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[Assistant] Probing and finding another place in the hash table offset from the place where we originally hashed to.


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[Assistant] So in open addressing, everything is kept inside one big array.


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[Assistant] So the time complexity of the hashable is actually pretty remarkable. In fact, it's amazing.


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[Assistant] On average, we can achieve constant time for insertion removal and search. But if you


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[Assistant] Have a terrible hash function that's not uniform, then you can get linear time, which is really, really bad.


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[Assistant] Alright that's it for this video but in the next few videos we'll be going over separate chaining and open addressing.


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[Assistant] And covering all of that as well as how to remove some elements. Guys, thank you for watching and I'll catch you in the next video.


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[Assistant] How are you Erika? I'm doing great Marco and you? Excellent, I'm doing really well and I'm really excited about our lesson for today.


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[Assistant] Exactly, and today, as Erica mentioned, we have an intermediate lesson. And not only is it intermediate, but it's a business lesson.


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[Assistant] Great, so why don't we take a look at our vocabulary preview for today.


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[Assistant] Okay great, so that is what vocabulary preview is. We have two words for you today, and we can start off by looking at the first one.


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[Assistant] To drive sales. Drive sales. Drive sales. To drive sales, and that means? To increase sales. Right, to sell more. Exactly, so to drive sales. Okay, so now let's look at our second word.


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[Assistant] And it's an interesting one, it's promotion. Promotion. Promotion. Promotion. So Erica, what is a promotion exactly?


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[Assistant] Okay, so I can give you an example. Suppose that I want to buy shampoo. And if I go to the supermarket and I see buy one and get one free.


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[Assistant] So that's a two for one. That's a two for one promotion. Yeaah.


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[Assistant] Great, so we are ready to listen to our dialogue. It's gonna be pretty fast, so it might be a little bit difficult to understand.


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[Assistant] We're gonna talk about him later on in the show, but now let's take a look at our language takeaway.


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[Assistant] Exactly, so we have three words for you today. Let's look at the first one. Match the competitors. Match the competitors. Match the competitors.


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[Assistant] Great, so we have some examples for you so you can listen and try and see if you can figure out what match the competitors really means.


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[Assistant] Exactly. I can say, for example, English pod is the best language pod in the market.


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[Assistant] So this phrase sounds a little bit strange.


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[Assistant] Great, so now we've seen a lot of useful phrases and we are ready to listen to our dialogue a second time, but this time it's gonna be slow.


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[Assistant] Right, so now it's time for us to take a look at Fluency Builder.


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[Assistant] Right, and we have three of these words for you today. Yeah. Let's start with the first one. Okay, so often students will say something like, I'll be here soon. Or, I will arrive soon.


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[Assistant] Okay, so, be here any minute. He'll be here any minute. It just sounds a little bit more natural.


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[Assistant] Great. Okay, so let's move on to our second phrase for fluency builder.


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[Assistant] Right, so you can say something like, we are thinking about a sales strategy.


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[Assistant] But in the dialogue, we heard something a little bit different, so let's listen to it.


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[Assistant] It's a good word. Okay, brilliant, so let's move on to our third word.


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[Assistant] Yeah, I actually did. Brilliant. Uhm, that's a great word right there.


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[Assistant] I like that word. Okay, so we're ready to listen to our dialogue again, a third time, but at its normal speed.


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[Assistant] And you can tell because they are a little bit scared of talking and he cuts them off with saying, oh, it's a bad idea. Give me a better idea and stuff like that.


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[Assistant] Great, so be sure everyone to visit our website at EnglishPod.com and where you can find a lot of other information and really good resources to continue improving your English.


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[Assistant] What? You want to sell bikinis in Alaska? That'll never fly.


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[Assistant] Well, uhm, in fact, we're the most expensive in the market, so maybe we need to lower our prices to match the competitors.


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[Assistant] That's right, and we've got an intermediate lesson today about spending money.


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[Assistant] So it's a document that outlines how much money the company makes and how much it spends.


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[Assistant] Okay, so we're gonna be listening to, uh, some people discuss a profit and loss statement in just a moment.


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[Assistant] But before we do that, it's time for vocabulary preview.


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[Assistant] Okay, and maybe in a household or a family, your expenses might be your food,


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[Assistant] Perhaps your transportation or your rent or your heating bill. So these are all things you spend money on regularly. They're expenses.


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[Assistant] Yeah, that's totally true. Gas prices have gone really high in the past couple of months.


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[Assistant] That's right, we typically use this word with numbers. It also gives you the idea that the number has risen really quickly.


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[Assistant] Don't worry if you don't understand everything because we will explain all of the key language in a minute.


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[Assistant] Okay, so this accountant, she's, uh, pretty thorough, hey?


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[Assistant] So expenditure sounds pretty close to expenses, right?


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[Assistant] So expenditures is the total amount of money that you're spending on something.


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[Assistant] Yeah, this is a really common word and it basically means look at carefully.


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[Assistant] In English, we often find simple little words, they fit together really well, and you think, oh, they're so easy, like the word go, over, so easy.


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[Assistant] But it's the way that they interact with each other that makes them...


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[Assistant] Exactly, so go over in this case, we might say, uhm, let's go over the lesson.


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[Assistant] Okay, so we've taken a look at our language takeaways for today. I think it's time to listen to the dialogue one more time.


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[Assistant] Off the charts for through the roof in these examples.


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[Assistant] Okay, so two ways of saying really, really, really high.


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[Assistant] Yeah, that's true. Okay, so this next word is a phrase that you can use if you want to tell somebody that you'll check something or you'll investigate something.


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[Assistant] So look into that. That means I'll check something.


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[Assistant] Okay, so I think we've got another word that does mean you're going to take action.


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[Assistant] Well Marco, I guess one of the benefits of being an executive in a company, especially a large company, is you get a lot of amazing benefits.


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[Assistant] Yeah, so you can go out to a restaurant, get the receipt, and claim the expenses at work.


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[Assistant] So Marco, I'm curious to know what our listeners' expenses are. Yes.


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[Assistant] Well, let's see, my spending on Coke Zero has gone through the roof since we started this podcast.


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[Assistant] That's right, you can find us at EnglishPod.com and Marco and I are always there to respond to your questions and comments.


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[Assistant] Yes, this is Julianne Horton and I'm calling to arrange an appointment with Miss McNeely. Certainly. What date were you thinking of? How's Thursday? Does she have any time available then?


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[Assistant] Actually, I've got something scheduled on Monday. Can she do Tuesday? Sure. Tuesday's perfect.


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[Assistant] May I ask where you're calling from? Sure, Merton Financial Advisors.


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[Assistant] Example one. What seems to be the problem? Example two.


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[Assistant] Example three. What seems to be the trouble?


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[Assistant] That's right, so we've got a lesson today about weddings. And you know what? A lot of the language in this lesson is about weddings and marriages. And maybe you don't need to use this language every day, but


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[Assistant] Okay, great point Marco. I think now we can look at our vocabulary preview.


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[Assistant] So two simple words in this vocabulary preview. The first one is groom.


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[Assistant] Bride. Bride. Bride. And obviously the bride is?


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[Assistant] Perfect. Now we have our bride and our groom, so it's time to listen to our dialogue the first time.


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[Assistant] Well, there's some great language in this dialogue, and now let's look at our language takeaway.


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[Assistant] Okay, so the bridesmaids are the women who are friends of the bride who stand next to her when she's getting married. Usually they're her best friends.


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[Assistant] The flower girl is that cute little girl who walks down the aisle and who throws flowers.


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[Assistant] Yeaah. You know, beautiful you can only use with a woman.


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[Assistant] Alright, well, we've learned some really interesting vocabulary that will help us to understand an Anglo wedding, so why don't we listen to the dialogue slowed down.


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[Assistant] So this is a word that causes a lot of problems.


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[Assistant] Right, so these are wrong examples. Example one.


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[Assistant] These are great examples of mistakes students make with the word marry. They're missing a word. Let's listen to these right examples to see what word is missing.


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[Assistant] Well like I said earlier, the bridesmaids are the friends of the bride. But the most important people, besides the bride and groom, are the best man and the maid of honor.


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[Assistant] Okay, well everyone, thanks for listening and until next time, goodbye!


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[Assistant] More Baby Animals Written by Lauren Simmons Focus Question


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[Assistant] Science. Label one side of a piece of paper adult animals and the other side baby animals.


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[Assistant] But while these pioneers gazed out across the waves in search of a new world, few thought to look downwards.


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[Assistant] Perhaps they thought it futile. After all,


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[Assistant] The mainstream scientific viewpoint was that life could not exist more than 550 metres.


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[Assistant] Giving way to vastly increased efforts in deep sea exploration.


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[Assistant] So much so that it led to the Royal Navy granting use of a ship called the HMS Challenger for a global expedition. A voyage that would help lay the foundations of modern oceanography.


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[Assistant] The date is the 21st of December, 1872, and something remarkable is taking place.


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[Assistant] The HMS Challenger is departing from the port. Captained by George Nairs.


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[Assistant] Scottish natural historian and naturalist, Charles Wyville Thompson,


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[Assistant] Loading specimen jars with alcohol to preserve samples, microscopes, trolls and dredges, sounding leads, devices to collect sediment from the deep sea.


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[Assistant] And great lengths of rope to suspend this equipment into the depths. This expedition was to be the first of its kind. One organized specifically to gather data on the ocean environment and its inhabitants.


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[Assistant] He believed that the conditions of extreme cold, intense darkness and a lack of currents


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[Assistant] A team of five scientists on board the HMS Challenger, conducted the research. And over a three year period at sea,


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[Assistant] Now estimated to be a few thousand meters deeper than their initial measurements. The discovery of this location, now bearing the name the Challenger Deep,


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[Assistant] led to a huge broadening in our understanding of oceanography, in addition to the use of sounding.


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[Assistant] As it quickly became apparent that the oceans are teeming with life. And in March of 1875, after more than two years at sea, the crew of the HMS Challenger made a remarkable discovery.


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[Assistant] They dipped down within sight of Antarctic icebergs, and then headed up along Australia's southeast coast, making their way through Micronesia and Asia.


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[Assistant] Then east across the Pacific, tracing South America and arriving back in England on May 24th, 1876.


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[Assistant] Much like our theories about the cosmic expanse of the universe.


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[Assistant] Because of our knowledge of pressure and the extreme conditions down there.


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[Assistant] But now, ocean science could advance in the knowledge that the depths concealed yet more secrets.


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[Assistant] The Challenger Expedition's exciting discoveries encouraged other countries to take interest in the oceans, and to mount their own expeditions.


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[Assistant] Don't be sad, Peppa. The electric light can make shadows. And we can make shadow puppets.


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[Assistant] Goodnight, Pepper. Goodnight, George. Goodnight, Shadows.


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[Assistant] Basically, we need to come up with a clear plan. We need to outline specific actions that our company can take to maintain critical business functions in case a pandemic strikes.


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[Assistant] Well, let's see. There are a few points we need to be thinking about.


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[Assistant] We need to come up with a clear plan We need to come up with a clear plan


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[Assistant] Basically, we need to come up with a clear plan. We need to outline specific actions that our company can take to maintain critical business functions in case a pandemic strikes.


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[Assistant] Well, let's see. There are a few points we need to be thinking about.


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[Assistant] That alone means I have 1,500 employees under me.


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[Assistant] Wow, yeah, that sounds exciting. And what about you, Arthur? What do you do for a living?


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[Assistant] Actually, I'm not all that crazy about Italian food. I'm in the mood for something a bit lighter.


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[Assistant] Ella, you took me there last time I visited, and I got food poisoning, remember?


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[Assistant] Actually, I'm not all that crazy about Italian food. I'm in the mood for something a bit lighter.


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[Assistant] And today we're bringing you the sequel of I'm Sorry I Love You. Part 2. Part 2.


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[Assistant] And since it was such a romantic dialogue.


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[Assistant] We're bringing part two, so it's even more romantic, and I'm sure everyone is gonna find some great and useful language in it.


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[Assistant] So, useful language for when you're going on a date.


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[Assistant] Yeah, it's a really romantic thing that's going on right now, but there was some really useful words here, so why don't we take a look at language takeaway?


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[Assistant] So, ordinary is a normal word. Yes, meaning? It's normal. Uh huh. Nothing uncommon about it. Yeaah. So you can have like an ordinary person.


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[Assistant] So, ordinary. Okay, great words, and I guess now we can listen to our dialogue a second time.


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[Assistant] On Fluency Builder today we have three great phrases. So why don't we just start with the first one?


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[Assistant] To you. Make it up to you. Make it up to you. Okay, so we have some great examples on how we use make it up, so let's listen.


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[Assistant] Right, so if you call your mother-in-law fat,


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[Assistant] Okay, our second phrase, my treat. My treat. My treat.


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[Assistant] Hey, let's go get some beers. It's my treat.


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[Assistant] Alright, for example, okay, you're supposed to catch a flight to another country, alright, but you're late, so you miss your flight.


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[Assistant] Okay, so we're back. Erica, I know you have a story of a twist of fate in your life.


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[Assistant] Alright, well we want to hear your stories of maybe some type of twist of fate that you've had.


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[Assistant] Maybe love stories, maybe tragic stories, any story.


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[Assistant] And, uh, where you can also find us to answer any questions or doubts. Yes, that's right. So, I guess until then, it's... Goodbye! Bye!


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[Assistant] They were relieved to hear that the company would not be making any layoffs.


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[Assistant] Yeah, I guess we'll have to stay tuned and find out.


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[Assistant] The first word is thoughtful. Thoughtful. Thoughtful. Thoughtful. So when you're thoughtful, you're kind, right?


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[Assistant] It's like you convince me to do something that I don't really want to do.


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[Assistant] The first one is appetite, appetite, appetite.


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[Assistant] So, appetite is like a strong desire for food, right? Right, an appetite. We've got some examples that show you how to use this phrase. Let's listen.


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[Assistant] And our third phrase is, why on earth?


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[Assistant] You can use it in a lot of different ways, so we've got some examples for you. Let's listen.


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[Assistant] So when you ask a question with on earth, so why on earth, how on earth, what on earth, it's like you're showing a lot of surprise.


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[Assistant] That's right. Marco and I will choose the best continuation of the story and we'll use that in part three of The New Guy in Town.


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[Assistant] Yes, Marco and I are always happy to answer your questions.


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[Assistant] Ally and Ollie. Written by Katherine Page. Illustrated by Kaori Tajima.


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[Assistant] Allie and Ollie think they are people.


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[Assistant] Allie and Ollie run like people.


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[Assistant] And with very little energy making its way down here to where the sunlight does not reach, survival in the depths is a challenge for any creature.


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[Assistant] Every now and then, islands of life appear around sunken carrier, providing a temporary surge of nutrients.


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[Assistant] There are some locations in the deep that life has clung to for millions of years, and where food and energy is ever abundant.


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[Assistant] Here, at depths of 2000 metres or more, life gathers around hydrothermal vents in great numbers.


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[Assistant] Up until that point, we had thought all life depended on sunlight to survive.


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[Assistant] But this extreme ecosystem represents the only place on Earth where the ultimate source of energy for light is not sunlight, but the Earth itself.


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[Assistant] Over 300 animal species have been identified living at these vents. 95% of these organisms are unique to the vent ecosystem, and they were new discoveries previously unknown to science.


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[Assistant] Many don't appear to be closely related to any other creatures on the planet.


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[Assistant] Suggesting that they likely belonged to a divergent evolutionary path that splinted off in the distant past.


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[Assistant] Or perhaps, they represent the primordial community of life from which all life on earth evolved.


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[Assistant] Though they are toxic to humans, the chemicals that are expelled within the superheated water contain nutrients that bacteria are able to convert to energy.


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[Assistant] Much like plants convert sunlight during photosynthesis.


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[Assistant] This process of converting chemicals to energy became known as chemosynthesis, and it redefined our understanding of life.


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[Assistant] Like plants and algae on land and in the shallows, the chemical harvesting microbes are the primary producers in the food web here, and they are eaten by larger animals.


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[Assistant] Which encourages the growth of microbes on its claws and shells.


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[Assistant] The worms absorb hydrogen sulphide and other chemicals from the vent fluids in order to feed the bacteria.


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[Assistant] The bacteria provide the carbon that the tube worms require in order to live.


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[Assistant] It is also thought that the bacteria benefit by being sheltered within the tube worms.


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[Assistant] And are therefore protected from predators like the limpets and crabs.


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[Assistant] Some deep sea skates, which are related to sharks and rays, have become highly evolved to live in this environment.


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[Assistant] They lay their eggs near the heat producing vents, utilizing the volcanic heat to accelerate egg development and reduce the usually years long incubation time of their eggs.


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[Assistant] Hydrothermal vents form when water seeps into the Earth's crust through cracks and fissures in volcanically active regions, such as the Mid-Ocean Ridge. The water becomes superheated with the hot magma that is found within the Earth's layers.


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[Assistant] The water boils up to be released from the ocean floor and picks up dissolved minerals along its journey. This forms the towering chimney structures, as the dissolved minerals solidify when the heated water mixes with the cool seawater above.


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[Assistant] There are many varieties of hydrothermal vents, characterized by the specific mineral content that is brought up by the heated water.


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[Assistant] Black smokers emit the hottest, darkest blooms, forming chimneys over 50 meters tall, with high levels of sulfides that precipitate on contact with the cold ocean to form the black smoke.


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[Assistant] White smokers contain barium, calcium and silicon.


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[Assistant] Other vents are characterized by the shimmering streams of water that vary with temperature, some being up to 400 degrees Celsius.


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[Assistant] The discovery of deep sea hydrothermal vents was groundbreaking for another reason.


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[Assistant] Got scientists speculating whether these vents could be where life on Earth originated. It remains to this day to be only a theory.


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[Assistant] Firstly, some of the thermophilic, or heat-loving, vent microbes are among the most primitive organisms known on Earth.


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[Assistant] Evidence is also given by the fact that many of the building blocks of life are found at the vents suggesting that the precursors of life


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[Assistant] Harnessed carbon dioxide and hydrogen available in those primitive conditions to create these complex organic molecules, such as amino acids and nucleotides.


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[Assistant] In conclusion, hydrothermal vents support unique ecosystems and their communities of both highly specialized as well as simple organisms in the deep ocean. The islands of abundance they create in the otherwise barren depths are sites of outstanding scientific interest, providing a new insight


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[Assistant] Into what is truly necessary in order for life to survive.


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[Assistant] Who knows what else lies in the depths, in wait of discovery.


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[Assistant] Hello and welcome. My name is William and today we're talking about sparse tables, a niche data structure with a great time complexity when answering range queries on static arrays.


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[Assistant] Alright, let's talk about the type of situation you might want to use a sparse table.


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[Assistant] So sparse tables are all about doing efficient range queries on static arrays. So the typical use case is when you're dealing with say, an integer array that has immutable data.


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[Assistant] So I want to give you a brief intuition on how a sparse table works at a high level without getting into too many details.


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[Assistant] So if you think about any positive integer, you know that it can easily be represented as the sum of powers of two given by its binary representation.


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[Assistant] For example, the number 19 in binary is 10011, which is equivalent to two to the power four plus two to the power of one plus two to the zero.


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[Assistant] Similarly, we can break down an interval with a left and a right endpoint into ranges, which are all lengths that are powers of two.


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[Assistant] Now imagine we want to do a range query on the interval


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[Assistant] All range query functions need to meet some certain prerequisites in order to be compatible with the types of aggregation and combination operations that we want to do while building the sparse table and also while performing range queries.


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[Assistant] is associative, which means that the order in which operations are performed does not matter. If your range combination function is associative, then you can do range queries on a sparse table in logarithmic time. We will look at this in more detail later on.


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[Assistant] Now even though logarithmic time range queries are really good, we can actually do even better. When the range query combination function is what I call overlap friendly, then range queries can be answered in constant time, which is just truly amazing.


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[Assistant] By overlap friendly, I mean that the function yields the same result, whether you're combining ranges which overlap, or those that do not.


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[Assistant] We can also define the concept of an overlap friendly function in a more rigorous way.


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[Assistant] A binary function f of x y is overlap friendly if combining A with B, then B with C, and then combining the result of the two is the same as individually applying the binary function to each adjacent element pair in a sequence.


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[Assistant] Let's see an example. Suppose we have this array of values and a summation function f of x, y, which just adds x and y.


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[Assistant] Unfortunately, this function is not overlap friendly, and I can easily show you why.


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[Assistant] Here I have already computed the sum for three arbitrary ranges, range one, range two, and range three, denoted as r1, r2, and r3, which we can use in the formula I presented earlier.


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[Assistant] What we're trying to test is whether our function is agnostic to the middle interval or two.


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[Assistant] First we can pass the two leftmost intervals into the left side of the function.


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[Assistant] And then do the same thing for the two rightmost intervals after computing the result.


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[Assistant] And the result of combining each interval individually, you see that we get different answers. What ends up happening in this case specifically, is that the summation function double counts the middle interval twice. Therefore, we know that our function is not overlap friendly.


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[Assistant] So here are a handful of functions I made up. Take a moment and identify which of them are overlap friendly functions and which of them are not. Feel free to pause the video.


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[Assistant] I left the functions which are overlap friendly highlighted and grayed out the ones that are not.


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[Assistant] The central idea behind a sparse table is to pre compute the range query answer for all intervals of size two to the x to efficiently answer range queries between a left and a right endpoint.


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[Assistant] The main downside to this approach is that you need on the order of n log n memory to store all the intervals. But in the end, you end up reaping the benefits with fast queries. So that's a trade off you need to make.


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[Assistant] To get started, we're going to need to know two variables n, the size of the input array, and two to the P, the largest power of two that fits in n.


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[Assistant] We can actually calculate p as the floor of the base two logarithm, which actually turns out to be more important than to the power of p itself.


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[Assistant] After that, we can initialize a table with p plus one rows and n columns.


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[Assistant] Next up, we can fill the first row with the input values. The input values simply consist of the values in the original array, we want to do range queries on.


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[Assistant] Combined answer for the range j inclusive to j plus two to the i non inclusive in the original array. For example, the cell at row two column five represents the answer for the range five to nine non inclusive.


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[Assistant] If we are building a sparse table to calculate minimum range queries, then the blue cell would have a value of three. However, if we're building a sparse table to do range some queries, then the blue cell would have a value of 20.


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[Assistant] So the value in the blue cell will vary depending on what you're trying to accomplish with the sparse table.


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[Assistant] On this slide, the blue cell at row three column two represents the answer for the range two to 10 non inclusive. While on this slide, the cell at row one column seven represents a much smaller range of seven to nine non inclusive.


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[Assistant] Now, what do we do about the cell acquisition row two column 10, which represents the range 10 to 14 non inclusive.


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[Assistant] This interval reaches outside the bounds of the sparse table.


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[Assistant] Well, we don't need to consider partial ranges. So we can actually simply ignore this cell and all other cells with invalid intervals.


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[Assistant] Now that we understand what each cell represents, let's build a sparse table to support minimum range queries. To do min range queries, we will first need a range combination function to combine cells together.


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[Assistant] For a min sparse table, the range combination function simply takes the minimum of the left and the right interval.


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[Assistant] The way we're going to build the table is by reusing already computed range values of previous cells. We know that the current cell at position i comma j represents the interval from j to j plus two to the i non inclusive in the original input array.


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[Assistant] You will notice that the interval for each cell always has an even length. This means that the interval for the current cell can easily be broken down into a left and right interval, or rather a left and a right cell.


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[Assistant] Suppose we want to know the value of the blue cell.


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[Assistant] To compute its value, we would take the minimum of both the red cells, which represent intervals of length four, which combined together cover the same range as the blue cell would.


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[Assistant] In turn, the red cells are computed from green cells, which represent intervals of size 2.


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[Assistant] And those are based on orange cells and so on. In the end, the blue cell would contain the minimum value for the entire range covered by the orange cells highlighted in the table.


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[Assistant] We can finish filling the sparse table by combining values from the previous rows. So here we would take the minimum of four and two. And here the minimum of two and three


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[Assistant] Of three and seven, and so on for the rest of the row.


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[Assistant] On the next row, we would do the same thing. But now we're constructing all intervals of size four instead of all intervals of size two.


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[Assistant] And lastly, we would build the bottom row, which represents all intervals of size 8.


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[Assistant] Now suppose we want to know the minimum value between index one and 11 inclusive.


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[Assistant] Of course we can look at the original input values and scan all the items until we find the smallest one. But how do we leverage the sparse table to help us?


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[Assistant] Well, in the table we have already pre-computed the answer for all intervals of length 2 to the power of x.


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[Assistant] Suppose that we know the value of K, the largest power of two that fits in the length of the range between L and R, the left and the right endpoints respectively.


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[Assistant] Knowing K, we can easily do a lookup in the table to find the minimum between L and R by splitting the range L to R into a left and a right interval. The left interval consists of the range L to L plus K,


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[Assistant] And the right interval consists of r minus k plus one to r, the left and the right intervals may overlap. But this does not matter given the overlap friendly property of our function.


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[Assistant] So long as the entire range is covered. As an example, the left interval here would be between one and eight inclusive and the right interval between four and 11 inclusive. As you can see the entire range between one and 11 is covered and there is an overlap section.


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[Assistant] So if you take the minimum of both the blue cells, we can conclude that the minimum value between the range one to 11 is negative


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[Assistant] Let's take a step back and look at how we actually found the values of the left and the right cells. The first thing we want to do is get the value of P, the exponent on the largest power of two that fits in the range one to 11 inclusive.


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[Assistant] Finding p is the same as taking the floor of the base 2 logarithm for the length of the interval.


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[Assistant] Once we know p, we can calculate k, which is just two to the power of p. Knowing the values of p


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[Assistant] And k, we can do a lookup in the table for the left and the right interval ranges. intuitively, p corresponds to the row in the sparse table and k corresponds to the length of the largest power of two that fits in the range, which is ultimately used to calculate the offset for the right cell.


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[Assistant] Let's do another example. Can you find the minimum value between two and seven inclusive in the original array using the sparse table? Pause the video if you need more time.


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[Assistant] You can break it down into a few steps. First, find P, which is the floor of the base two logarithm of the left and the right endpoints, then compute K, which is two to the power of P. And finally, do a look up in the sparse table for the left and the right interval values.


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[Assistant] Let's do one more example in case you want the extra practice. What is the minimum value between three and five inclusive?


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[Assistant] As you may have realized earlier, some functions such as multiplication and summation are associative, but they are not overlap friendly.


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[Assistant] Luckily, a sparse table can still accommodate such functions for range queries. However, the runtime will be logarithmic instead of constant.


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[Assistant] The alternative approach to performing a range query is to do a cascading query on the sparse table.


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[Assistant] For example, the range between two and 15 inclusive can be split into three intervals of lengths, eight, four and two, which are two to 10 non inclusive.


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[Assistant] 10 to 14 non-inclusive and 14 to 16 non-inclusive.


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[Assistant] Let's have a look at an example. Suppose we have an input array with seven elements, one, two, minus three, two, four, minus one and five.


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[Assistant] So if we are querying the range zero to six, we want to break it down into powers of


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[Assistant] We can do that by fitting the largest power of two that we can starting at the left endpoint, and then with the remaining interval fitting in the next largest power of two in there and so on.


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[Assistant] So the interval between zero and six can be broken down into the intervals zero to four non inclusive, four to six non inclusive, and six to seven non inclusive.


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[Assistant] Notice that all those ranges have lengths which are powers of 2.


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[Assistant] Once you know the intervals you'll be querying, you can do a lookup on each of those intervals in the sparse table and then multiply them all together. For this example, we would do a lookup in the table at row two, column zero corresponding to the interval between zero and four non inclusive.


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[Assistant] Let's do another example. Suppose this time we want to find the product of all the elements in the interval between one and five inclusive. First, we would break down the interval one to five into one to five non inclusive, and five to six non inclusive.


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[Assistant] After that, we would do a lookup in the table for both of those intervals. The first interval between one and five is found at cell


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[Assistant] Row two column one and the second interval between five and six in the cell at row zero column five. The product of those two cells is 48, which is the value you would get by multiplying all the elements in the range one to five inclusive.


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[Assistant] Alrighty, let's take some time and look at some pseudocode. Let's dive into how we would implement a sparse table.


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[Assistant] The first thing you need to know is n, the number of elements in the input array.


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[Assistant] For all values between one and n later we're going to want a way to quickly look up these values in an efficient manner. So I'm doing it now.


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[Assistant] The variable dp is the sparse table with p plus one rows and n columns. This next variable is actually pretty interesting.


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[Assistant] Unfortunately, knowing the index value of the range query doesn't always make sense for all range query types, like a some range query or a product range query, but it does make sense for minute max range queries.


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[Assistant] We can keep track of the index of the minimum element in an index table, which has the same dimension as our sparse table.


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[Assistant] Now here's the function that builds the sparse table.


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[Assistant] Next, these two for loops iterate over all the cells of the table while making sure not to consider intervals which go outside the bounds of the table.


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[Assistant] After that, we can find the values of the left and the right cells and take the minimum.


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[Assistant] Lastly, we want to save and propagate the index of the smallest element inside the index table so that we don't lose track of it. You can think of the index table as an identical sparse table that keeps track of index values instead of minimum values.


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[Assistant] Once the sparse table is built, we can start doing range queries on our array. This first method finds the smallest element in a range L to R inclusive in constant


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[Assistant] To do this, first calculate the length of the range and find the value of p, then simply


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[Assistant] And this function at the bottom is the cascading min query function, which also finds the smallest element.


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[Assistant] In a range L to R inclusive, but does so in logarithmic time, you can easily adapt this function to support range query functions which are associative but not overlap friendly.


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[Assistant] To find the minimum value, start by assigning min val to positive infinity, then this next loop finds all the powers of two that fit within the interval. Each iteration I do a look up in the log two table to find p


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[Assistant] P is useful because it can tell us the next largest power of two that fits in the current range length between L and R.


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[Assistant] The last method I want to take a look at is the min index query function, which returns the index of the minimum element in the range L to R inclusive. If there are multiple smallest elements, the index of the leftmost one is returned.


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[Assistant] To do this, we're basically going to do the same thing as when we were finding the minimum query value, we're going to find the values of the left and the right cell. But rather than returning the minimum of the two, we're going to compare them


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[Assistant] Hopefully you learned something in this video and guys, please subscribe for more mathematics and computer science videos. I'll catch you next time.


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[Assistant] Allowing organisms to rely on others for food, shelter, or to act as warning for nearby danger.


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[Assistant] But nowhere else on earth are creatures more uniquely adapted to relying on others than in the deep sea. A world of darkness, cold, and intense pressure.


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[Assistant] Let's dive in and take a closer look at the incredible role of symbiosis in the deep sea ecosystem.


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[Assistant] Mutualism, which is best simplified by the phrase, you feed me, I feed you.


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[Assistant] You might at first think of clownfish relying on anemones for protection, in turn providing nutrients through their excrement. But increasingly,


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[Assistant] Deep sea exploration uncovers some truly unique cases of organisms depending on one another.


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[Assistant] In many cases, a relationship will form between a microbe and a host.


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[Assistant] The microbe provides food for the host, while in return the host provides the microbe with protection from predators. They both benefit, making this relationship a form of mutualism.


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[Assistant] Mutualism often forms between bacteria and a wide range of host animals including corals, mussels and tube worms at deep sea hydrothermal vents and cold seeps.


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[Assistant] Here, the water that wells up from below the seafloor is rich in minerals for the bacteria to convert into food and energy.


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[Assistant] These compounds are hydrogen sulphide and methane. Both are toxic to animals.


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[Assistant] But certain specialized bacteria are able to use the chemicals to make the organic matter that animals rely on.


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[Assistant] This process is known as chemosynthesis. Think of it as an alternative to photosynthesis.


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[Assistant] Odd looking tube worms grow in clusters around vents and cold seeps


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[Assistant] This is because they instead contain a troposome.


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[Assistant] The tube worms are specifically adapted to being a symbiont in this relationship.


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[Assistant] The stable nature of the vents has allowed the worms to evolve over millions of years to possess these important physical characteristics.


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[Assistant] Both the oxygen and the chemicals are transported to the troposome, where the bacteria use them and carbon dioxide to produce organic molecules.


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[Assistant] Without the tubeworm's troposome providing them with a constant supply of these key ingredients, the single-celled bacteria would have a hard time gathering it all in one place.


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[Assistant] 100% of the tube worm's nutrition is provided by the bacteria undergoing this process.


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[Assistant] Especially as photosynthesis is not an option down where the sunlight cannot reach.


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[Assistant] It also supports an abundance of other organisms that rely on the tube worms.


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[Assistant] To put it simply, the bacteria need to live inside the worms and muscles in order to gain the ingredients for chemosynthesis.


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[Assistant] The tube worms need the bacteria to live inside them in order to synthesize the nutrients and energy they need.


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[Assistant] And the associates need the worms and mussels as a source of prey. It all comes back to symbiosis. The key to survival is working together.


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[Assistant] Instead, they turn to symbiosis, and allow glowing photobacteria to take shelter in their fleshy law called an escha.


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[Assistant] Sometimes, one organism benefits from causing harm to the other.


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[Assistant] Parasites are key components of food webs.


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[Assistant] They are often seen with a long white parasitic copepod attached to the corneas of their eyes, called Omatechoita elongata, which causes blindness in the sharks.


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[Assistant] Its large size is an example of abyssal gigantism, allowing it to be more efficient in the nutrient-poor depths.


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[Assistant] But one thing that the Greenland shark does not rely on in the deep dark sea is eyesight.


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[Assistant] Unlike many organisms that have evolved large, light-sensitive eyes to see better, Greenland sharks instead have opted to rely more on their acute sense of smell to detect prey and carrion.


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[Assistant] But rather it may be an example of the third kind of symbiosis. Commensalism.


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[Assistant] When one organism benefits without helping or harming the other.


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[Assistant] A good example of a commensal relationship is found on the skin of whales.


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[Assistant] This gives barnacles a significant advantage over other filter feeders that are fixed in one position and must compete for space on the rocks.


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[Assistant] Overall, symbiosis is a key ecological association in the extreme deep sea ecosystem.


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[Assistant] With nutrient production from sunlight impossible, Hemosynthetic bacteria must fill the role of food producers.


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[Assistant] We find that it allows animals to thrive in habitats and adapt to live in ways that would not otherwise be possible without their symbiotic counterparts.


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[Assistant] Through symbiosis, they thrive. Through cooperation, they conquer.


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[Assistant] It is an extraordinary phenomenon, showing off the resilience of life to the extreme conditions of the abyss. Thanks for watching.


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[Assistant] Check out the brand new Deepsea Hub over on our website for more facts and footage about the deep sea. See you next time.


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[Assistant] Thomas is pretty unreliable. He never finishes his projects on time.


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[Assistant] Two people possess a secret so valuable, so powerful, they have to defend it at all costs.


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[Assistant] Okay, you want to play rough? Say hello to my little friend! With a little help from the governor.


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[Assistant] Nothing will prevent them from doing their job. Double the action! Get down! Triple the excitement! Get down again! This summer, nothing will stand in their way. I'm gonna make him an offer he can't refuse. Two hosts, one podcast. EnglishPod. Coming to a theater near you.


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[Assistant] Snow falls. Written by Nigel Pepperhouse. Focus question. Where and when does snow fall?


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[Assistant] Snow falls in the mountains.


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[Assistant] Snow falls on the plains.


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[Assistant] Snow falls in the forest.


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[Assistant] Snow falls on the ocean.


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[Assistant] Snow falls in the winter.


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[Assistant] What is your favorite activity to do in the snow? Draw a picture and write about it. Science. How is the weather different in the summer than in the winter? Share your ideas with a partner.


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[Assistant] That's right, this topic was actually suggested by one of our listeners.


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[Assistant] Today's lesson is about applying for a visa.


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[Assistant] Yes, and specifically it's about a visa interview.


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[Assistant] No, so a visa is an official document that you get in your passport that allows you to travel legally to a country.


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[Assistant] Right, a B2 visa is a tourist visa.


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[Assistant] Right. So Marco, we use a tourist visa when we want to be a tourist and just travel in the US. What about a resident visa?


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[Assistant] So basically a resident visa allows you to live in that country.


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[Assistant] In this dialogue, we're gonna hear two people. A visa officer and a person who's applying for the visa. Now, the person who's applying for the visa has an accent, right?


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[Assistant] But this is really good practice for helping you to understand people with different accents.


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[Assistant] Yeah, that's, that's great. But, uh, does this really happen? No.


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[Assistant] Okay, well, we can dream that this might happen for us.


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[Assistant] When you sponsor somebody for a visa, you take care of them and make sure they have enough money.


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[Assistant] So you, you are the one who's responsible for all of their expenses and making sure they just have enough money.


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[Assistant] So they took responsibility for your money. Exactly.


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[Assistant] Well, an invitation letter is a formal letter that a friend or a relative or maybe a business writes to ask you to come to their country.


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[Assistant] Yeah, and you have to give this letter to the visa officer.


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[Assistant] The ties you have to your country are the things that keep you attached to your country.


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[Assistant] Like maybe a house or a wife or a child or maybe some money in your bank account.


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[Assistant] Yeah, a good way to think of this is imagine like a rope that's attached to you and tying you to your country, to your house, to your job, to your kids.


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[Assistant] Right, so you don't have to ask your parents to pay for your ticket or pay for your food or whatever.


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[Assistant] Right, there are things of value that you own, things that are expensive that you own in your home country.


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[Assistant] Yeah, so Marco, I know you have a lot of experience with US visas. How should we answer this question?


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[Assistant] Right, but you just have to make sure that your answer matches.


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[Assistant] So showing the things that will pull you back to your home country.


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[Assistant] Yes. And Marco, I'm sure that people have already applied for visas for the US, right?


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[Assistant] And I want to hear from our users any stories that they have about applying for a visa.


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[Assistant] So visit our website at EnglishPod.com and Marco and I will be there to respond to you and answer your questions. Well everyone, thanks for listening and until next time, goodbye.


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[Assistant] Spirals. Spirals everywhere. Written by D.G. Chelsea. Focus question. Where can spirals be seen in nature?


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[Assistant] This plant has a spiral This finger has a spiral This cloud has a spiral


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[Assistant] This hair has a spiral.


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[Assistant] Sort the spirals from the book into different groups.


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[Assistant] Welcome back in this video, we're going to look at how to remove elements from an AVL tree.


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[Assistant] And what you'll discover is that removing elements from an AVL tree is almost identical to removing elements from a regular binary search tree.


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[Assistant] So just for review, I want to look at how to remove nodes


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[Assistant] In the find phase, you find the element you want to remove from the tree if it exists, and then replace it with a successor node. The successor node is necessary for us to maintain the binary search tree invariant.


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[Assistant] More details on the find phase. This is when we're searching for the element in the tree to see if it exists. And basically four things can happen. First is we hit a null node, in which case we know that the value we're looking for doesn't exist.


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[Assistant] Our comparator returns a value of zero, meaning we found the node we want to remove.


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[Assistant] The comparator value is less than zero. So the value we're looking for if it exists is going to be found in the left subtree or the comparator value is greater than zero.


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[Assistant] In which case the value if it exists is in the right subtree. So let's do an example of finding nodes in a binary search tree. Suppose we're looking for 14.


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[Assistant] Well, we should have a reference to the root node. So this is where we start. So we compare 20 and 14. And we know 14 is less than 20. So we go on the left subtree, we know 14 is greater than 10. So we go on the right subtree, we know 14 is


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[Assistant] Less than 15. So we go in the left subtree 14 is greater than 12. So the right subtree. And finally there we found it, the node we were looking for.


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[Assistant] Now let's see what happens with a node that doesn't exist. So let's try and find 26. So again, we start the root node.


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[Assistant] Then we go to the right subtree because 26 is greater than 20. Then we go to the left subtree because 26 is less than 31.


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[Assistant] And once we're at 25, we would go to the right subtree.


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[Assistant] And then discover that 26 does not exist in the tree.


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[Assistant] So once we find the node, assuming it exists, we need to replace that node with its successor. The motivation for this is that if we just remove the node without finding a successor, then there'd be a gap in the


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[Assistant] And when we're looking for successor node, one of four cases will happen. Either were a leaf node, in which case there are no subtrees.


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[Assistant] The node to remove has no left subtree, the node to remove has no right subtree, or the node to remove has both a left subtree and a right subtree. We'll see how to handle all these cases. In the first case where the node


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[Assistant] So suppose we want to remove node eight from this tree, the first thing we do is find out where eight is in the tree. So we go down the tree and then we'd found node eight.


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[Assistant] Then we discover that oh, it's a leaf node, so we can just remove it like so.


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[Assistant] Alright, now for cases two and three, where there is only a left or a right subtree. In these cases, the successor node is the immediate child of that left or right subtree.


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[Assistant] The reason the successor is the immediate node down from the node we're removing is that it is the next node which is either greater than it the case of right subtree or less than it in the case of a


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[Assistant] Left subtree. Let's do an example. Suppose we want to remove node nine, the first thing we do is find where node nine is in the tree. So start the root


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[Assistant] And go to the right subtree and find the node you want to remove, which is nine.


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[Assistant] Then we inspect nine and discover that it only has a left subtree. So the successor node is its immediate child on the left. So seven,


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[Assistant] So what we do is we get a reference to seven, and then get ready to remove nine. And then we remove nine and then make seven the successor by linking it back up to five.


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[Assistant] And if we rebalance the tree, that's what it looks like. And node nine has been removed.


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[Assistant] So the last case is when the node we're trying to remove has both a left subtree and a right subtree.


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[Assistant] So the question in this case is in which subtree will we find the successor of the node we're trying to remove.


[User] Please transcribe this text

[Assistant] And surprisingly, or not surprisingly, the answer is both. The successor can either be the largest value in the left subtree, or the smallest value in the right subtree.


[User] Please transcribe this text

[Assistant] Once the successor node has been found in either that left or right subtree, we replace the value of the node to remove with a value in the successor node.


[User] Please transcribe this text

[Assistant] However, the story doesn't end there. We must not forget to remove the duplicate value of the successor node that still exists in the tree. One common strategy to resolve this is to recursively call the function again, but with the value to remove as the value in the successor node. Let's see an example because this isn't completely trivial. Let's remove node seven from this tree, which is the root node.


[User] Please transcribe this text

[Assistant] So we would start at the root node and discover that in fact


[User] Please transcribe this text

[Assistant] This is the node we want to remove and notice that it has two non empty sub trees. So we must choose a successor.


[User] Please transcribe this text

[Assistant] To choose a successor, we either pick the smallest value in the right subtree.


[User] Please transcribe this text

[Assistant] Or the largest value in the subtree, let's find the smallest value in the right subtree. And to do this, you would go to the right once and then dig as far left as possible. So now that we found successor node 11,


[User] Please transcribe this text

[Assistant] We would copy its value into the node we're trying to remove, which is the root node seven. Notice that now there are two instances of 11 in our tree, and we want unique values in our tree. So to remove


[User] Please transcribe this text

[Assistant] The 11 that is currently highlighted, we would recursively call our remove method


[User] Please transcribe this text

[Assistant] So we stage the removal and get ready to remove 11 that we remove 11 and then hook 14 back up to 18. And if we rebalance the tree, then we can see that the duplicate 11 value is gone.


[User] Please transcribe this text

[Assistant] Alright, the moment we've been waiting for, how do we augment the binary tree removal algorithm for AVL trees? The solution is simple, you only need to add two lines of code to ensure that the tree remains balanced and that the bounce factor and height values remain up to date.


[User] Please transcribe this text

[Assistant] On the recursive callback, you invoke the update and balance methods you saw in the insert video, which ensure that when the node is removed from the AVL tree, that the tree remains balanced, it's as easy as that.


[User] Please transcribe this text

[Assistant] We'll have a look at how this is actually implemented code in the next video. So stay tuned for that.


[User] Please transcribe this text

[Assistant] You can also find some source code for the AVL tree on GitHub at github.com slash William physis slash data dash structures. Thank you for watching. If you learned something, please like this video and subscribe for more computer science and mathematics videos.


[User] Please transcribe this text

[Assistant] Yeaah, I've been meaning to talk to you about that. I might need to ask for an extension on that deadline.


[User] Please transcribe this text

[Assistant] Yeaah, I've been meaning to talk to you about that. I might need to ask for an extension on that deadline.


[User] Please transcribe this text

[Assistant] I know, and I apologize for the delay, but some things were just beyond my control. I had trouble booking the photographer, and then Michael was sick for three weeks so I couldn't include him in the photos, and the design team lost all the files so I had to redo the pictures.


[User] Please transcribe this text

[Assistant] Yeaah, I've been meaning to talk to you about that. I might need to ask for an extension on that deadline.


[User] Please transcribe this text

[Assistant] I'm sorry I haven't called you yet. I've been meaning to, but I've been busy.


[User] Please transcribe this text

[Assistant] This is an exclusive design by Damarco. It's a bargain at that price.


[User] Please transcribe this text

[Assistant] Okay, I can give you a special discount just because you seem like a nice person. 190 for both.


[User] Please transcribe this text

[Assistant] Okay, my final price, $100 for both. That's two for the price of one, and that's my last offer.


[User] Please transcribe this text

[Assistant] This is an exclusive design by Damarco. It's a bargain at that price.


[User] Please transcribe this text

[Assistant] Okay, I can give you a special discount just because you seem like a nice person. $190 for both.


[User] Please transcribe this text

[Assistant] Okay, my final price. One hundred dollars for both. That's two for the price of one. That's my last offer.


[User] Please transcribe this text

[Assistant] I really like this shirt, but it's too expensive. Can you give me a better deal?


[User] Please transcribe this text

[Assistant] This is an exclusive design by Damarco. It's a bargain at that price.


[User] Please transcribe this text

[Assistant] Okay, I can give you a special discount just because you seem like a nice person. 190 for both.


[User] Please transcribe this text

[Assistant] Okay, my final price, $100 for both, that's two for the price of one, and that's my last offer.


[User] Please transcribe this text

[Assistant] Yes, an early night would be nice. First we'll put baby Alexander to bed.


[User] Please transcribe this text

[Assistant] Why are you boring? Yeah. I ask myself that frequently.


[User] Please transcribe this text

[Assistant] Uhm, the, uh, we're trying to dig a hole, uhm, under L.A. And this is to create the beginning of what will hopefully be a 3D network of tunnels.


[User] Please transcribe this text

[Assistant] To alleviate congestion. So, I mean, right now, I think one of the most, uh, soul-destroying things is traffic. Uhm, and it affects people in every part of the world. Uh, it takes away so much of your life, and you're, it's horrible. It's particularly horrible in LA.


[User] Please transcribe this text

[Assistant] Yeah, absolutely. So this is the first time, yeah, we're just to sort of show what we're talking about. So there are a couple of key things that are important in having uhm,


[User] Please transcribe this text

[Assistant] So I think, I don't know if you will notice it in the video, but there's no real limit to how many levels of tunnel you can have. You can go much further deep than you can go up. The deepest mines are much deeper than the tallest buildings are tall. So you can alleviate any arbitrary level of open congestion


[User] Please transcribe this text

[Assistant] Yeah, it's quite difficult to dig tunnels normally. I think we need to have at least a tenfold improvement in the cost per mile of tunneling. And how could you achieve that?


[User] Please transcribe this text

[Assistant] Actually, if you just do two things, you can get to approximately an order of magnitude improvement, and I think you can go beyond that.


[User] Please transcribe this text

[Assistant] Uh, you drop the, uh, the diameter by a factor of 2 and the cross sectional area by a factor of 4. So, uh, and the tunneling cost scales with cross sectional area. So that's roughly a half order of magnitude improvement right there. Then tunneling machines, uh, currently


[User] Please transcribe this text

[Assistant] Tunnel for half the time, then they stop, and then the rest of the time is putting in reinforcements for the tunnel wall. So if you have, if you design the machine instead to do continuous tunneling and reinforcing, that'll give you a factor of two improvement. Combine that and it's a factor of eight.


[User] Please transcribe this text

[Assistant] Also, these machines are far from being at their power or thermal limit. So you can jack up the power to the machine substantially. I think you can get at least a factor to maybe a factor of


[User] Please transcribe this text

[Assistant] 4 or 5 improvements on top of that. So I think there's a fairly straight forward series of steps to get somewhere in excess of an order of magnitude improvement in a cost per mile.


[User] Please transcribe this text

[Assistant] Uhm, and uhm, our target actually is, we've got a pet snail called Gary. Uhm, this is from Gary the snail from South Park. I mean, sorry, Spongebob Squarepants.


[User] Please transcribe this text

[Assistant] So, so Gary, uh, is, is capable, uh, uh, uh, uh, currently he's capable of going 14 times faster than, than a tunnel boring machine. Okay.


[User] Please transcribe this text

[Assistant] Yeah, so uhm, we've been sort of puttering around with the Hyperloop stuff for a while. We built a Hyperloop test track adjacent to SpaceX just for a student competition to encourage innovative ideas in transport. It actually ends up being the biggest vacuum chamber in the world after the Large Hadron Collider by volume.


[User] Please transcribe this text

[Assistant] Uhm, so it was sort of quite fun to do that, but it was kind of a hobby thing.


[User] Please transcribe this text

[Assistant] And, and then uhm, we, we think we might, so we developed a little pusher card to push these, the, the student pods. Uhm, but we're gonna try seeing how fast we can make the pusher go if it's not pushing something.


[User] Please transcribe this text

[Assistant] So, I mean, so cautiously optimistic, we'll be able to be faster than a, uh, the world's fastest bullet train, even in a 0.8 mile stretch. Woah.


[User] Please transcribe this text

[Assistant] In looking at tunneling technology, it turns out that in order to make a tunnel, you have to, uh,


[User] Please transcribe this text

[Assistant] In order to seal against the water table, uh, you've got to typically design a tunnel wall to be, uh, good to about five or six atmospheres. Uhm, so to go to vacuum is only one atmosphere, or near vacuum.


[User] Please transcribe this text

[Assistant] So, uh, actually, it sort of turns out that automatically, if you build a tunnel that is good enough to resist the water table, it is automatically capable of holding backing.


[User] Please transcribe this text

[Assistant] Yeah, I think there's no real length limit. You could dig as much as you want. I think if you were to do something like a DC to New York


[User] Please transcribe this text

[Assistant] I think you'd probably want to go underground the entire way because it's a high density area.


[User] Please transcribe this text

[Assistant] Uhm, under a lot of buildings and houses. And if you go deep enough, you cannot detect the tunnel. This is, sometimes people think, well, it's going to be pretty annoying to have a tunnel dug under my house. But if that tunnel is dug more than about three or four tunnel diameters beneath your house, you will not be able to detect it being dug. At all.


[User] Please transcribe this text

[Assistant] Uhm, in fact, if you, if you're able to detect the tunnel,


[User] Please transcribe this text

[Assistant] Yeah, yeah, uhm, the, I think almost every automaker has some electric vehicle program. They vary in seriousness. Some are very serious about transitioning entirely to electric, uhm, and some are just dabbling in it.


[User] Please transcribe this text

[Assistant] And some amazingly are still pursuing fuel cells, but I think that won't last much longer.


[User] Please transcribe this text

[Assistant] I intend to stay with Tesla as far into the future as I can imagine. Uhm, and, uh, there are a lot of exciting things that we are coming. Uh, we've got, uhm, obviously the Model 3 is coming soon. Uh, we'll be unveiling the, uh, Tesla semi-truck. Uhm, and maybe... Okay, we're gonna come to this.


[User] Please transcribe this text

[Assistant] Yeah, so this is, uhm, using only cameras and a GPS. So there's no lidar or radar being used here. This is just using passive optical, which is essentially what a person uses. Uhm, the whole road system is meant to be navigated with


[User] Please transcribe this text

[Assistant] Uh, passive optical or cameras. And so, once you solve cameras, uh, or vision,


[User] Please transcribe this text

[Assistant] Uh, then autonomy is solved. If you don't solve vision, it's not solved. So that's why our focus is so heavily on having a vision neural net that's very effective for road conditions.


[User] Please transcribe this text

[Assistant] Most of it. You can absolutely be superhuman with just cameras. Like you could probably do ten times better than humans with just cameras.


[User] Please transcribe this text

[Assistant] Yea, essentially November or December of this year we should be able to go from, yea, all the way from a parking lot in California to a parking lot in New York. No controls touched at any point during the entire journey.


[User] Please transcribe this text

[Assistant] Yes, the thing that will be interesting is that I'm actually fairly confident it will be able to do that route.


[User] Please transcribe this text

[Assistant] Uhm, even if you change the route dynamically. So, it's fairly easy, if you say I'm going to be really good at one specific route, that's one thing, but uhm, it should be able to go


[User] Please transcribe this text

[Assistant] Really be very good, suddenly once you enter a highway, to go anywhere on the highway system in a given country. Uhm, so it's not sort of limited to LA, New York, we could change it and make it Seattle, Florida.


[User] Please transcribe this text

[Assistant] Or, you know, in real time. So you were going from LA to New York, now go from LA to Toronto.


[User] Please transcribe this text

[Assistant] I think that's about, that's about two years. The real trick of it is not, you know, how do you make it work, say 99.9% of the time, because like, if a car crashes, say one in a thousand times, then you're probably still not going to be comfortable falling asleep.


[User] Please transcribe this text

[Assistant] Uhm, it's, it's, the call is unlikely to crash in a hundred lifetimes or a thousand lifetimes, then people are like, okay, wow, if I would live a thousand lives,


[User] Please transcribe this text

[Assistant] So, most likely never experienced a crash, then that's probably okay.


[User] Please transcribe this text

[Assistant] There's some chance that any time a human driver gets in the car that they will have an accident. That is their fault.


[User] Please transcribe this text

[Assistant] Uhm, it's never zero. Uhm, and so the key threshold for autonomy is how much better does autonomy need to be than a person before you can rely on it.


[User] Please transcribe this text

[Assistant] Yeah, absolutely this is what will happen. So there will be a shared autonomy fleet where you buy your car and you can choose to use that car exclusively. Uhm, you could choose to have it be used only by friends and family, only by, uh,


[User] Please transcribe this text

[Assistant] Five star, other drivers who are rated five star. You can choose to.


[User] Please transcribe this text

[Assistant] That's definitely a case where we want to be cautious about the autonomy features.


[User] Please transcribe this text

[Assistant] Uhm, and this is something which, uh, people do not today think is possible, to think the truck doesn't have enough power or it doesn't have enough range. Uhm, and then with this, with the Tesla Semi, we want to show that no electric


[User] Please transcribe this text

[Assistant] Yes, so what will be really fun about this is you don't have, you have a flat torque RPM curve with an electric motor, uh, whereas with a diesel motor or any kind of internal combustion engine car, you've got a torque RPM curve that looks like a hill. So this will be a very spry truck. You could drive this around like a sports car. There's no gears, it's like single speed.


[User] Please transcribe this text

[Assistant] I mean, it's quite bizarre test driving the, you know, when I was driving the test prototype for the post truck. It's really weird because you're driving around and you're just, you're so nimble and you're in this giant truck.


[User] Please transcribe this text

[Assistant] That's a picture of a real, well, admittedly, it's a real fake house. That's a real fake house.


[User] Please transcribe this text

[Assistant] All the tiles look, the tiles look the same whether there is a solar panel behind it or a solar cell behind it or not.


[User] Please transcribe this text

[Assistant] Uhm, so you have an even, uhm, even color from the ground level. If you were to look at it from a helicopter, you would be actually able to look through and see that some of the glass tiles have a solar cell behind them and some do not.


[User] Please transcribe this text

[Assistant] Uh, plus the cost of electricity, uh, that this, that, that a solar glass roof will be less than the cost of a normal roof plus the cost of electricity.


[User] Please transcribe this text

[Assistant] So uhm, this will be economically a no-brainer, uhm, it will look, we think it will look great, uhm, and it will last, I mean, we thought about having the warranty be infinity, uhm, but then people thought, well, that might sound like we were just talking rubbish, but actually,


[User] Please transcribe this text

[Assistant] Yeah, we're starting off with two, two initially, and then the second two will be introduced early next year.


[User] Please transcribe this text

[Assistant] I mean I think eventually, uhm, I think eventually almost all houses will have a solar roof.


[User] Please transcribe this text

[Assistant] Now the thing is to consider the time scale here to be probably on the order of


[User] Please transcribe this text

[Assistant] So on average a roof is replaced every 20 to 25 years. So uhm, but you don't start replacing all roofs immediately. But eventually, if you say we're going to fast forward to


[User] Please transcribe this text

[Assistant] Say 15 years from now, it will be unusual to have a roof that does not have solar.


[User] Please transcribe this text

[Assistant] Yeah, it depends on where you are and what the house size is relative to the roof area. But it's a fair statement to say that most houses in the US have enough roof area to power all the needs of the house.


[User] Please transcribe this text

[Assistant] We'll announce locations for somewhere between 2 and 4 gigafactories later this year. Yeaah. Probably 4.


[User] Please transcribe this text

[Assistant] Uh, well I think that there's, first of all, I'm just on two advisory councils where the format consists of going around the room and asking people's opinion on things.


[User] Please transcribe this text

[Assistant] Uh, you know, I've used the meetings I've had thus far to argue in favor of immigration and in favor of climate change. Uhm, and if uhm, if I hadn't done that,


[User] Please transcribe this text

[Assistant] Yeah, so this is one of our rocket boosters coming back, uh, from very, very high, very high and fast in space. So just delivered the upper stage at high velocity. I think this may have been a sort of Mach 7 or so.


[User] Please transcribe this text

[Assistant] Well, I think visually you can see that, uhm, person.


[User] Please transcribe this text

[Assistant] I mean, in units of 747, 747 is only about a quarter million pounds of thrust, so that, that's, so there are, uhm, for every 10 million pounds of thrust there's 47, 47, so this would be the thrust equivalent of 120 747s, with all engines blazing.


[User] Please transcribe this text

[Assistant] Into orbit. This can take a fully loaded 747 with maximum fuel, maximum passengers, maximum cargo on the 747. This can take it as cargo.


[User] Please transcribe this text

[Assistant] I mean, I'm hopeful it's sort of in the eight, eight to ten year time frame. Aspirationally, that's our target. Our internal targets are more aggressive, but I think, uhm,


[User] Please transcribe this text

[Assistant] The future space ships will be truly enormous.


[User] Please transcribe this text

[Assistant] A future that is inspiring and appealing. I just think that there...


[User] Please transcribe this text

[Assistant] Like, there have to be reasons that you get up in the morning and you want to live. Like, why do you want to live? What's the point? What inspires you? What do you love about the future? And if we're not out there, if the future does not include being out there among the stars, and being a multi-planet species, I find that


[User] Please transcribe this text

[Assistant] It's incredibly depressing if that's not the future that we're gonna have.


[User] Please transcribe this text

[Assistant] Sustainable energy will happen no matter what. If there was no Tesla, Tesla never existed, it would have to happen


[User] Please transcribe this text

[Assistant] Out of necessity. It's tautological. If you don't have sustainable energy, it means you have unsustainable energy. Eventually you'll run out and the laws of economics will drive


[User] Please transcribe this text

[Assistant] This is not inevitable. It's very important to appreciate. This is not inevitable. The sustainable energy future, I think, is largely inevitable. Uh, but being a space-burning civilization is definitely not inevitable. If you look at, uh,


[User] Please transcribe this text

[Assistant] The space shuttle, the space shuttle could only take people to low Earth orbit.


[User] Please transcribe this text

[Assistant] So that's the trend. The trend is like down to nothing. This is not...


[User] Please transcribe this text

[Assistant] Who are mistaken when they think that technology just automatically improves? It does not automatically improve. It only improves if a lot of people work very hard to make it better. And actually, it will, I think, by itself, degrade, actually.


[User] Please transcribe this text

[Assistant] You look at great civilizations like ancient Egypt, and they were able to make the pyramids, and they forgot how to do that. And the Romans, they built these incredible aqueducts. They forgot how to do it.


[User] Please transcribe this text

[Assistant] That's a good idea. How you get? What? I'm borrowing your train. All change! But what am I going to do?


[User] Please transcribe this text

[Assistant] Oh dear, a traffic jam.


[User] Please transcribe this text

[Assistant] This is like a once in a lifetime opportunity. Can you believe it?


[User] Please transcribe this text

[Assistant] We're here at the biggest party in the world.


[User] Please transcribe this text

[Assistant] They're amazing. Look at that girl on top of that float. She must be the carnival queen.


[User] Please transcribe this text

[Assistant] Move over there so I can get a picture of you.


[User] Please transcribe this text

[Assistant] Good thing I studied for my exam. It was really hard.


[User] Please transcribe this text

[Assistant] It's a good thing that I bought my house before the prices went up.


[User] Please transcribe this text

[Assistant] Q Research did a study of 10,000 American adults, and they found that at this moment, we are more polarized, we are more divided than we ever have been in history. We're less likely to compromise, which means we're not listening to each other, and we make decisions about where to live.


[User] Please transcribe this text

[Assistant] According to Pew Research, about a third of American teenagers send more than a hundred texts a day. And many of them, almost most of them, are more likely to text their friends than they are to talk to them face to face.


[User] Please transcribe this text

[Assistant] Nobel Prize winners, truck drivers, billionaires, kindergarten teachers, heads of state, plumbers. I talk to people that I like. I talk to people that I don't like.


[User] Please transcribe this text

[Assistant] So I'd like to spend the next 10 minutes or so teaching you how to talk and how to listen.


[User] Please transcribe this text

[Assistant] Think of interesting things, topics to discuss in advance.


[User] Please transcribe this text

[Assistant] I'm going to teach you how to interview people, and that's actually going to help you learn how to be better conversationalists. Learn to have a conversation without wasting your time, without getting bored, and please God, without offending anybody.


[User] Please transcribe this text

[Assistant] So I have 10 basic rules. I'm going to walk you through all of them, but honestly, if you just choose one of them and master it, you're already going to enjoy better conversations. Number one.


[User] Please transcribe this text

[Assistant] Don't multitask. And I don't mean just set down your cell phone or your tablet or your car keys or whatever's in your hand. I mean, be present. Be in that moment.


[User] Please transcribe this text

[Assistant] If you wanted to state your opinion without any opportunity for response or argument or pushback or growth, write a blog.


[User] Please transcribe this text

[Assistant] The famed therapist Ebb Scott Peck said that true listening requires a setting aside of oneself. And sometimes that means setting aside your personal opinion.


[User] Please transcribe this text

[Assistant] He said that sensing this acceptance, the speaker will become less and less vulnerable and more and more likely to open up the inner recesses of his or her mind to the listener. Again, assume that you have something to learn.


[User] Please transcribe this text

[Assistant] Bill Nye, everyone you will ever meet knows something that you don't. I put it this way, everybody is an expert in something. Number three.


[User] Please transcribe this text

[Assistant] Use open-ended questions. In this case, take a cue from journalists. Start your questions with who, what, where, when, why or how.


[User] Please transcribe this text

[Assistant] If you put in a complicated question, you're going to get a simple answer out. If I ask you, were you terrified? You're going to respond to the most powerful word in that sentence, which is terrified, and the answer is, yes I was or no I wasn't. Were you angry? Yes, I was very angry. Let them describe it. They're the ones that know. Try asking them things like, what was that like? How did that feel?


[User] Please transcribe this text

[Assistant] You don't need to take that moment to prove how amazing you are or how much you've suffered.


[User] Please transcribe this text

[Assistant] Try not to repeat yourself. It's condescending and it's really boring. And we tend to do it a lot, especially in work conversations or in conversations with our kids. We have a point to make, so we just keep rephrasing it over and over. Don't do that. Number eight, stay out of the weeds.


[User] Please transcribe this text

[Assistant] Frankly, people don't care about the years, the names, the dates, all those details that you're struggling to come up with in your mind. They don't care. What they care about is you. They care about what you're like, what you have in common. So forget the details. Leave them out.


[User] Please transcribe this text

[Assistant] Number nine. This is not the last one, but it is the most important one. Listen.


[User] Please transcribe this text

[Assistant] I cannot tell you how many really important people have said that listening is perhaps the most, the number one most important skill that you could develop.


[User] Please transcribe this text

[Assistant] Buddha said, and I'm paraphrasing, if your mouth is open, you're not learning.


[User] Please transcribe this text

[Assistant] So our minds are filling in those other 275 words. And look, I know, it takes effort and energy to actually pay attention to someone. But if you can't do that, you're not in a conversation.


[User] Please transcribe this text

[Assistant] One more rule and number 10 and it's this one. Be brief.


[User] Please transcribe this text

[Assistant] You know, I grew up with a very famous grandfather and there was kind of a ritual in my home. People would come over to talk to my grandparents.


[User] Please transcribe this text

[Assistant] I keep my mouth shut as often as I possibly can. I keep my mind open and I'm always prepared to be amazed and I'm never disappointed. You do the same thing. Go out.


[User] Please transcribe this text

[Assistant] Talk to people, listen to people and most importantly, be prepared to be amazed. Thanks.


[User] Please transcribe this text

[Assistant] Do whatever it takes. I just want my little Frankie to be okay.


[User] Please transcribe this text

[Assistant] Do whatever it takes. I just want my little Frankie to be okay.


[User] Please transcribe this text

[Assistant] Do whatever it takes. I just want my little Frankie to be okay.


[User] Please transcribe this text

[Assistant] Hello English learners. Welcome back to EnglishPod. My name is Marco. And I'm Erica. And today we're bringing you a lesson that was requested by one of our listeners.


[User] Please transcribe this text

[Assistant] So, a receptionist at an office or at a hotel. So today's dialogue is...


[User] Please transcribe this text

[Assistant] Simple, but we're gonna be looking at some really great phrases.


[User] Please transcribe this text

[Assistant] That was embarrassing. That's what happens to women when they wear high heels. See?


[User] Please transcribe this text

[Assistant] Oh no, see, high heels are dangerous. I don't know why women wear them. Well...


[User] Please transcribe this text

[Assistant] I don't know, but that's not what we're here to discover. Right. Okay, so let's take a look at some of these great phrases in Fluency Builder.


[User] Please transcribe this text

[Assistant] So, Josh O'Neill said, yes, I'm here to see you, Joanna Stevens. I have an appointment at four.


[User] Please transcribe this text

[Assistant] So she is saying, I understand what you said. Yes. And then she said, may I take your name?


[User] Please transcribe this text

[Assistant] Exactly, or I would say polite to a certain extent.


[User] Please transcribe this text

[Assistant] Right, so if you meet somebody on the street or at a bar, you wouldn't say, may I take your name?


[User] Please transcribe this text

[Assistant] So usually for an office setting where the receptionist has to write down the name. Yes.


[User] Please transcribe this text

[Assistant] Okay, Miss Stevens will be with you momentarily. Will be with you momentarily. Okay, so this is really polite. Yes. Momentarily, what does that mean?


[User] Please transcribe this text

[Assistant] Miss Stevens will come out soon or Miss Stevens will see you in a minute.


[User] Please transcribe this text

[Assistant] But that's, again, it's not really that polite, right? Yes.


[User] Please transcribe this text

[Assistant] Okay, so it's pretty clear now, but there are still a couple of phrases that I would like to look at. So why don't we look at the last two sentences.


[User] Please transcribe this text

[Assistant] Miss Stevens is ready for you. So when she says ready for you, what does that mean? Prepared to speak to you. Okay. So instead of saying Miss Stevens is ready or Miss Stevens can see you now.


[User] Please transcribe this text

[Assistant] Okay, and then she said, I'll show you to her office.


[User] Please transcribe this text

[Assistant] And she followed it by saying, right this way.


[User] Please transcribe this text

[Assistant] Right. And especially if you use it together, right? I'll show you to her office, right this way, please.


[User] Please transcribe this text

[Assistant] Okay, so, it's a really great way of being polite to somebody at an office.


[User] Please transcribe this text

[Assistant] So watch your step. You see that everywhere in science. Be careful. Be careful where you step.


[User] Please transcribe this text

[Assistant] Okay, so obviously she didn't watch her step and she fell. She fell. Okay, so really great phrases. Let's listen to this dialogue one last time.


[User] Please transcribe this text

[Assistant] Alright, so a really simple dialogue, but with a lot of good phrases in there, and it's also a good review for more advanced students, right?


[User] Please transcribe this text

[Assistant] Okay, so if you have any questions or doubts, please come to our website, EnglishPod.com.


[User] Please transcribe this text

[Assistant] Okay guys, so we'll see you there, and until next time, it's... Goodbye! Bye!


[User] Please transcribe this text

[Assistant] That's right. And in this lesson, we're going to be focusing on two very, very common, but sometimes difficult questions.


[User] Please transcribe this text

[Assistant] That's right. So why don't we just get started and we'll take a listen to the dialogue and see how our interviewee handles these questions.


[User] Please transcribe this text

[Assistant] Yeah. Okay, but what isn't a controversy is the language, cause there's some great stuff in here.


[User] Please transcribe this text

[Assistant] Alright, we've got some great phrases and words for you to use when you're talking about what sort of benefits and skills and experience and expertise you can bring to a company.


[User] Please transcribe this text

[Assistant] It's basically insight and understanding and the ability to, um, make good and difficult decisions.


[User] Please transcribe this text

[Assistant] So a strong insight or understanding of technical issues.


[User] Please transcribe this text

[Assistant] Yep, but here it's a verb meaning to be really, really good at something.


[User] Please transcribe this text

[Assistant] The best. That's not really gonna help me in a job interview, but, but, the next word might.