in gaming. It can recognize what my various body parts are doing in real time.


[User] Please transcribe this text

[Assistant] Similar to the pointer that I used earlier, we can use this as inputs to the system. We now have a natural way of interacting with the Roth lettuces of these quads with my gestures.


[User] Please transcribe this text

[Assistant] Interaction doesn't have to be virtual, it can be physical. Take this quad for example. It's trying to stay at a fixed point in space. If I try to move it out of the way, it fights me and moves back to where it wants to be.


[User] Please transcribe this text

[Assistant] We can use mathematical models to estimate the force that I'm applying to the quad. Once we know this force, we can also change the laws of physics. As far as the quad is concerned, of course.


[User] Please transcribe this text

[Assistant] Here the quad is behaving as if it were in a viscous fluid.


[User] Please transcribe this text

[Assistant] We now have an intimate way of interacting with a machine.


[User] Please transcribe this text

[Assistant] I will use this new capability to position this camera carrying quad to the appropriate location for filming the remainder of this demonstration.


[User] Please transcribe this text

[Assistant] So we can physically interact with these quads, and we can change the laws of physics. Let's have a little bit of fun with this.


[User] Please transcribe this text

[Assistant] For what you will see next, these quads will initially behave as if they were on Pluto.


[User] Please transcribe this text

[Assistant] As time goes on, gravity will be increased until we're all back on planet Earth. But I assure you, we won't get there. Okay, here goes.


[User] Please transcribe this text

[Assistant] And you're probably also asking yourself, why exactly are they building machine athletes?


[User] Please transcribe this text

[Assistant] Some conjecture that the role of play in the animal kingdom is to hone skills and develop capabilities. Others think that it has more of a social role, that it's used to bind the group.


[User] Please transcribe this text

[Assistant] Similarly, we use the analogy of sports and athleticism to create new algorithms for machines to push them to their limits. What impact will this beta machine have on our way of life?


[User] Please transcribe this text

[Assistant] Like all our past creations and innovations, they may be used to improve the human condition, or they may be misused and abused. This is not a technical choice we are faced with, it's a social one.


[User] Please transcribe this text

[Assistant] Let's make the right choice, the choice that brings out the best in the future of machines, just like athleticism and sports can bring out the best in us.


[User] Please transcribe this text

[Assistant] Let me introduce you to the wizards behind the green curtain. They're the current members of the Fly Machina research team.


[User] Please transcribe this text

[Assistant] Federico Albuliaro, Dario Brascianini, Marcus Henn, Sergey Lupashen, Mark Muller, and Robin Ritz. Look out for them, they're destined for great things. Thank you.


[User] Please transcribe this text

[Assistant] Uhm, I don't think so. I need the car tonight to pick up your mother.


[User] Please transcribe this text

[Assistant] Mmmm, I don't think so. I need the car tonight to pick up your mother.


[User] Please transcribe this text

[Assistant] Uhm, I don't think so. I need the car tonight to pick up your mother.


[User] Please transcribe this text

[Assistant] That's right. Um, and who knew there was so much to talk about when we're talking eggs.


[User] Please transcribe this text

[Assistant] Yes, and we'll learn some of the language that goes along with eggs.


[User] Please transcribe this text

[Assistant] Our preview word for this lesson is picky, picky, picky.


[User] Please transcribe this text

[Assistant] So picky is an interesting adjective.


[User] Please transcribe this text

[Assistant] Yeah, he'll say, do it again. Change this, this, and this.


[User] Please transcribe this text

[Assistant] So if you are picky, uhm, you want everything to be perfect.


[User] Please transcribe this text

[Assistant] And if there's one small thing that's not, you won't, you won't be happy.


[User] Please transcribe this text

[Assistant] Okay, yeaah, the yolk is still yellow, it's still a little bit, uh, liquid, it's a little bit soft.


[User] Please transcribe this text

[Assistant] Right, the yoke, the yellow part stays a little bit wet, a little bit liquid.


[User] Please transcribe this text

[Assistant] Well, this is a very British, uhm, way of eating eggs. So, you have your soft boiled egg in a cup, and you have a piece of toast.


[User] Please transcribe this text

[Assistant] But the toast is cut into long pieces.


[User] Please transcribe this text

[Assistant] And then you take those pieces and you dip them into the egg yolk.


[User] Please transcribe this text

[Assistant] Right, I feel like eating lunch.


[User] Please transcribe this text

[Assistant] Mmhm, traditional, uhm, American type breakfast.


[User] Please transcribe this text

[Assistant] I know, I think, I'm not sure if this is just in my family, but I think actually it might be, it might be common, uhm, with other people as well. Uhm, when you eat a soft boiled or hard boiled egg,


[User] Please transcribe this text

[Assistant] You have to, you know, eat all of the egg outside of the shell, and then you have to break the bottom of the shell after you've finished.


[User] Please transcribe this text

[Assistant] Visit our website at EnglishPod.com where you can leave all of your comments and questions.


[User] Please transcribe this text

[Assistant] Would you mind cooking dinner tonight? I'll be home late.


[User] Please transcribe this text

[Assistant] What? Why? I mean, just like that. I'm fired?


[User] Please transcribe this text

[Assistant] Oh, were you talking to me, honey? I'm sorry. I'm just really preoccupied with work.


[User] Please transcribe this text

[Assistant] What? Why? I mean, just like that, I'm fired?


[User] Please transcribe this text

[Assistant] One thing that I want to tell you, uhm, it's so important that


[User] Please transcribe this text

[Assistant] I don't like, they, I always, sometimes when


[User] Please transcribe this text

[Assistant] Alright, here's the deal. This is it. Specifically...


[User] Please transcribe this text

[Assistant] It's not this, it's not that, it's not you, it's not me. It's everyone! It's everything! You understand what I'm saying?


[User] Please transcribe this text

[Assistant] What? Why? I mean, just like that, I'm fired?


[User] Please transcribe this text

[Assistant] We've been over this a thousand times. The data is irrefutable. Look, we've done extensive research, built studies and read the literature, and there is conclusive evidence to support my theory. Horrible.


[User] Please transcribe this text

[Assistant] We have your test results back and, indeed, you are pregnant. Let's see here. Everything seems to be in order. Your approximate due date is October 27th, 2009, so that means the baby was conceived on February 3rd, 2009.


[User] Please transcribe this text

[Assistant] We have your test results back, and indeed, you are pregnant. Let's see here.


[User] Please transcribe this text

[Assistant] Everything seems to be in order. Your approximate due date is October 27, 2009. So that means the baby was conceived on February 3, 2009. Are you sure? Are these things accurate?


[User] Please transcribe this text

[Assistant] We have your test results back and, indeed, you are pregnant.


[User] Please transcribe this text

[Assistant] Let's see here. Everything seems to be in order. Your approximate due date is October 27th, 2009. So that means the baby was conceived on February 3rd, 2009.


[User] Please transcribe this text

[Assistant] Here is Mr. Fox. Mmm! This all looks very interesting.


[User] Please transcribe this text

[Assistant] And, you've got the best chief mechanic in the whole world too.


[User] Please transcribe this text

[Assistant] But now it's time for grandpa to take you home.


[User] Please transcribe this text

[Assistant] Had he been racing against the winner of the 1904 Olympic Marathon, he would have won by nearly an hour and a half.


[User] Please transcribe this text

[Assistant] Now, we all have this feeling that we're somehow just getting better as a human race, inexorably progressing. But it's not like we've evolved into a new species in a century. So, what's going on here? I want to take a look at what's really behind this march of athletic progress.


[User] Please transcribe this text

[Assistant] In 1936, Jesse Owens held the world record in the 100 meters. Had Jesse Owens been racing last year in the world championships of the 100 meters? When Jamaican sprinter Usain Bolt finished, Owens would have still had 14 feet to go. That's a lot in sprinterland. To give you a sense of how much it is, I want to share with you a demonstration conceived by sports scientist Ross Tucker.


[User] Please transcribe this text

[Assistant] Now, picture the stadium last year at the World Championships of the 100 meters.


[User] Please transcribe this text

[Assistant] Flashbulbs popping as the nine fastest men in the world coil themselves into their blocks. And I want you to pretend that Jesse Owens is in that race. Now close your eyes for a second and picture the race. Bang! The gun goes off. An American sprinter jumps out to the front


[User] Please transcribe this text

[Assistant] That's the entire finish of the race. You can open your eyes now. That first beep was Usain Bolt. That last beep was Jesse Owens. Listen to it again.


[User] Please transcribe this text

[Assistant] And then consider that Usain Bolt started by propelling himself out of blocks, down a specially fabricated carpet.


[User] Please transcribe this text

[Assistant] Designed to allow him to travel as fast as humanly possible. Jesse Owens, on the other hand, ran on cinders, the ash from burnt wood.


[User] Please transcribe this text

[Assistant] And that soft surface stole far more energy from his legs as he ran.


[User] Please transcribe this text

[Assistant] Biomechanical analysis of the speed of Owens' joints shows that had he been running on the same surface as Bolt, he wouldn't have been 14 feet behind. He would have been within one stride. Rather than the last beep, Owens would have been the second beep. Listen to it again.


[User] Please transcribe this text

[Assistant] That's the difference track surface technology has made, and it's done it throughout the running world. Consider a longer event.


[User] Please transcribe this text

[Assistant] In 1954, Sir Roger Bannister became the first man to run under four minutes in the mile. Nowadays, college kids do that every year. On rare occasions, a high school kid does it. As of the end of last year,


[User] Please transcribe this text

[Assistant] Sir Roger Bannister ran on soft cinders that stole far more energy from his legs than the synthetic tracks of today.


[User] Please transcribe this text

[Assistant] So I consulted biomechanics experts to find out how much slower it is to run on cinders than synthetic tracks, and their consensus was that it's one and a half percent slower. So if you apply a one and a half percent slowdown conversion to every man who ran his sub-four mile on a synthetic track, this is what happens. Only 530 are left.


[User] Please transcribe this text

[Assistant] If you look at it from that perspective, fewer than 10 new men per decade have joined the Sub Four Mile Club since Sir Roger Bannister. Now, 530 is a lot more than one.


[User] Please transcribe this text

[Assistant] Who trained for 45 minutes at a time while he ditched gynecology lectures in med school.


[User] Please transcribe this text

[Assistant] That guy was drinking rat poison and brandy while he ran along the course. That was his idea of a performance enhancing drug.


[User] Please transcribe this text

[Assistant] And that's made a difference in some sports at some times, but technology has made a difference in all sports, from faster skis to lighter shoes. Take a look at the record for the 100 meter freestyle swim. The record is always trending downward, but it's punctuated by these steep cliffs.


[User] Please transcribe this text

[Assistant] This first cliff in 1956 is the introduction of the flip turn.


[User] Please transcribe this text

[Assistant] Rather than stopping and turning around, athletes could somersault under the water and get going right away in the opposite direction. This second cliff


[User] Please transcribe this text

[Assistant] The introduction of gutters on the side of the pool that allows water to splash off rather than becoming turbulence that impedes the swimmers as they race. This final cliff, the introduction of full body and low friction swimsuits. Throughout sports, technology has changed the face of performance.


[User] Please transcribe this text

[Assistant] Now that record improved and improved as bicycles improved and became more aerodynamic.


[User] Please transcribe this text

[Assistant] Still, technology isn't the only thing pushing athletes forward. While indeed we haven't evolved into a new species in a century, the gene pool within competitive sports most certainly has changed. In the early half of the 20th century,


[User] Please transcribe this text

[Assistant] Physical education instructors and coaches had the idea that the average body type was the best for all athletic endeavors. Medium height, medium weight, no matter the sport. And this showed in athletes' bodies.


[User] Please transcribe this text

[Assistant] In the 1920s, the average elite high jumper and average elite shot putter were the same exact size. But as that idea started to fade away,


[User] Please transcribe this text

[Assistant] As sports scientists and coaches realize that rather than the average body type, you want highly specialized bodies that fit into certain athletic niches.


[User] Please transcribe this text

[Assistant] In fact, if you plot on a height versus mass graph one data point for each of two dozen sports in the first half of the 20th century, it looks like this.


[User] Please transcribe this text

[Assistant] There's some dispersal, but it's kind of grouped around that average body type.


[User] Please transcribe this text

[Assistant] Then that idea started to go away, and at the same time, digital technology, first radio, then television and the internet, gave millions or in some cases billions of people a ticket to consume elite sports performance.


[User] Please transcribe this text

[Assistant] The financial incentives and fame and glory afforded elite athletes skyrocketed. And it tipped toward the tiny upper echelon of performance.


[User] Please transcribe this text

[Assistant] And if you plot a data point for these same two dozen sports today, it looks like this. The athlete's bodies have gotten much more different from one another.


[User] Please transcribe this text

[Assistant] And because this chart looks like the charts that show the expanding universe, with the galaxies flying away from one another,


[User] Please transcribe this text

[Assistant] The scientists who discovered it call it the big bang of body types.


[User] Please transcribe this text

[Assistant] In 1983, the National Basketball Association signed a groundbreaking agreement, making players partners in the league, entitled to shares of ticket revenues and television contracts. Suddenly, anybody who could be an NBA player wanted to be.


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[Assistant] And teams started scouring the globe for the bodies that could help them win championships. Almost overnight, the proportion of men in the NBA who were at least seven feet tall doubled to 10 percent.


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[Assistant] But a seven foot tall man is incredibly rare in the general population. So rare.


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[Assistant] There's a 17 percent chance he's in the NBA right now.


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[Assistant] That is, find six honest seven-footers. One is in the NBA right now. And that's not the only way that NBA players' bodies are unique. This is Leonardo da Vinci's Vitruvian Man.


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[Assistant] The ideal proportions? With arm span equal to height? My arm span is exactly equal to my height. Yours is probably very nearly so. But not the average NBA player.


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[Assistant] The average NBA player is a shade under six foot seven, with arms that are seven feet long. Not only are NBA players ridiculously tall, they are ludicrously long.


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[Assistant] Conversely, in sports where diminutive stature is an advantage, the small athletes got smaller.


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[Assistant] The average elite female gymnast shrunk from five foot three to four foot nine on average over the last 30 years. All the better for their power to weight ratio and for spinning in the air.


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[Assistant] And while the large got larger and the small got smaller, the weird got weirder.


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[Assistant] The average length of the forearm of a water polo player in relation to their total arm got longer. All the better for a forceful throwing whip.


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[Assistant] The ideal body type is a long torso and short legs. It's like the long hull of a canoe for speed over the water.


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[Assistant] And the opposite is advantageous in running. You want long legs and a short torso. And this shows in athletes' bodies today.


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[Assistant] Here you see Michael Phelps, the greatest swimmer in history.


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[Assistant] Standing next to Hisham El-Gurouj, the world record holder in the mile. These men are seven inches different in height. But because of the body types advantaged in their sports, they wear the same length pants. Seven inches difference in height, these men have the same length legs.


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[Assistant] Now, in some cases, the search for bodies that could push athletic performance forward ended up introducing into the competitive world populations of people that weren't previously competing at all, like Kenyan distance runners. But we think of Kenyans as being great marathoners.


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[Assistant] Kenyans think of the Kalenjin tribe as being great marathoners.


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[Assistant] The Kalenjin make up just 12% of the Kenyan population, but the vast majority of elite runners. And they happen on average to have a certain unique physiology. Legs that are very long and very thin at their extremity.


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[Assistant] And this is because they have their ancestry at very low latitude in a very hot and dry climate.


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[Assistant] And an evolutionary adaptation to that is limbs that are very long and very thin at the extremity for cooling purposes. It's the same reason that a radiator has long coils to increase surface area compared to volume to let heat out.


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[Assistant] And because the leg is like a pendulum, the longer and thinner it is at the extremity, the more energy efficient it is to swing. To put calendar and running success in perspective, consider that 17 American men in history


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[Assistant] Have run faster than two hours and ten minutes in the marathon. That's a four minute and 58 second per mile pace. 32 Kalenjin men did that last October.


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[Assistant] Still, even changing technology and the changing gene pool in sports don't account for all of the changes in performance. Athletes have a different mindset than they once did. Have you ever seen in a movie when someone gets an electrical shock and they're thrown across a room? There's no explosion there.


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[Assistant] What's happening when that happens is that the electrical impulse is causing all their muscle fibers to twitch at once. And they're throwing themselves across the room. They're essentially jumping. That's the power that's contained in the human body.


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[Assistant] But normally we can't access nearly all of it. Our brain acts as a limiter.


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[Assistant] Preventing us from accessing all of our physical resources, because we might hurt ourselves, tearing tendons or ligaments. But the more we learn about how that limiter functions, the more we learn how we can push it back just a bit. In some cases,


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[Assistant] By convincing the brain that the body won't be in mortal danger by pushing harder. Endurance and ultra endurance sports serve as a great example. Ultra endurance was once thought to be harmful to human health.


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[Assistant] No body fur and a glut of sweat glands that keep us cool while running.


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[Assistant] Narrow waists and long legs compared to our frames. Large surface area of joints for shock absorption.


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[Assistant] And when we run, we can turn our torso and our shoulders, like this, while keeping our heads straight. Our primate cousins can't do that. They have to run like this.


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[Assistant] And as athletes have realized that we're perfectly suited for ultra endurance, they've taken on feats that would have been unthinkable before. Athletes like Spanish endurance racer Kilian Jornet. Here's Kilian running up the Matterhorn.


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[Assistant] With a sweatshirt there tied around his waist. He's, it's so steep he can't even run here, he's pulling up on a rope. This is a vertical ascent of more than 8,000 feet.


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[Assistant] And talented though he is, Kilian is not a physiological freak. Now that he has done this,


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[Assistant] Other athletes will follow, just as other athletes followed after Sir Roger Bannister ran under four minutes in the mile. Changing technology, changing genes and a changing mindset. Innovation in sports.


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[Assistant] Whether that's new track surfaces or new swimming techniques, the democratization of sport, the spread to new bodies and to new populations around the world, and imagination in sport.


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[Assistant] An understanding of what the human body is truly capable of have conspired to make athletes stronger, faster, bolder and better than ever. Thank you very much.


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[Assistant] No, it's against the law. What are you talking about, Pedro?


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[Assistant] Reports from Egypt say democracy activists have been attacked by men in plain clothes armed with knives outside the offices of the interior ministry in Cairo.


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[Assistant] Over the weekend activists stormed several offices of the secret police.


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[Assistant] The newly appointed US Special Envoy for Afghanistan and Pakistan, Mark Grossman, has stressed the importance of pursuing a diplomatic settlement in Afghanistan alongside military operations.


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[Assistant] During his first visit to Kabul, he said the United States supported the Afghan government's move toward talks with the Taliban, but he said it was important that the Taliban end its alliance with al-Qaeda.


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[Assistant] Reports from Egypt say democracy activists have been attacked by men in plain clothes armed with knives outside the offices of the interior ministry in Cairo.


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[Assistant] Over the weekend activists stormed several offices of the secret police.


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[Assistant] The newly appointed US Special Envoy for Afghanistan and Pakistan, Mark Grossman, has stressed the importance of pursuing a diplomatic settlement in Afghanistan alongside military operations.


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[Assistant] During his first visit to Kabul, he said the United States supported the Afghan government's move toward talks with the Taliban. But he said it was important that the Taliban end its alliance with al-Qaeda.


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[Assistant] Uhm, she has filled out a bit, hasn't she?


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[Assistant] Here is Mr Zebra, the postman. A postcard, all the way from Italy.


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[Assistant] The commander of NATO forces in Afghanistan, General David Petros, has issued a personal apology for the killing of nine young boys in Kunar province on Tuesday.


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[Assistant] Local Afghan officials say the boys aged 12 or younger had been gathering firewood when helicopter gunships attacked them with rockets. NATO says there was a mistake in relaying information about the position of presumed militants who were firing at a NATO base.


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[Assistant] The international development secretary, Andrew Mitchell, told parliament that he wanted to concentrate the money where it would do most good.


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[Assistant] Nations like Lesotho and Kosovo will lose direct funding, but others like Ethiopia and Bangladesh will receive more aid from the Department for International Development or DEFID.


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[Assistant] The commander of NATO forces in Afghanistan, General David Petros, has issued a personal apology for the killing of nine young boys in Kunar province on Tuesday.


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[Assistant] Local Afghan officials say the boys aged 12 or younger had been gathering firewood when helicopter gunships attacked them with rockets. NATO says there was a mistake in relaying information about the position of presumed militants who were firing at a NATO base.


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[Assistant] Britain is to end its international aids to 16 countries.


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[Assistant] The international development secretary, Andrew Mitchell, told parliament that he wanted to concentrate the money where it would do most good.


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[Assistant] Nations like Lesotho and Kosovo will lose direct funding, but others like Ethiopia and Bangladesh will receive more aid from the Department for International Development or DEFID.


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[Assistant] Western leaders have been discussing ways to increase pressure on the Libyan leader, Colonel Gaddafi, to stop him killing the people rebelling against him and persuade him to step down.


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[Assistant] The Pentagon in Washington says it's repositioning naval and air forces around Libya so that there's flexibility for action should government planners require it. News item 26.


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[Assistant] Two of Argentina's former military rulers have gone on trial accused of overseeing the systematic theft of babies from political prisoners.


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[Assistant] Jorge Vedea and Ronaldo Bigione are accused of kidnapping about 30 babies whose parents were killed or disappeared during military rule.


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[Assistant] The babies were then given for adoption to members of the Argentine military or their allies. Both former leaders are already serving long sentences for murder and torture.


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[Assistant] That's right, we're talking about my least favorite subject.


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[Assistant] Many people find it hard to find the right words to talk about math in English. Right, so that's what we're going to be looking at today. And we'll also look at some names that you can call people who are really, really, really smart.


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[Assistant] Okay, so like we said, you guys know how to do math and you know the words in your language, but maybe in English it's a little bit harder to find the right words. So let's look at those now.


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[Assistant] So let's give some examples to show what is the square root.


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[Assistant] Exactly. So this language, uhm, is pretty simple. You all know it in your own language, but let's hear it again in English one more time with the dialogue.


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[Assistant] It is the favorite student the teacher has in that class.


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[Assistant] And similar to teacher's pet is a suck up.


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[Assistant] A suck up is a person who tries really, really hard to make the teacher like him.


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[Assistant] Alright, so the teacher calls Crystal a smartypants.


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[Assistant] Yeah, but if you say it, you are, um, suggesting that you're being like a child.


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[Assistant] Somebody who, uhm, tries to show everyone that they know it all.


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[Assistant] Well, yes, that's true. I really do hate math and even, even doing a simple uhm, you know, like 16 plus 32.


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[Assistant] That's right. Well, thanks for downloading this lesson and until next time, goodbye.


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[Assistant] I have spent my entire life either at the schoolhouse, on the way to the schoolhouse, or talking about what happens in the schoolhouse.


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[Assistant] Both my parents were educators. My maternal grandparents were educators. And for the past 40 years, I've done the same thing.


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[Assistant] And so needless to say, over those years, I've had a chance to look at education reform from a lot of perspectives. Some of those reforms have been good, some of them have been not so good.


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[Assistant] And we know why kids drop out. We know why kids don't learn. It's either poverty, low attendance, negative peer influences. We know why.


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[Assistant] But one of the things that we never discuss or we rarely discuss is the value and importance of human connection. Relationships.


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[Assistant] James Comer says that no significant learning can occur without a significant relationship.


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[Assistant] George Washington Carver says all learning is understanding relationships.


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[Assistant] For years, I have watched people teach. I have looked at the best and I've looked at some of the worst. A colleague said to me one time, they don't pay me to like the kids. They pay me to teach a lesson. The kids should learn it. I should teach it. They should learn it case closed. Well, I said to her, you know, kids don't learn from people they don't like.


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[Assistant] I think Stephen Covey had the right idea. He said you oughta just throw in a few simple things. Like seeking first to understand as opposed to being understood. Simple things like apologizing.


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[Assistant] So I came back to class the next day and I said, look guys, I need to apologize. I taught the whole lesson wrong. I'm so sorry.


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[Assistant] I said, that's okay, Ms. Pearson. You were so excited. We just let you go.


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[Assistant] So academically deficient that I cried.


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[Assistant] I wondered how am I going to take this group in nine months from where they are to where they need to be. And it was difficult. It was, it was awfully hard.


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[Assistant] How do I raise the self-esteem of a child and his academic achievement at the same time?


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[Assistant] One year I came up with a bright idea. I told all my students, you were chosen to be in my class.


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[Assistant] Because I am the best teacher and you are the best students. They put us all together so we could show everybody else how to do it. One of the students said, really?


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[Assistant] I say really, we have to show the other classes how to do it. So when we walk down the hall, people will notice us. So you can't make noise, you just have to strut.


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[Assistant] And I gave them a saying to say, I am somebody. I was somebody when I came. I'll be a better somebody when I leave. I am powerful and I am strong. I deserve the education that I get here. I have things to do, people to impress and places to go. And they said, yeaah.


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[Assistant] He said, yes ma'am, I can do better. You see, minus 18 sucks all the life out of you. Plus two said I ain't all bad.


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[Assistant] Four years I watched my mother. Take the time at recess to review.


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[Assistant] Go on home visits in the afternoon. Buy combs and brushes and peanut butter and crackers to put in a desk drawer for kids that needed to eat and a washcloth and some soap for the kids who didn't smell so good. See, it's hard to teach kids who stink.


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[Assistant] And so she kept those things in her desk and years later after she retired, I watched some of those same kids come through and say to her, you know, Ms. Walker, you made a difference in my life.


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[Assistant] You made it work for me. You made me feel like I was somebody when I knew at the bottom I wasn't.


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[Assistant] And I want you to just see what I've become. And when my mama died two years ago at 92.


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[Assistant] There were so many former students at her funeral, it brought tears to my eyes, not because she was gone, but because she left the legacy of relationships that could never disappear.


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[Assistant] Can we stand to have more relationships? Absolutely. Will you like all your children? Of course not.


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[Assistant] You won't like them all and, and, and the tough ones show up for a reason. It's the connection. It's the relationships. And while you won't like them all, the key is they can never ever know.


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[Assistant] So teachers become great actors and great actresses and we come to work when we don't feel like it and we listen to policy that doesn't make sense and we teach anyway.


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[Assistant] We teach anyway because that's what we do. Teaching and learning should bring joy.


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[Assistant] How powerful would our world be if we had kids who were not afraid to take risks, who were not afraid to think, and who had a champion every child?


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[Assistant] Deserves the champion, an adult who will never give up on them, who understands the power of connection and insist that they become the best that they can possibly be. Is this job tough? You betcha. Oh God, you betcha. But it is not impossible.


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[Assistant] Hello, welcome to Universal Bank. Please insert your card into the slot.


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[Assistant] Please input your six digit pin code followed by the pound key. Thank you. Please select an option. Thank you. You have selected withdraw.


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[Assistant] Please type the amount you would like to withdraw Thank you. You want to transfer.


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[Assistant] 10,000 U.S. dollars to the World Wildlife Foundation. If this is correct, please press 1.


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[Assistant] Confirmed. Thank you for using our bank. Please remove your card from the slot. Goodbye.


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[Assistant] Danger, danger. The exits have been sealed and the doors will remain locked until the local authorities arrive. Thank you for using our bank. Have a nice day.


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[Assistant] Oh, I know I'm orange, but what's this?


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[Assistant] Let's see. Okay, so 50 milligrams of Prozac. Would you prefer this in capsule or tablet?


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[Assistant] Okay, so 50 milligrams of Prozac. Would you prefer this in capsule or tablet? Capsules are fine.


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[Assistant] Okay, you should take one capsule three times a day. Be sure not to take it on an empty stomach. And also, don't ever mix it with alcohol.


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[Assistant] Can I get a price check on fun times ribbed condoms please?


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[Assistant] I told him to be sure not to do anything stupid, but he did.


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[Assistant] Okay, you should take one capsule three times a day. Be sure not to take it on an empty stomach and also don't ever mix it with alcohol.


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[Assistant] That's right, we're gonna listen as a man, uhm, checks in at the airport and, uh, deals with his luggage.


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[Assistant] We're gonna hear this guy say, I'd like to check three pieces.


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[Assistant] That's right. Luggage is a non-count noun. So you can't say one luggage, two luggages, three luggages. That's wrong.


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[Assistant] It means to, uh, to give your bags to the airline to register them.


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[Assistant] Exactly, you carry it on to the plane. Now, we can, we can talk about carry on luggage, right?


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[Assistant] Exactly. All right, so carry on luggage. Now he was traveling on an intercontinental flight.


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[Assistant] Yeah, and the compartment is a place where you can put something and store it. Kind of like a box.


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[Assistant] So this guy was pretty angry about, uh, this airline policy and he said, how am I supposed to?


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[Assistant] Okay, so I can understand that it means, how can I do this?


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[Assistant] So we use this phrase, uhm, when someone's pushing you too much, right?


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[Assistant] Can we look at the use here? Uhm, alright, so in the dialogue we heard, you charge an arm and a leg, but we can also say it costs an arm and a leg.


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[Assistant] Yeah, uhm, I know that this happened to me once and it was really expensive.


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[Assistant] Hello baseball fans and welcome back to today's game. My name is Rick Field and of course I am here once again with the man that seals the deal, Bob Copeland. It's a beautiful day to see two world class teams face each other and fight for their right to be called champions. Well, the national anthem has just been sung and the umpire has started the game. It's time to play ball.


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[Assistant] Roger Vargas is up at bat. Pitcher winds up and strike one. Very nice curveball by the pitcher. The catcher gives him the sign. He winds up.


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[Assistant] And Vargas gets a line drive! The players are scrambling to get the ball. Vargas gets to first base and he's still going! The outfielder throws it to second.


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[Assistant] Hello baseball fans, and welcome back to today's game. My name is Rick Fields, and of course, I am here once again with the man that seals the deal, Bob Copeland. It's a beautiful day to see two world-class teams face each other and fight for their right to be called champions.


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[Assistant] Well, the national anthem has just been sung, and the umpire has started the game. It's time to play ball. Roger Vargas is up at bat. The pitcher winds up, and strike one.


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[Assistant] A very nice curveball by the pitcher. The catcher gives him the sign. He winds up. And Vargas gets a line drive.


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[Assistant] The players are scrambling to get the ball. Vargas gets to first base and he's still going. The outfielder throws it to second. Vargas slides. He's safe. Great play.


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[Assistant] We have a runner on third, and up at bat is Brian Okami. There's the pitch, he hits it. It's going, going, that ball is gone. Home run by Okami. That puts this team ahead by two, as we are at the bottom of the fifth inning here at Ritchie Stadium.


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[Assistant] Hello baseball fans, and welcome back to today's game. My name is Rick Field, and of course, I am here once again with the man that seals the deal, Bob Copeland. It's a beautiful day to see two world-class teams face each other and fight for their right to be called champions. Well, the national anthem has just been sung, and the umpire has started the game. It's time to play ball!


[User] Please transcribe this text

[Assistant] Roger Vargas is up at bat. Pitcher winds up and strike one. Very nice curveball by the pitcher. The catcher gives him the sign. He winds up.


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[Assistant] And Vargas gets a line drive! But players are scrambling to get the ball. Vargas gets to first base and he's still going! The outfielder throws it to second.


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[Assistant] Vargas slides, he's safe. Great play. We have a runner on third and up at bat is Brian Okami.


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[Assistant] That's right. And today we're going to focus on some phrases. We're not going to do any vocabulary today. We're just going to learn some phrases that you'll find relating to science fiction.


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[Assistant] Okay, so warp drive, I think a very sci-fi specific phrase here.


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[Assistant] You know, maybe in the woods or something. You send out a search party to find them.


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[Assistant] Alright, so in the dialogue we saw that actually these were not real Star Trek characters, but they were just acting, but it didn't sound quite right, right?


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[Assistant] Now because his voice wasn't deep enough, he didn't sound authentic.


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[Assistant] Exactly, so uhm, Marco, is that an authentic Rolex?


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[Assistant] Alright, so we've got some phrases here that you can use together with a number of different words, right?


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[Assistant] Definitely. Now you can change this by changing the last word. We are under fire.


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[Assistant] Yeah, except that when you're under fire, uhm, there are guns involved.


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[Assistant] Sustain heavy damage. So when you sustain something, you receive it or you undergo this thing.


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[Assistant] Alright, so you see, we typically sustain something like an injury, uhm, or damage that is negative.


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[Assistant] What is the nature of? What is the nature of?


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[Assistant] Okay, so basically he's just asking, why are you doing this?


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[Assistant] That's true, and speaking of culture, I think we've got, uhm, a Star Trek movie coming out pretty soon, so some of this language can help you guys understand it a little bit better.


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[Assistant] Well thanks for downloading you guys and until next time. Goodbye!


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[Assistant] Yep, that's true. And so we're going to be focusing on language, uhm, to express your romantic feelings and also maybe, uhm, some phrases you can use to ask someone out.


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[Assistant] Okay, so we're doing things a little differently today. Uh, we're looking at phrases and not just vocabulary words. So he used some wonderful phrases to ask her to be his boyfriend. And he started with this. Here's the thing. Here's


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[Assistant] Not quite, he's not giving her an object, but he's giving her some information.


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[Assistant] We can't take it anymore. Take what? Well, why don't we find out by listening to some examples?


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[Assistant] Exactly, this is a phrase we use when we are really frustrated.


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[Assistant] So this is a phrase that's really, uhm, it's quite informal, isn't it?


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[Assistant] Alright, so to have the guts to do something. Hey, but Marco, this word guts is an interesting one.


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[Assistant] Alright, so that's a little bit clearer this time, but while I was listening, I noticed that there's some more great phrases that you can use together with different words. So let's look at those now. I'm putting it together.


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[Assistant] So just the two of us, uhm, quite simply it means you and me, just us, right?


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[Assistant] So, so it suggests the idea of only us. Okay.


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[Assistant] Mhm. Or even, uh, she wants to eat the cake all to herself.


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[Assistant] Okay, so our last phrase is also the last thing we heard in the dialogue. He said,


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[Assistant] Okay, so when you give someone a shot, you take a chance, right?


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[Assistant] Alright, so we don't know if she will give him a shot or not, but why don't we listen to the dialogue once more to hear these phrases in action.


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[Assistant] That's right. Uhm, so in the dialogue, the guy was asking her if she would be his girlfriend, right?


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[Assistant] Uhm, I think for us, when we start to have romantic relationships, it just sort of happens naturally, right? You never really have this conversation, will you be my boyfriend?


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[Assistant] Well, I don't know, but I'm looking forward to hearing from our listeners. So guys, uh, check out our website, EnglishPod.com. You can leave your questions and comments there.


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[Assistant] First of all, it's the Sadie Hawkins dance. The girls gotta ask the guys.


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[Assistant] First of all, it's the Sadie Hawkins dance. The girls gotta ask the guys. Also,


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[Assistant] First of all, it's the Sadie Hawkins dance. The girls gotta ask the guys.


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[Assistant] I've colored one, two, three, three flags blue.


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[Assistant] It's your castle. I thought blue flags would make it castle blue.


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[Assistant] I am imagining she did all these horrible things. Be fine.


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[Assistant] Republican lawmakers in the American state of Wisconsin have sent out police to search for a group of Democratic party politicians.


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[Assistant] The Democratic state senators left Wisconsin in order to block a crucial budget bill, which includes controversial plans by the Republican governor, Scott Walker, to limit the power of trades unions.


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[Assistant] Without the Democratic lawmakers, the Senate cannot reach a quorum and the bill, which would have been passed easily by the Republican majority, cannot be voted on. News item 32.


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[Assistant] A former Serbian police chief has been jailed for 27 years for his role in the murder of more than 700 ethnic Albanians in Serbia's province of Kosovo in 1999.


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[Assistant] Vlastimir Dojovic was convicted by the International Tribunal in The Hague of four counts of crimes against humanity.


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[Assistant] Thomas is always so belligerent. It is impossible to talk to him.


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[Assistant] To finish this house, we need such materials as cement, wood and steel.


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[Assistant] I hate this class. It's so boring and tedious. You know what I mean?


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[Assistant] This movie is so confusing. I have no idea where the plot is going.


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[Assistant] If you want to buy high quality, low price cocaine, there really is only one place to go.


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[Assistant] And that is the darknet anonymous markets. You can't get to these sites with a normal browser, Chrome or Firefox, because they're on this hidden part of the internet.