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[Assistant] No, we haven't. Sally, this is Steve. Sally, this is Steve.


[User] Please transcribe this text

[Assistant] Sally, please meet Steve.


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[Assistant] Sally, I'd like you to meet Steve. Sally, I'd like you to meet Steve.


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[Assistant] Sally, I'd like you to meet Steve. Sally, do you know Steve?


[User] Please transcribe this text

[Assistant] You have got to meet Harriet. Sally, this is Harriet.


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[Assistant] You have got to meet Harriet. Sally, this is Harriet. Sally, do you know my cousin Jeff?


[User] Please transcribe this text

[Assistant] I'd like you to meet a friend of mine. Sally, this is Kurt.


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[Assistant] I'd like you to meet a friend of mine. Sally, this is Kurt.


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[Assistant] Hi, Russell. I am Sally.


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[Assistant] Hi, Russell. I am Sally. Hi, Heike Te, ni hao ah.


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[Assistant] Hi, Hector. How are you? Nice to meet you. I am Sally.


[User] Please transcribe this text

[Assistant] Sally, this is Cliff. Cliff, this is Sally.


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[Assistant] Sally, this is Cliff. Cliff, this is Sally. Excuse me while I get another drink.


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[Assistant] Excuse me for five minutes while I answer a phone call.


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[Assistant] Excuse me for 5 minutes while I answer a phone call. Excuse me while I check on an appointment.


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[Assistant] Ma Li, let me introduce you to our new employee, Mr. Carter.


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[Assistant] Mary, let me introduce our new employee, Mr. Carter.


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[Assistant] Mary, let me introduce our new employee, Mr. Carter.


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[Assistant] Mr. Carter, Mary is a very experienced analyst in this field.


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[Assistant] Mr. Carter, Mary is a very experienced analyst in this field.


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[Assistant] Mr. Carter, Mary organizes everything. We would be lost without her.


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[Assistant] Mr. Carter, Mary organizes everything. We would be lost without her.


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[Assistant] Mali, 容我為你介紹我們的新員工,安格斯。


[User] Please transcribe this text

[Assistant] Mary, allow me to introduce our new employee, Angus.


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[Assistant] Mary, allow me to introduce our new employee, Angus.


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[Assistant] Greg, Mary is very important to us.


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[Assistant] Greg, Mary is very important to us.


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[Assistant] Mali, please introduce the company's routine to Hamilton.


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[Assistant] Mary, please explain the office routine to Hamilton.


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[Assistant] Mary, please explain the office routine to Hamilton.


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[Assistant] I'd like to introduce you to our new employee, Louis.


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[Assistant] Mary, I'd like to introduce you to our new employee, Louis.


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[Assistant] Mary, Morris has lots of ideas about our project.


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[Assistant] Mary, Morris has lots of ideas about our project. Mary, Terry is from New York too.


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[Assistant] Mali, let me introduce our new employee, Billy.


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[Assistant] Mary, may I introduce you to Billy, our new employee.


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[Assistant] Mary, may I introduce you to Billy, our new employee.


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[Assistant] Mr. Carter, Mary is our sales manager.


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[Assistant] Mr. Carter, Mary is our sales manager.


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[Assistant] Mary, Mr. Carter, has just come back from Tokyo.


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[Assistant] Mary, Mr. Carter has just come back from Tokyo. You two will have a great deal to discuss.


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[Assistant] You two will have a great deal to discuss. I'm sure you two have lots to talk about.


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[Assistant] I'm sure you two have lots to talk about. I believe you have lots to talk about.


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[Assistant] I believe you have lots to talk about. Can you introduce me to Mr. Albright?


[User] Please transcribe this text

[Assistant] Do you think you could introduce me to Mr. Albright?


[User] Please transcribe this text

[Assistant] Do you think you could introduce me to Mr. Albright?


[User] Please transcribe this text

[Assistant] Would you mind introducing me to Mr. Albright?


[User] Please transcribe this text

[Assistant] Would you mind introducing me to Mr. Albright?


[User] Please transcribe this text

[Assistant] I need to be introduced to Mr. Albright. Can you help?


[User] Please transcribe this text

[Assistant] I need to be introduced to Mr. Albright. Can you help?


[User] Please transcribe this text

[Assistant] If you're willing, please introduce me to Mr. O'Bright.


[User] Please transcribe this text

[Assistant] Please introduce me to Mr. Albright, if you feel comfortable doing so.


[User] Please transcribe this text

[Assistant] Please introduce me to Mr. Albright, if you feel comfortable doing so.


[User] Please transcribe this text

[Assistant] I'd be very grateful if you could introduce me to Mr. Albright.


[User] Please transcribe this text

[Assistant] I'd be very grateful if you could introduce me to Mr. Albright.


[User] Please transcribe this text

[Assistant] I noticed that you're connected to Mr. Albright, and was hoping that you could introduce me.


[User] Please transcribe this text

[Assistant] I noticed that you're connected to Mr. Albright, and was hoping that you could introduce me.


[User] Please transcribe this text

[Assistant] I heard that you are well connected to Mr. Albright. Can I request an introduction?


[User] Please transcribe this text

[Assistant] I heard that you are well connected to Mr. Albright. Can I request an introduction? So, what do you do for a living?


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[Assistant] So, what do you do for a living? What is your job?


[User] Please transcribe this text

[Assistant] What is your job? 我是老师。 I am a teacher.


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[Assistant] How long have you been working for this company? 我在这里工作五年了。 I've been working here for five years.


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[Assistant] I've been working here for five years. Where are you from?


[User] Please transcribe this text

[Assistant] Where are you from? 我來自佛羅里達州。 I am from Florida.


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[Assistant] I am from Florida. How long have you been here?


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[Assistant] How long have you been here? 我最近才剛搬來,兩個月而已。


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[Assistant] I just moved here recently, only two months.


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[Assistant] I just moved here recently, only two months. Do you live around here?


[User] Please transcribe this text

[Assistant] Yes, I live on Willow Street.


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[Assistant] Yes, I live on Willow Street. No, I don't live here. My aunt lives here.


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[Assistant] No, I don't live here. My aunt lives here.


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[Assistant] What is your nationality?


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[Assistant] What is your nationality? I am American.


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[Assistant] Yeah, I volunteer for the local animal shelter.


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[Assistant] Yeah, I volunteer for the local animal shelter. Do you come here often?


[User] Please transcribe this text

[Assistant] Do you come here often?


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[Assistant] This is my first time here. I have never been here before.


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[Assistant] Have you done much traveling nearby?


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[Assistant] 我还没有时间游览,但是我很想去看看著名的海滩。


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[Assistant] I haven't had much time yet, but I really want to check out the famous beaches.


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[Assistant] I haven't had much time yet, but I really want to check out the famous beaches. What do you do in your downtime?


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[Assistant] What do you do in your downtime?


[User] Please transcribe this text

[Assistant] I like to enjoy the outdoors and go hiking.


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[Assistant] I like to enjoy the outdoors and go hiking. Where do you go to school?


[User] Please transcribe this text

[Assistant] Where do you go to school? I go to Mountain Glen High School.


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[Assistant] I go to Mountain Glen High School. How do you know Mitch?


[User] Please transcribe this text

[Assistant] He is my friend from university.


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[Assistant] We've just met. We've known each other for a long time.


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[Assistant] We've known each other for a long time. We're old friends.


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[Assistant] We take them on a journey to the spiritual heart of Australia.


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[Assistant] They always say innovation is the pirate ship that sails into the yacht club. Nobody likes it, but then they appreciate it later.


[User] Please transcribe this text

[Assistant] I realized quickly that these people didn't give a crap about what I was talking about. And so I called a break and I said, listen, I'm going to shake things up.


[User] Please transcribe this text

[Assistant] I challenged each of those groups to identify who their number one competitor was.


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[Assistant] And then I said, pretend you're that competition, pretend you have that hat on. I want you to put yourself out of business.


[User] Please transcribe this text

[Assistant] I mean, just the room lit on fire. They were so excited because I gave them permission to talk about the things that were literally verboten. It was a mindset shift as well as a business strategy shift.


[User] Please transcribe this text

[Assistant] Really what it does is give people a framework and permission to start attacking things that aren't working. And that, that's what's energizing to people is that they, they don't know the difference, Adam, between being in a groove and being in a rut.


[User] Please transcribe this text

[Assistant] And most people when you talk about complacency are in a rut. And until you talk to them about what do you wish you could change, why are you frustrated, they get pumped up.


[User] Please transcribe this text

[Assistant] Save means safe and preserve. You know, I think of a life preserver. How can we keep what we have safe versus how can we get rid of what we have and do things better? It's permission to admit that things might not be right. So you can look at what's not working and make space for things that are.


[User] Please transcribe this text

[Assistant] It was sort of what I was searching for when I was younger, like if I would have seen out trans men being a part of men's campaigns, being a part of men's fashion magazines or commercials on TV that are talking about men and masculinity, I think that my trajectory would have been drastically different as a person.


[User] Please transcribe this text

[Assistant] Are we there yet?


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[Assistant] Are we there yet? I think we might be lost.


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[Assistant] I think we might be lost. Let's stop and ask for directions.


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[Assistant] Let's stop and ask for directions. Are you from around here?


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[Assistant] I'm sorry, we're looking for a train station, but we're lost.


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[Assistant] Excuse me, we are trying to find the train station, but we've lost our way.


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[Assistant] Excuse me, we are trying to find the train station, but we've lost our way.


[User] Please transcribe this text

[Assistant] You sure have. You're on the wrong side of town.


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[Assistant] You sure have. You're on the wrong side of town. You are going in the wrong direction.


[User] Please transcribe this text

[Assistant] You are going in the wrong direction. 你们得往回走。 You need to turn around and go back.


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[Assistant] Can you tell me how to get to the train station?


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[Assistant] Can you tell me how to get to the train station? Do you know the way to the train station?


[User] Please transcribe this text

[Assistant] Do you know the way to the train station? Can you show me the way to the train station?


[User] Please transcribe this text

[Assistant] Can you show me the way to the train station? Can you give me directions to the train station?


[User] Please transcribe this text

[Assistant] Can you give me directions to the train station? How do I get to the train station?


[User] Please transcribe this text

[Assistant] 對不起,我該往哪個方向走才能到車站


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[Assistant] Excuse me, which way should I go to get to the train station?


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[Assistant] Excuse me, which way should I go to get to the train station?


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[Assistant] 对不起,我在着火站,你知道在哪里吗?


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[Assistant] Excuse me, I am trying to find the train station. Do you know where it is?


[User] Please transcribe this text

[Assistant] Excuse me, I am trying to find the train station. Do you know where it is? Go three blocks and turn left.


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[Assistant] Go three blocks and turn left. Go straight for three blocks and take a left.


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[Assistant] Walk down this street for three blocks and make a left turn.


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[Assistant] Walk down this street for three blocks and make a left turn. Take a left at the next intersection.


[User] Please transcribe this text

[Assistant] Take a left at the next intersection. Go straight until you see a park.


[User] Please transcribe this text

[Assistant] At the next traffic light, turn right.


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[Assistant] At the next traffic light, turn right.


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[Assistant] Walk up this road until you get to Oxford Street.


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[Assistant] Walk up this road until you get to Oxford Street.


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[Assistant] After that, go down Oxford Street for two blocks.


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[Assistant] After that, go down Oxford Street for two blocks.


[User] Please transcribe this text

[Assistant] Go across Regent Street and turn right.


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[Assistant] Go across Regent Street and turn right. You'll soon be at the train station.


[User] Please transcribe this text

[Assistant] You'll find it on your left.


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[Assistant] You can't miss it.


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[Assistant] It will be on your left.


[User] Please transcribe this text

[Assistant] If you pass the gas station, you will go too far.


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[Assistant] If you passed the petrol station, you went too far.


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[Assistant] If you passed the petrol station, you went too far. Did you get all that?


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[Assistant] Yes, thank you so much.


[User] Please transcribe this text

[Assistant] Yes, thank you so much.


[User] Please transcribe this text

[Assistant] So after I cross Oxford Street, what should I do?


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[Assistant] So after I cross Oxford Street, what should I do? Do you want me to draw you a map?


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[Assistant] Follow me. I'll show you the way.


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[Assistant] Follow me. I'll show you the way.


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[Assistant] Actually, I'm going there right now. Do you want to walk together?


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[Assistant] Actually, I'm going there right now. Do you want to walk together? That would be great. Thanks.


[User] Please transcribe this text

[Assistant] That would be great. Thanks. Excuse me, which way is north?


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[Assistant] It's to the left.


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[Assistant] It's to the right.


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[Assistant] What is the best way to get to the art museum?


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[Assistant] What is the best way to get to the art museum? The easiest way is to take the tube.


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[Assistant] The quickest way is to take the tube.


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[Assistant] The quickest way is to take the tube. Is it possible to walk to the art museum?


[User] Please transcribe this text

[Assistant] Is it possible to walk to the art museum? You'd better catch the bus across the street.


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[Assistant] You'd better catch the bus across the street. Sure. It will only take about 15 minutes.


[User] Please transcribe this text

[Assistant] Sure. It will only take about 15 minutes.


[User] Please transcribe this text

[Assistant] How far is the nearest underground station?


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[Assistant] How far is the nearest underground station? It's just around the corner.


[User] Please transcribe this text

[Assistant] It's just around the corner. It's a bit out of the way.


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[Assistant] It's about a five minute walk.


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[Assistant] Excuse me, where is the Grand Palace?


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[Assistant] Excuse me, where is the Grand Palace? I'm sorry. I don't know where it is.


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[Assistant] I'm sorry. I don't know where it is. I'm sorry. I'm not from here.


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[Assistant] I'm sorry, I'm not from here. I'm afraid I can't help you.


[User] Please transcribe this text

[Assistant] I'm afraid I can't help you. It's on Maple Street.


[User] Please transcribe this text

[Assistant] It's a cross from the opera house.


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[Assistant] It's a cross from the opera house. It's near the museum.


[User] Please transcribe this text

[Assistant] It's opposite the opera house.


[User] Please transcribe this text

[Assistant] It's between a park and a museum.


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[Assistant] It's between a park and a museum. It's next to a park.


[User] Please transcribe this text

[Assistant] Is there a pharmacy around here?


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[Assistant] Where is the nearest pharmacy?


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[Assistant] Where is the nearest pharmacy? Do you know where I can find a pharmacy?


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[Assistant] Do you know where I can find a pharmacy? Do you know what the name of the street is?


[User] Please transcribe this text

[Assistant] Do you know what the name of the street is? This is Maple Street.


[User] Please transcribe this text

[Assistant] Thank you very much.


[User] Please transcribe this text

[Assistant] Don't mention it. My pleasure.


[User] Please transcribe this text

[Assistant] Excuse me. Do you know how to go to Westfield Mall?


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[Assistant] Do you know where the nearest bus stop is?


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[Assistant] Do you know where the nearest bus stop is? Could you tell me how to get to the railway station?


[User] Please transcribe this text

[Assistant] Could you tell me how to get to the railway station?


[User] Please transcribe this text

[Assistant] Go down the stairs here and turn left at the crossroads.


[User] Please transcribe this text

[Assistant] Go down the stairs here and turn left at the crossroads. Turn left at the first crossing.


[User] Please transcribe this text

[Assistant] Turn left at the first crossing. Then walk two blocks to the traffic light.


[User] Please transcribe this text

[Assistant] Excuse me. Can you show me the way to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. Can you show me the way to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. Can you tell me how to get to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. Can you tell me how to get to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. Do you know the way to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. Do you know the way to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. Can you tell me where the bank is?


[User] Please transcribe this text

[Assistant] Excuse me. Can you tell me where the bank is? Excuse me. How do I get to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. How do I get to the bank?


[User] Please transcribe this text

[Assistant] Excuse me. Can you give me directions to the bank?


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[Assistant] Excuse me. Can you give me directions to the bank?


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[Assistant] Excuse me. Is there a bank around here?


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[Assistant] Excuse me. Is there a bank around here?


[User] Please transcribe this text

[Assistant] Turn left at the first street.


[User] Please transcribe this text

[Assistant] Turn left at the first street. Turn right at the petrol station.


[User] Please transcribe this text

[Assistant] Turn right at the petrol station. Turn left after the flower shop.


[User] Please transcribe this text

[Assistant] Turn left at the corner of the street.


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[Assistant] Turn left at the corner of the street. Go down the street.


[User] Please transcribe this text

[Assistant] Go straight for two blocks.


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[Assistant] Go straight for two blocks. 沿着路直走 Go along the road.


[User] Please transcribe this text

[Assistant] Go along the road. Go straight down the street.


[User] Please transcribe this text

[Assistant] Go straight down the street. Go straight until you see the traffic lights.


[User] Please transcribe this text

[Assistant] Go straight until you see the traffic lights. Keep going south until you reach the bank.


[User] Please transcribe this text

[Assistant] There is a restaurant on your left hand side.


[User] Please transcribe this text

[Assistant] You can see a school just before the lights.


[User] Please transcribe this text

[Assistant] After passing the red light, turn right on the second street.


[User] Please transcribe this text

[Assistant] After passing the lights, turn right at the second street.


[User] Please transcribe this text

[Assistant] After passing the lights, turn right at the second street.


[User] Please transcribe this text

[Assistant] After the school, go straight for two more blocks.


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[Assistant] After the school, go straight for two more blocks. Go past the clinic.


[User] Please transcribe this text

[Assistant] Cross the road.


[User] Please transcribe this text

[Assistant] It's on your right.


[User] Please transcribe this text

[Assistant] You won't miss it.


[User] Please transcribe this text

[Assistant] Thanks a lot. You're welcome. You're welcome.


[User] Please transcribe this text

[Assistant] Have you ever watched a flock of birds work together?


[User] Please transcribe this text

[Assistant] Thousands of animals flying in perfect synchrony. Isn't it fascinating?


[User] Please transcribe this text

[Assistant] What I find remarkable is that these birds would not be able to do that if they all would have to follow one leader. Their reaction speed would simply be too low. Instead,


[User] Please transcribe this text

[Assistant] Allowing every single bird to make autonomous decisions while still flying in perfect synchrony. Their alignment enables their autonomy, and their autonomy makes them fast and flexible. Now, what does this have to do with any one of us?


[User] Please transcribe this text

[Assistant] The world is getting faster and more complex, so we need a new way of working.


[User] Please transcribe this text

[Assistant] A way that creates alignment around purpose.


[User] Please transcribe this text

[Assistant] That takes out bureaucracy and that truly empowers people to make decisions faster. But the question is in order to get there, what are we willing to give up?


[User] Please transcribe this text

[Assistant] They wanted their offering to be simpler, more intuitive, more relevant. Now,


[User] Please transcribe this text

[Assistant] So let me try to illustrate what many traditional banks look like. You see lots of people in suits, taking elevators to go to their department.


[User] Please transcribe this text

[Assistant] Marketeers sitting with marketeers, engineers with engineers, et cetera.


[User] Please transcribe this text

[Assistant] You see meetings with 20 people where nothing gets decided.


[User] Please transcribe this text

[Assistant] And there are endless handovers between departments. Getting anything done can take forever. So this bank knew that in order to transform, they would have to improve their time to market.


[User] Please transcribe this text

[Assistant] By drastically changing their ways of working as well. But how?


[User] Please transcribe this text

[Assistant] To get some inspiration, we decided to go and have a look at companies that seem to be more innovative, like Google, Netflix, Spotify, Zappos.


[User] Please transcribe this text

[Assistant] And I remember how we were walking the halls at one of these companies in December 2014. A management consultant and a team of bankers.


[User] Please transcribe this text

[Assistant] We felt like strangers in a strange land, surrounded by beanbags and hoodies and lots of smart, creative employees. So then we asked, how is your company organized?


[User] Please transcribe this text

[Assistant] And we expected to get an Orchard. But instead ...


[User] Please transcribe this text

[Assistant] We tried to translate that to our own world. We asked, how many people are working for you? It depends. Who do you report to? It depends. Who decides on your priorities? It depends.


[User] Please transcribe this text

[Assistant] You can imagine our surprise. We were asking for what we thought were some of the basic principles of organizations. And their answer was, it depends.


[User] Please transcribe this text

[Assistant] Their teams were like mini startups. They had product people and IT engineers in the same team. So they could design, build and test ideas with customers independently of others in the company.


[User] Please transcribe this text

[Assistant] And we had started to like their model, so we were already thinking of how to apply some of these ideas to a bank.


[User] Please transcribe this text

[Assistant] But then one of the hosts, a guy who had not said a word all day, he suddenly said, so I see you like a model, but I have one question for you. What are you willing to give up?


[User] Please transcribe this text

[Assistant] We did not have an answer immediately, but we knew he was right.


[User] Please transcribe this text

[Assistant] Change is not only about embracing the new, it's about giving up on some of the old as well.


[User] Please transcribe this text

[Assistant] Every company has their own skeptics about why this is not going to work for them. Our product is more complex. Or they don't have the legacy IT like we do.


[User] Please transcribe this text

[Assistant] But for this bank, and also for the other companies that I have worked with afterwards, change was possible.


[User] Please transcribe this text

[Assistant] Within a year, we completely blew up the old silos between marketing, product, channels and IT. 3,000 employees were reorganized into 350 multidisciplinary teams.


[User] Please transcribe this text

[Assistant] So instead of products people sitting just with product people and engineers with engineers, a product person and an engineer are now members of the same team.


[User] Please transcribe this text

[Assistant] You could be a member of a team responsible for account opening or for the mobile banking app, et cetera.


[User] Please transcribe this text

[Assistant] Only to find out that they had been sitting two minutes away from each other, but they were sending each other emails and status reports for the last 10 years.


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[Assistant] But now, they're having coffee together every day.


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[Assistant] Autonomous decision-making requires multidisciplinary teams.


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[Assistant] Instead of decisions going up and down the organization, we want the team to decide. But to do so, we need all the skills and expertise for that decision in the team. And this brings difficult trade-offs.


[User] Please transcribe this text

[Assistant] Can we physically co-locate our people who are working in different buildings, different cities or even different countries today? Or should we invest in better video conferencing?


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[Assistant] And how do we ensure consistency in the way we do things across these teams? We still need some kind of management matrix.


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[Assistant] All these changes to structure and process and procedure, they are not easy. But in the end,


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[Assistant] I found that the most difficult thing to change is our own behavior. Let me try to illustrate.


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[Assistant] If we want these teams to be fast, flexible, creative, like a mini-startup, they have to be empowered and autonomous.


[User] Please transcribe this text

[Assistant] But this means we cannot have leaders commanding their people what to do, when to do, how to do. No micromanagers.


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[Assistant] But it also means that each employee needs to become a leader, regardless of their formal title. It's about all of us stepping up to take initiative.


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[Assistant] Now, obviously, we also cannot afford to have all these teams running in different directions, because that would certainly lead to chaos.


[User] Please transcribe this text

[Assistant] So we need alignment and autonomy at the same time, just like a flock of birds. In an organizational setting,


[User] Please transcribe this text

[Assistant] This requires new behaviors. And with each new behavior, there is giving up on something old as well.


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[Assistant] Leaders have to make sure that everyone in the organization is aligned around the overall purpose, the why, and the overall priorities, the what.


[User] Please transcribe this text

[Assistant] But then, they have to let go and trust their teams to make the right decisions on how to get there. Now,


[User] Please transcribe this text

[Assistant] Creating alignment requires open and transparent communication. But you know how they say that information is a source of power?


[User] Please transcribe this text

[Assistant] Well, for some managers, sharing information may feel as if they're giving up that source of power. And it's not just managers.


[User] Please transcribe this text

[Assistant] In these companies, the teams typically work in short sprints, and at the end of every sprint, they organize a demo session to share the output of what they've done transparently. And every day,


[User] Please transcribe this text

[Assistant] Now, all this transparency can be uncomfortable for people, because suddenly, there is no place to hide anymore.


[User] Please transcribe this text

[Assistant] Everything we do is transparent for everyone. So alignment is not easy. And providing autonomy is not so obvious either.


[User] Please transcribe this text

[Assistant] One executive at another company likes to explain how he used to be a master of milestone tracking.


[User] Please transcribe this text

[Assistant] Today, to know how things are going, instead of looking at status reports, he needs to walk down to the team floors to attend one of their sessions.


[User] Please transcribe this text

[Assistant] That is radical change for someone who used to be a master of milestone tracking. But in the old world, this executive said,


[User] Please transcribe this text

[Assistant] I only had the illusion of control. In reality, many projects would run overtime and over budget anyway.


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[Assistant] Now I have much more transparency and I can course correct much earlier if needed. And middle managers need to change as well. First of all,


[User] Please transcribe this text

[Assistant] And in the old world, there was this idea of thinkers and doers. Employees would just follow orders. But now ...


[User] Please transcribe this text

[Assistant] So imagine, for the last 10 years, you have just been telling other people what to do, but now you're expected to do things yourself again.


[User] Please transcribe this text

[Assistant] But the result is a new culture with less hierarchy.


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[Assistant] The companies that I worked with, they were used to deploying new product features a few times per year.


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[Assistant] And finally, if you walk the halls of these companies today, you just feel a new energy. It feels as if you're walking the halls of a very large startup. Now to be fair, these companies, they cannot claim victory yet.


[User] Please transcribe this text

[Assistant] But at least with this new model, they are much better prepared to respond to change. The world is getting faster and more complex, so we need to reboot our way of working. And the hardest part of that change?


[User] Please transcribe this text

[Assistant] It's not in structure or process or procedure.


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[Assistant] Leaders will be all of those in the organization who embrace the change. We all have to lead the change. So the question is, what are you willing to give up? Thank you.


[User] Please transcribe this text

[Assistant] That might not come as a surprise to some of you. I look like a woman. I'm dressed like one, I guess. The thing is, I also have balls.


[User] Please transcribe this text

[Assistant] And it does take a lot of nerve to come up here and talk to you about my genitalia. Hello.


[User] Please transcribe this text

[Assistant] But I'm not talking about bravery or courage. I mean, literally. I have balls. Right here. Right where a lot of you have ovaries. I'm not male or female. I'm intersex.


[User] Please transcribe this text

[Assistant] Most people assume that you're biologically either a man or a woman, but it's actually a lot more complex than that.


[User] Please transcribe this text

[Assistant] There's so many ways somebody could be intersex. And in my case, it means I was born with XY chromosomes, which you probably know as male chromosomes. And I was born with a vagina and balls inside my body.


[User] Please transcribe this text

[Assistant] I don't respond to testosterone, so during puberty I grew breasts, but I never got acne or body hair or body oil. You can be jealous of that.


[User] Please transcribe this text

[Assistant] We put people in boxes based on their genitalia. Before a baby's even born, we ask whether it's a boy or a girl, as if it actually matters, as if you're going to be less excited about having a baby if it doesn't have the genitals you wanted.


[User] Please transcribe this text

[Assistant] As if what's between somebody's legs tells you anything about that person. Are they kind? Generous? Funny? Smart? Who do they want to be when they grow up?


[User] Please transcribe this text

[Assistant] Genitals don't actually tell you anything, yet we define ourselves by them.


[User] Please transcribe this text

[Assistant] In this society, we love putting people into boxes and labeling each other. It kind of, it gives us a sense of belonging and knows, teaches us kind of how to interact with one another. But there's one really big problem.


[User] Please transcribe this text

[Assistant] And biological sex is not black or white. It's on a spectrum.


[User] Please transcribe this text

[Assistant] Besides your genitalia, you also have your chromosomes, your gonads, like ovaries or testicles, you have your internal sex organs, your hormone production, your hormone response, and your secondary sex characteristics, like breast development, body hair, etc.


[User] Please transcribe this text

[Assistant] Those seven areas of biological sex all have so much variation, yet we only get two options, male or female.


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[Assistant] If there are infinite ways for our bodies to look, for minds to think, personalities to act, wouldn't it make sense that there's that much variety in biological sex, too?


[User] Please transcribe this text

[Assistant] Did you know that besides XX or XY chromosomes, you could have XX and XY chromosomes? Or you could have an extra X, XXY, or two extra XX, XY.


[User] Please transcribe this text

[Assistant] Goes on from there. And for those normal people with XX or XY, what does that mean?


[User] Please transcribe this text

[Assistant] I have XY chromosomes. If my DNA is found at the scene of a crime, not saying it will, but you know, we'll see.


[User] Please transcribe this text

[Assistant] If my skeleton is discovered thousands of years from now, I'll be labeled male. Is that the truth?


[User] Please transcribe this text

[Assistant] My balls would say so. But what about the rest of me?


[User] Please transcribe this text

[Assistant] And what if a woman has ovarian cancer and has to have her ovaries removed? Does she still qualify as a woman?


[User] Please transcribe this text

[Assistant] Or about other intersex people who are born without balls or ovaries or with just one or a combination of the two. Where do they go?


[User] Please transcribe this text

[Assistant] Do you have to have a uterus to be a woman? Because a lot of us are born without one. And everyone's favorite part, genitalia.


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[Assistant] The sex and gender binary are both so ingrained in our society that we never stop to think about it.


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[Assistant] We just automatically place each other into one box or the other as if ...


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[Assistant] And if you're thinking that I'm the exception, an anomaly, an outlier,


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[Assistant] Intersex people represent around two percent of the population.


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[Assistant] It's about 150 million people, roughly, which is more than the entire population of Russia.


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[Assistant] So, there's a lot of us, needless to say. We're not new, we're rare. We're just invisible.


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[Assistant] We've existed throughout every culture in history, yet we never talk about it. In fact, a lot of people might not know that they're intersex.


[User] Please transcribe this text

[Assistant] What about a full blood panel for all of your hormone levels? A friend of mine found out last year in his 50s.


[User] Please transcribe this text

[Assistant] The executive director of Interact, which is the leading organization for intersex human rights here in the US, she found out she was intersex at age 41. Her doctors found out when she was 15, but they didn't tell her. They lied and said that she had cancer.


[User] Please transcribe this text

[Assistant] Because that seemed like an easier option than finding out she wasn't fully a woman.


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[Assistant] This kind of thing happens a lot, where intersex people are lied to or kept in the dark about our bodies, which comes as a surprise to a lot of people, but


[User] Please transcribe this text

[Assistant] We live in a society that doesn't talk about sex or bodies at all, unless it's to mock or shame each other. I found out I was intersex at age 10, and for the most part, I was fine with that information.


[User] Please transcribe this text

[Assistant] It didn't really phase me, I was still developing my understanding of the world. And it wasn't until I got older and realized that I didn't fit society's expectations of me, that I didn't belong, that I was abnormal. And that's when the shame started.


[User] Please transcribe this text

[Assistant] How many times have you seen kids play with the wrong toys for their gender? Or try on the wrong clothes? All the time, right?


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[Assistant] Kids don't have these ideas about gender norm. They don't have shame about who they're supposed to be or what they're supposed to like or love.


[User] Please transcribe this text

[Assistant] They don't care about any of this stuff. They don't have shame until we put it on them.


[User] Please transcribe this text

[Assistant] Age 10, they told me that I would also get cancer unless I removed my balls. Uhm, then they proceeded to tell me that every year.


[User] Please transcribe this text

[Assistant] Until today, there's still doctors who want me to remove them. But there's literally no reason.


[User] Please transcribe this text

[Assistant] Mine don't need to do that. They're not responding to testosterone.


[User] Please transcribe this text

[Assistant] Yet because there's such a lack of information about intersex people,


[User] Please transcribe this text

[Assistant] My doctors never understood the difference. They never really understood my body.


[User] Please transcribe this text

[Assistant] Uhm, I'm fine. My body's fine. You actually wouldn't be able to tell the difference between me and another person unless I told you. You wouldn't be able to tell that I was intersex unless I told you.


[User] Please transcribe this text

[Assistant] But again, because of the lack of understanding about bodies, my doctor didn't understand the difference. And for the most part my sex life is fine. The only issue that really comes up is that


[User] Please transcribe this text

[Assistant] Physical harm that comes from these unnecessary surgeries.


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[Assistant] That comes from living in a society that tries to cover up your existence.


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[Assistant] Most of my intersex friends have had operations like these. Oftentimes, they will remove testes like mine, even though


[User] Please transcribe this text

[Assistant] My risk of testicular cancer is lower than the risk of breast cancer in a typical woman with no predisposition, no family history. But we don't tell her to remove her breasts, do we?


[User] Please transcribe this text

[Assistant] And oftentimes, these surgeries are done to improve intersex kids' lives, but they usually end up doing the opposite, causing more harm and complications, both physical and emotional.


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[Assistant] It's just that we live in a society that causes some doctors to fix those of us who don't fit their definition of normal.


[User] Please transcribe this text

[Assistant] One of the ways I'm doing that is by creating a genderless puberty guidebook that can teach kids about their bodies as they grow up. Not their girl bodies or their boy bodies, just their bodies. We often place unrealistic expectations on the things that our bodies do that are outside of our control.


[User] Please transcribe this text

[Assistant] I mean, if one man can grow a full, luxurious hipster beard and the other can only grow a few mustache hairs, what does that mean about who they are as men? Nothing.


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[Assistant] Imagine a world where we could live in a society that teaches us not to have shame about the things that our bodies do or do not do.


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[Assistant] Not only could that knowledge save intersex kids from physical and emotional harm, I think it would help everyone else, too.


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[Assistant] Who here has ever felt inadequate or ashamed because you weren't girly enough? You were too girly. You weren't manly enough or too manly.


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[Assistant] We constantly shame people for not fitting into a box, but the reality is, I think we shame others because it prevents them from seeing that we don't fit inside our boxes either. And the truth is that nobody actually fits in a box because they don't exist.


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[Assistant] I was only 9 when my grandfather first described to me the horrors he witnessed 6 years earlier when human stampedes killed 39 people in our hometown Nashik, India. It was during the 2003 Nashik Kumbh Mela.


[User] Please transcribe this text

[Assistant] One of the world's largest religious gatherings.


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[Assistant] Every 12 years, over 30 million Hindu worshippers descend upon our city, which is built only for 1.5 million people, and stay for 45 days.


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[Assistant] The main purpose is to wash away all their sins by bathing in the river Godavari.


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[Assistant] And stampedes majorly happen because a high density crowd moves at a slow pace.


[User] Please transcribe this text

[Assistant] Apart from Nashik, this event happens in three other places in India, with varying frequency. Between 2001 and 2014,


[User] Please transcribe this text

[Assistant] In witnessing the seemingly inevitable deaths of dozens at every Kumbh Mela.


[User] Please transcribe this text

[Assistant] I thought to change this and I thought why can't I try to find a solution to this because I knew it is wrong. Having learned coding at an early age and being a maker, I considered the wild idea.


[User] Please transcribe this text

[Assistant] I considered the wild idea of building a system that would help regulate the flow of people and use it in the next Kumamela in 2015 to have fewer stampedes and hopefully fewer deaths. It seemed like a mission impossible.


[User] Please transcribe this text

[Assistant] A dream too big, especially for a 15 year old.


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[Assistant] Yet, that dream came true in 2015, when not only did we mark, when not only did we succeed in reducing the stampedes and their intensity,


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[Assistant] It was the first time in recorded history that this event passed without any casualties. How did we do it?


[User] Please transcribe this text

[Assistant] To solve this stampede problem, we wanted to know only three things.


[User] Please transcribe this text

[Assistant] Can we distribute radio frequency tokens to identify people?


[User] Please transcribe this text

[Assistant] We figured out that it would be too expensive and impractical to distribute 30 million tags.


[User] Please transcribe this text

[Assistant] Can we use CCTV cameras with image processing techniques? Again, too expensive for that scale, along with the disadvantages of being non-portable and being completely useless in the case of rain, which is a common thing to happen in Kumbh Mela.


[User] Please transcribe this text

[Assistant] Can we use cell phone tower data? It sounds like the perfect solution. But the funny part is most of the people do not carry cell phones in events like Kumbh Mela.


[User] Please transcribe this text

[Assistant] Study and waterproof and it was easy to get the data for processing. So we built a Shioto.


[User] Please transcribe this text

[Assistant] Meaning footstep in Japanese, as it consists of a portable mat,


[User] Please transcribe this text

[Assistant] Which has pressure sensors which can count the number of people walking on it and sends the data over the internet to the advanced data analysis software we created.


[User] Please transcribe this text

[Assistant] The optimum breadth of the mat was determined to be 18 inches after we tested many different versions and observed the average stride length of a person. Otherwise, people might step over the sensor.


[User] Please transcribe this text

[Assistant] We built another one with aluminium composite panels and piezoelectric plates, which are plates that generate a small pulse of electricity under pressure.


[User] Please transcribe this text

[Assistant] And people let us run these pilots because they were excited to see localites work on problems, work on problems for the city.


[User] Please transcribe this text

[Assistant] Used as a safety trigger in hazardous areas as the sensor and a black neoprene rubber sheet as the cover.


[User] Please transcribe this text

[Assistant] Now, another added benefit of using black rubber was that dust naturally accumulates over the surface, eventually camouflaging it with the ground.


[User] Please transcribe this text

[Assistant] Otherwise people might trip over it, which in itself would cause stampedes.


[User] Please transcribe this text

[Assistant] Now the data is sent to the server in real time and a heatmap is plotted, taking into account all the active devices on the ground.


[User] Please transcribe this text

[Assistant] Or if the crowd density moved beyond the desired threshold.


[User] Please transcribe this text

[Assistant] We installed five of these mats in the Nashik Kumamela 2015.


[User] Please transcribe this text

[Assistant] That the data was available in real time at various checkpoints, ensuring a safe flow of people. Now this system, eventually, with other innovations, is what helped prevent stampedes altogether at that festival.


[User] Please transcribe this text

[Assistant] I would be glad if someone uses the code to make many more gatherings safer.


[User] Please transcribe this text

[Assistant] And my new dream is to improve, adapt and deploy this system all over the world to prevent loss of life and ensure a safe flow of people.


[User] Please transcribe this text

[Assistant] Why we did this to welcome the country is to keep you safe from the land and the land will heal you as well and guide you and keep you safe. Thank you very much. Thank you.


[User] Please transcribe this text

[Assistant] My strengths in this competition have been my Indian cooking, chicken biryani with coriander and mint raita, a prawn curry, tandoori chicken with naan, as well as desserts, chopped cherry eclair, green curry cake with coconut ice cream.


[User] Please transcribe this text

[Assistant] I'm doing, uhm, a worgle green and a native spice mix jamper with, uhm, a tomato salad and I'm gonna do like a cold soup. It's almost like a gazpacho.


[User] Please transcribe this text

[Assistant] I've always cooked dishes that I know. But this one, I'm just, I just don't know.


[User] Please transcribe this text

[Assistant] Oh, oh, oh, oh, we've got a windy day. Oh my god, everything's flying everywhere.


[User] Please transcribe this text

[Assistant] Yeah, just doing my last element. Okay, good. Then I just have to kind of taste it all together and bring it together. Yeah, good. Uhm, feeling really confident actually with my tomato salad. I've just got to balance my, uhm, pesto.


[User] Please transcribe this text

[Assistant] Walnut greens aren't really too strong when it comes to the flavor profile. They act like spinach.


[User] Please transcribe this text

[Assistant] I've made a tomato salad with a tomato gazpacho, a woggle greens dampaar and some crispy saltbush.


[User] Please transcribe this text

[Assistant] Oh, to be honest, I'm terrified. Like, absolutely terrified.


[User] Please transcribe this text

[Assistant] And now it's just getting really scary because it's making it surreal.


[User] Please transcribe this text

[Assistant] This phrase also covers our own lives. Just as we are born, so shall we die. It is an unstoppable or inevitable process, and for many humans, it is one which causes a great deal of distress. But why is this so?


[User] Please transcribe this text

[Assistant] Humans are very special. You and I have a unique ability of knowing that we are alive. We are self-aware. Our conscience tells us this during every waking moment.


[User] Please transcribe this text

[Assistant] Right now I know that I'm standing in a churchyard surrounded by tombstones and graves. I'm aware of this and I know it's happening.


[User] Please transcribe this text

[Assistant] Humans are sentient beings. We learn more than just our basic instincts. We gather knowledge and we are able to feel a wide range of emotions such as happiness, sadness, loneliness and fear.


[User] Please transcribe this text

[Assistant] Although this term can cause great effects.


[User] Please transcribe this text

[Assistant] After any animal dies, it will begin to rot or decompose. The cells will break down and be absorbed, for example, into the ground.


[User] Please transcribe this text

[Assistant] The body is placed in a wooden box called a coffin and then taken to a religious place where a service normally follows. After this event, there are two options. The body can be buried underground in a grave or tomb.


[User] Please transcribe this text

[Assistant] Or it can be burned in a cremation ceremony. These days this is done in a special building called a crematorium.


[User] Please transcribe this text

[Assistant] However, in other situations the heart can continue beating after the brain has stopped functioning. This is Claster's brain death.


[User] Please transcribe this text

[Assistant] The theme of death has been used very often in many forms of literature. The playwright William Shakespeare and authors Charles Dickens and Edgar Allan Poe at some point would use death as a way of studying the human condition and our own morbid fascination with dying.


[User] Please transcribe this text

[Assistant] The word dead can be used in many ways. Instead of saying very, we can say, the party was dead good. This weather is dead cold. Your new hat is dead cool.


[User] Please transcribe this text

[Assistant] As a way of showing emptiness or silence, the room was dead. Everyone had left. The forest had a dead calm about it.


[User] Please transcribe this text

[Assistant] To show that something electrical is not working or functioning. The lights are dead. I cannot get the TV to work. It is dead. The batteries are dead. They have no energy left.


[User] Please transcribe this text

[Assistant] You only live once. This is not a rehearsal. Life is like a big performance, and once the curtain has come down on it, there will be no encore.


[User] Please transcribe this text

[Assistant] That is all from me for today. I wish you all good health, stay in the pink, live long and prosper. Thank you for watching me teaching you. This is Mr Duncan in England saying ta ta for now.


[User] Please transcribe this text

[Assistant] There's been a lot of hype about neural networks and perhaps some of that hype is justified given how well they're working.


[User] Please transcribe this text

[Assistant] But it turns out that so far, almost all the economic value created by neural networks has been through one type of machine learning called supervised learning.


[User] Please transcribe this text

[Assistant] Let's see what that means and let's go over some examples. In supervised learning,


[User] Please transcribe this text

[Assistant] You have some input x and you want to learn a function mapping it to some output y.


[User] Please transcribe this text

[Assistant] So for example, just now we saw the housing price prediction application where you input some features of a home and try to output or estimate the price y.


[User] Please transcribe this text

[Assistant] Here are some other examples that neural networks have been applied to very effectively.


[User] Please transcribe this text

[Assistant] Possibly the single most lucrative application of deep learning today is online advertising, maybe not the most inspiring, but certainly very lucrative, in which by inputting


[User] Please transcribe this text

[Assistant] Neural networks have gotten very good at predicting whether or not you click on an ad, and by showing you and showing users the ads that you're most likely to click on, this has been an incredibly lucrative application of neural networks at multiple companies.


[User] Please transcribe this text

[Assistant] Because the ability to show you ads that you're more likely to click on has a direct impact on the bottom line of some of the very large online advertising companies.


[User] Please transcribe this text

[Assistant] Computer vision has also made huge strides in the last several years, mostly due to deep learning. So you might input an image and want to output an index, say from one to a thousand, trying to tell you if this picture might be any one of say a thousand different images. So you might use that for photo tagging.


[User] Please transcribe this text

[Assistant] I think the recent progress in speech recognition has also been very exciting where you can now input an audio clip to a neural network and have it output a text transcript.


[User] Please transcribe this text

[Assistant] Say a Chinese sentence. And in autonomous driving, you might input an image, say a picture of what's in front of your car, as well as some information from a radar. And based on that, maybe a neural network can be trained to tell you the position of the other cars on the road. So this becomes a key component in autonomous driving systems.


[User] Please transcribe this text

[Assistant] So a lot of the value creation through neural networks has been through, you know, cleverly selecting what should be X and what should be Y for your particular problem and then fitting this supervised learning component into, um, often a bigger system such as an autonomous vehicle.


[User] Please transcribe this text

[Assistant] It turns out that slightly different types of neural networks are useful for different applications.


[User] Please transcribe this text

[Assistant] For example, in the real estate application that we saw in the previous video, we used a, you know, relatively standard neural network architecture, right? Maybe for real estate and online advertising might be a relatively standard, um, neural network, like, like the one that we saw.


[User] Please transcribe this text

[Assistant] For image applications, we'll often use convolutional neural networks, often abbreviated CNN.


[User] Please transcribe this text

[Assistant] And for sequence data, so for example, audio has a temporal component, right? Audio is played out over time, so audio is most naturally represented as a one-dimensional time series, as a one-dimensional temporal sequence. And so for sequence data,


[User] Please transcribe this text

[Assistant] You often use an RNN, a recurrent neural network.


[User] Please transcribe this text

[Assistant] Language, you know, English and Chinese, the alphabets or the words come one at a time, so language is also most naturally represented as sequence data, and so more complex versions of RNNs.


[User] Please transcribe this text

[Assistant] Custom or some more complex hybrid neural network architecture.


[User] Please transcribe this text

[Assistant] So just a bit more concrete about what are the standard


[User] Please transcribe this text

[Assistant] Like this, so that's a standard neural net. You might have seen pictures like this. This is an example of a convolutional neural network. And we'll see in a later course exactly what this picture means and how you can implement this. But convolutional networks are often used for image data.


[User] Please transcribe this text

[Assistant] And uhm, you might also have seen pictures like this, and you learn how to implement this in a later course. Recurrent neural networks are very good for this type of one-dimensional


[User] Please transcribe this text

[Assistant] Right, sequence data that is a, maybe a temporal component.


[User] Please transcribe this text

[Assistant] You might also have heard about applications of machine learning to both structured data and unstructured data. Here's what the terms mean. Structured data means basically databases of data.


[User] Please transcribe this text

[Assistant] So for example, in housing price prediction, you might have a


[User] Please transcribe this text

[Assistant] A database with a column that tells you the size and the number of bedrooms. So this is structured data.


[User] Please transcribe this text

[Assistant] Size of a house, the number of bedrooms, or the age of a user has a very well defined meaning.


[User] Please transcribe this text

[Assistant] In contrast, unstructured data refers to things like audio, raw audio.


[User] Please transcribe this text

[Assistant] Or images, where you might want to recognize what's in the image. Or text.


[User] Please transcribe this text

[Assistant] Here, the features might be the pixel values in an image or the individual words in a piece of text. Historically, it's been much harder for computers to make sense of unstructured data compared to structured data.


[User] Please transcribe this text

[Assistant] And in fact the human race has evolved to be very good at understanding audio cues as well as images. And then text was a more recent invention, but people are just really good at interpreting unstructured data. And so one of the most exciting things about the rise of neural networks is that


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[Assistant] Thanks to deep learning, thanks to neural networks, computers are now much better at interpreting unstructured data as well compared to just a few years ago.


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[Assistant] And this creates opportunities for many new exciting applications that use speech recognition, image recognition, natural language processing on text.


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[Assistant] Much more than was possible even just two or three years ago.


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[Assistant] I think because people have a natural empathy to understanding unstructured data, you might hear about neural network successes on unstructured data more in the media.


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[Assistant] But it turns out that a lot of the short-term economic value that new networks are creating has also been on


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[Assistant] Uhm, structured data such as much better advertising systems, much better product recommendations and just a much better ability to process the giant databases that many companies have to make accurate predictions from them.


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[Assistant] So in this course, a lot of the techniques we'll go over will apply to both structured data and to unstructured data. For the purposes of explaining the algorithms, we will draw a little bit more on examples that use unstructured data.


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[Assistant] But as you think through applications of neural networks within your own team, I hope you find both


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[Assistant] Uses for them in both structured and unstructured data.


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[Assistant] So, neural networks have transformed supervised learning and are creating tremendous economic value.


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[Assistant] It turns out though that the basic technical ideas behind neural networks have mostly been around, sometimes for many decades.


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[Assistant] So why is it then that they're only just now taking off and working so well? In the next video, we'll talk about why it's only


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[Assistant] Quite recently, the neural networks have become this incredibly powerful tool that you can use.


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[Assistant] When I first stepped into this kitchen, I was just a home cook.


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[Assistant] Today I'm planning a menu uhm, that really reflects my time in this kitchen. Uhm, it, it reflects a lot of different


[User] Please transcribe this text

[Assistant] I can do this. Feels like a lot of work, but I can do this.


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[Assistant] Nan no avi is what I'll be serving on the side of my goat Mihari for the main.


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[Assistant] I think they are going to be light and fluffy, but uh, I am so nervous right now.


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[Assistant] I am just starting to slice my kingfish portions. This is the worst possible scenario


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[Assistant] Getting into the grand finale is really slipping through my fingers. I don't know if I'm gonna pull through.


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[Assistant] And I am just starting to plate up. I think that the levers are beautiful.


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[Assistant] To plate up my nihari, I place some of the stew at the bottom of the bowl and top it off with those beautiful bones that have the bone marrow in it.


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[Assistant] I cornell a scoop of my betel leaf cardamom and fennel ice cream on top and cover it with that really delicious crunchy candied fennel.


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[Assistant] When the judges eat my dessert, I want them to really be transported to Bengal.


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[Assistant] 4A, Unit 3. I had a loose tooth.


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[Assistant] Oh yes, you have a loose tooth. You've grown up.


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[Assistant] Now I know these jewels are pretty sparkly, but trust me, you want to focus on what I'm about to tell you. Today, you're playing for an advantage, but not just any advantage.


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[Assistant] The winner of today's challenge will be catapulted straight into the grand finale.


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[Assistant] Motor, and give yourself a good amount of time at the end of the cook to make sure your dish looks as beautiful as those jewels.


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[Assistant] Mate, that was delicious. Oh great. The onion puree, you got the soup.


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[Assistant] I really like the look of it. The shape mimics the shape of the emeralds.


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[Assistant] Loved the little jewels of your gel. I think that was really smart. And it added a sweetness and a acidity that tied it all really nicely together.


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[Assistant] When you said you were cooking this, that got me thinking. I wonder how...


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[Assistant] Your version has all the flavours, but...


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[Assistant] Okay, the winner of the Ruby Jewel...


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[Assistant] Cause in a day where you could get a free ticket to the finale.


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[Assistant] One dessert, one savoury.


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[Assistant] I really enjoyed it. Thought it was really delicate. The leeks are beautifully cooked.


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[Assistant] Oyster Emulsion. I would have liked more oyster. Okay. I'm searching for a little bit more oyster. Okay.


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[Assistant] It's kinda chewy, bouncy, and then you've got a nice pop of flavour from the mangosteen, the lime, the ginger and your sorbet, and all the flavours work really well together. I just wish you'd amped up parts of it more.


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[Assistant] We asked you to create a dish around the concept of a pearl, one of the most beautiful jewels of the ocean.


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[Assistant] This is your moment. No matter what happens today, do not give up.


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[Assistant] So smile when you're in trouble, it will vanish like a bubble. Come on, just smile!


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[Assistant] It isn't any trouble, just to L-A-U-G-H. Mwah! Ha ha ha!


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[Assistant] You know, the reward for me is all in the work and the reward for me is all in just it being something that moves you. You know.


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[Assistant] No, the reward for me is all in the work. And the reward for me is all in just it being something that moves you. No.


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[Assistant] You know, the reward for me is all in the work and the reward for me is all in just it being something that moves you.


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[Assistant] In this video I want to show you a slightly more complex example where the slope of the function can be different at different points of the function.


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[Assistant] Let's start with an example. Here I plotted the function f of a equals a squared. Let's again look at the point a equals 2. So a squared, or f of a, is equal to 4.


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[Assistant] Let's nudge a slightly to the right. So now a is equal to 2.001. f of a, which is a squared, is going to be approximately


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[Assistant] 4.004. It turns out that the exact value you put on the calculator to figure this out is actually 4.004001. But I'm just going to say 4.004 is close enough.


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[Assistant] So what this means is that when a is equal to 2, let's draw this on the plot. So what we're saying is that if a is equal to 2, then f of a is equal to 4.


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[Assistant] And here the, uhm, x and y axes are not drawn to scale. Technically, this vertical height should be much higher than this horizontal height, so the x and y axes are not on the same scale.


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[Assistant] But if I now nudge A to 2.001, then F of A becomes roughly 4.004. So if you draw this little triangle again, what this means is that if I nudge A to the right by 0.001,


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[Assistant] F of A goes up four times as much by 0.8.


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[Assistant] So in the language of calculus, we say that the slope, that is the derivative, of, uhm, f of a, at a equals two,


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[Assistant] Or, to write this out with our calculus notation, we say that


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[Assistant] DDA of F of A is equal to 4 when A is equal to 2.


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[Assistant] One thing about this function f of a equals a squared is that the slope is different for different values of a. This is different than the example we saw on the previous slide. So let's look at a different point. If a is equal to 5, so instead of a equals 2, we now have a equals 5.


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[Assistant] Then a squared is equal to 25, so that's f of a.


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[Assistant] If I nudge a to the right again, a tiny little nudge to a, so now a is 5.001, then f of a will be approximately 25 point.


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[Assistant] It goes up ten times as much. So we have that d da f of a is equal to ten when a is equal to five. Because f of a goes up ten times as much as a does.


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[Assistant] So one way to see why the derivative is different at different points is that if you draw that little triangle, right, at different locations on this, you see that the ratio of the height of the triangle over the width of the triangle is very different.


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[Assistant] So here, the slope is equal to 4 when a is equal to 2, but is equal to 10 when a is equal to 5.


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[Assistant] Now, if you pull up a calculus textbook, a calculus textbook will tell you that d da of f of a, so f of a is equal to a squared, so that's d da of a squared. One of the formulas you find in the calculus textbook is that this thing, the slope of the function a squared,


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[Assistant] I'm not going to prove this, but the way you find this out is that you open up a


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[Assistant] So I'm going to take this calculus textbook to the table of formulas and it will tell you the derivative of 2 of a squared is equal to 2a. And indeed this is


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[Assistant] 2a is 2 times 2 is therefore equal to 4, and when a is equal to 5, then the slope of the function 2 times a is 2 times 5 is equal to 10.


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[Assistant] So if you ever pull up a calculus textbook and you see this formula, that the derivative of a squared is equal to 2a, all that means is that for any given value of a, if you nudge it upward by 0.2,


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[Assistant] 001, already a tiny little value, you would expect f of a to go up by 2a, that is the slope or the derivative, times however much you had nudged to the right the value of a.


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[Assistant] Now, one tiny little detail, you know, I had used these approximate symbols here. This wasn't exactly 4.004, there's an extra .001 hanging out there.


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[Assistant] It turns out that this extra .001, this little thing here is because we were nudging A to the right by 0.001. If we're instead nudging it to the right by this, you know, infinitesimally small value, then this extra error term, uhm, will go away.


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[Assistant] And you find that the amount that f of a goes up is exactly equal to the derivative times the amount that you nudge a to the right. And the reason why it's not 4.004 exactly is because derivatives are defined using these infinitesimally small


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[Assistant] Not just to A, rather than, you know, 0.001, which is not, and while 0.001 is small, it's not infinitesimally small.


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[Assistant] So that's why the amount that f of a went up isn't exactly given by the formula, but is only kind of approximately given by the derivative. To wrap up this video, let's just go through a few more quick examples. The example you've already seen is that if f of a equals a squared, then the calculus


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[Assistant] Textbook's formula table will tell you that the derivative is equal to 2a


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[Assistant] And so the example we went through was that if a is equal to 2, f of a equals 4, and if we nudge a so it's a little bit bigger,


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[Assistant] Then F of A is about 4.04. And so F of A went up four times as much. And indeed,


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[Assistant] When a is equal to 2, the derivative is equal to 4. Let's look at some other examples. Let's say instead that f of a is equal to a cubed. If you go to a calculus textbook and look up the table of formulas, you see that the slope of this function, again the derivative of this function, is equal to 3.


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[Assistant] So you can, you know, get this formula out of a calculus textbook.


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[Assistant] So what this means, so the way to interpret this is as follows. Let's take a equals two as an example again. So f of a, or a cubed, is equal to


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[Assistant] So if we give A a tiny little nudge, you find that F of A is about 8.012. And feel free to check this. Take 2.001 to the power of 3, you find that it's very close to 8.012.


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[Assistant] And indeed, when a is equal to 2, that's 3 times 2 squared, that's equal to 3 times 4 is equal to 12. So the derivative formula predicts that if you nudge a to the right by a tiny little bit, f of a should go up 12 times as much.


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[Assistant] And indeed this is true when A went up by 0.001.


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[Assistant] F of A went up 12 times as much by .012. Just one last example and then we'll wrap up.


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[Assistant] Let's say the f of a is equal to the log function, right? So I'm going to write log of a, and I'm going to use this as the base e logarithm, so some people write that as log ln of a. So if you go to a calculus textbook, you find that when you take the derivative of log of a, so this is a function that just looks like that, the slope of this function is given by 1 over a.


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[Assistant] So the way to interpret this is that if a is any value, again, let's just keep using a equals two as an example, uhm, and you


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[Assistant] Nudge A to the right by .001. You would expect F of A to go up.


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[Assistant] By 1 over a, that is by the derivative, times the amount that you increased a. So in fact, uhm, if you pull up a calculator, you find that if a is equal to 2, f of a is about 0.5.


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[Assistant] And indeed, if you look at the formula for the derivative, when a is equal to 2, d da f of a is equal to 1 half.


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[Assistant] So this derivative formula predicts that if you bump up a by .001,


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[Assistant] You would expect f of a to go up by only one half as much, and one half of .001 is 0.0005, which is exactly what we got.


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[Assistant] Right? That when A goes up by .001, going from A equals 2 to A equals 2.001,


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[Assistant] F of A goes up by half as much, so it ends up going up by approximately .0005.


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[Assistant] So if you draw that little triangle, if you will, is that if on the horizontal axis this goes up by .001, on the vertical axis, log of A goes up by half of that, so .000.


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[Assistant] Five. And so that one over a, or one half in this case, when a is equal to two, that's just the slope of this line when a is equal to two.


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[Assistant] So, that's it for derivatives. They're just two take-home messages from this video. First is that the derivative of a function just means the slope of a function.


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[Assistant] And the slope of a function can be different at different points on the function. In our first example where f of a equals 3a, that was a straight line.


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[Assistant] The derivative was the same everywhere, it was 3 everywhere. But for other functions like f of a equals a squared or f of a equals log of a, the slope of the line varies and so the slope of the derivative can be different at different points on the curve. So that's the first takeaway. Divertive just means slope of a line.


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[Assistant] Second takeaway is that if you want to look up the derivative of a function, you can flip open your calculus textbook or look up Wikipedia and often get a formula for the slope of these functions at different points.


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[Assistant] So that, I hope you have an intuitive understanding of derivatives, or of slopes of lines.


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[Assistant] Let's go on to the next video. We'll start to talk about the computation graph and how to use that to compute derivatives of more complex functions.


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[Assistant] I can play the big drum. And this is the way I do it.


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[Assistant] Oh, I know what it is. It is a little flute. But how to play the little flute?


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[Assistant] I've been suggesting that philosophy is the activity of working out the right way of thinking about things and I've been trying to explain what I mean by that and something about how we do that activity. Now one question that you might have about that


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[Assistant] It's about this notion of the right way of thinking about things.


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[Assistant] For example, how do we know in any given case that there is a right way of thinking about things?


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[Assistant] Also, how do we know that finding the right way of thinking about things is something that we can do by doing philosophy? By constructing and critically evaluating arguments? Now these are really, really important questions for philosophy. And I don't want to try and answer them now.


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[Assistant] I do want to consider what a couple of famous influential philosophers have said about those questions.


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[Assistant] And that's why I'm here at Old Colton Cemetery outside the David Hume Monument. David Hume was a famous Edinburgh-based philosopher.


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[Assistant] And he thought that a skeptical attitude towards philosophy's capacity to find out the truth about the world was entirely appropriate. One way of understanding Hume's reasons for thinking this


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[Assistant] Was that he thought that the most important thing for philosophy was that it stayed true to our experience of the world.


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[Assistant] For example, we think that we experience the world in terms of causally connected events, in terms of one thing causing another to happen. But Hume argued that causation was something that we could never really know to be a property of the world in itself.


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[Assistant] But rather was something extra that our mind is prone to add to the impressions that we get from the world. This famous example to illustrate this was of two billiard balls knocking into each other.


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[Assistant] We're prone to experience the first billiard ball is rolling into the second and causing it to roll off. But Hume suggested that all we really experience


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[Assistant] It's a series of impressions of billiard balls at various times and places, and we never experience anything extra.


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[Assistant] We're not justified in thinking that there is some self.


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[Assistant] That connects all our different experiences and thoughts and beliefs.


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[Assistant] Because all we ever really experience about us and our own minds is those thoughts and experiences and beliefs.


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[Assistant] Most famously and controversially, Hume argued that we weren't entitled, on the basis of our experience, to believe in an omnipotent and omniscient god. That's why...


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[Assistant] After he was buried here they had to post armed guards outside his tomb for several days.


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[Assistant] By doing philosophy we can learn all about the various habits that we have of associating impressions and ideas.


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[Assistant] And the various propensities that we have to draw conclusions about the world on the basis of those impressions.


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[Assistant] We can never really know whether those habits of association are the right ones.


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[Assistant] That the observation of human blindness and weakness is the result of all philosophy and meets us at every turn in spite of our endeavours to elude or avoid it.


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[Assistant] Now it was that skeptical view that the German philosopher Immanuel Kant famously said awoke him from his dogmatic slumbers.


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[Assistant] Now in that book, Kant tried to say what he meant by being awoken from his dogmatic slumbers and also what he was going to do about it. Now what he meant was that he thought that prior to reading Hume,


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[Assistant] He had just assumed that philosophy could put us in touch with facts about how the world was. And in fact he thought that all philosophers prior to Hume had just assumed that. But after reading Hume, Kant realized that we couldn't just assume that, we need to prove it. And in The Critique of Pure Rhythm, Kant tried to do that. Now the way that he did that was very complicated. But the basic idea is that he tried to show that


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[Assistant] We have to experience the world as laid out in space, as unfolding over time, and as containing causally connected events. But where can't differ from you?


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[Assistant] In fact, he thought that these were facts about what it was for there to be a world there at all. So Kant argued that if we try and imagine a world


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[Assistant] That doesn't have these features of space and time and causality. Then we just have no reason


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[Assistant] To think of what we're imagining as a world at all. We just can't get a grip on what that would mean for a world to lack these things. And so in that way, can't try to argue.


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[Assistant] So this week I've been trying to explain to you what I think philosophy is.


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[Assistant] What it really means to try and work out the right way of thinking about something. In the rest of the course,


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[Assistant] So I really hope you enjoy it and thanks very much for watching.


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[Assistant] You've heard me say that the computations of a neural network are organized in terms of a forward pass or a forward propagation step in which we compute the outputs of the neural network.


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[Assistant] Followed by a backward pause, or back propagation step, which we use to compute gradients or compute derivatives.


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[Assistant] The computation graph explains why it is organized this way. In this video, we'll go through an example.


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[Assistant] In order to illustrate the computation graph, let's use a simpler example than logistic regression or a full-blown neural network.


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[Assistant] Let's say that we're trying to compute a function j, which is a function of three variables a, b, and c. And let's say that function is three times a.


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[Assistant] Plus b times c. Computing this function actually has three distinct steps. The first is you need to compute what is b times c. And let's say we store that in a variable called u. So u is equal to b times c. And then you might compute v, which is equal to a times u. So let's say, you know, this is v. And then finally, your output j is 3 times v. So this is your final, uhm,


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[Assistant] We can take these three steps and draw them in a computation graph as follows. Let's say, uhm, I draw your three variables a, b, and c here. So the first thing we did was compute


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[Assistant] u equals b times c. So I'm going to put a rectangular box around that and so the inputs to that are b and c. And then you might have, uhm, v equals a plus u. So the inputs to that are v, uhm,


[User] Please transcribe this text

[Assistant] So the inputs to that are u, which we just computed together with a. And then finally we have j equals 3 times v.


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[Assistant] So as a concrete example, if a equals five, b equals three, and


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[Assistant] C equals two, then u equals bc with


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[Assistant] J is 3 times that, so J is equal to 33. And indeed, hopefully you can verify that, you know, this is, uh, 3 times 5 plus 3 times 2, and if you expand that out,


[User] Please transcribe this text

[Assistant] You know, you actually get, so the 3 is the value of j.


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[Assistant] So the computation graph comes in handy when there is some distinguished or some special output variable, such as j in this case, that you want to optimize. And in the case of a logistic regression, j is of course the cost function that we're trying to minimize.


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[Assistant] And what we're seeing in this little example is that


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[Assistant] Through a left to right pass, you can compute the value of j. And what we'll see in the next couple slides is that in order to compute derivatives, it will be a right to left pass.


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[Assistant] Pass like this kind of going in the opposite direction as the blue arrows


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[Assistant] Uhm, that would be most natural for computing the derivatives. So to recap, the computation graph organizes a computation with this blue arrow left to right computation. Let's defer to the next video how you can do the backward red arrow right to left computation of the derivatives. Let's go on to the next video.


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[Assistant] The word viable comes up often in conversations about melee. From veterans, newer players, spectators, and even people who don't care much for the game at all.


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[Assistant] Less valid than others. And as more and more people weigh in on the matter, the number of arguments over the subject increase, and the Reddit and Twitter replies get more and more angry, the prospect of achieving a truly satisfactory list of viable characters seems further and further away. So fuck it. Allow me to stoke the flames, but in a video form.


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[Assistant] First, let's define viable. Google defines viable as capable of working successfully, feasible. And what would working successfully be in a tournament setting? Ignoring improvement, fun, or other reasons, for the sake of argument, let's just say to work successfully in a tournament is to win.


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[Assistant] Well, every character has won a tournament at some point, counting locals of course, but to say every character in Melee is viable would not only be an unsatisfying answer, but


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[Assistant] Also, disingenuous. Obviously locals aren't what people are talking about when discussing viable characters winning tournaments. So let's narrow down the tournaments that we'll be looking at to only the top tournaments. The tippy top. Majors and super majors.


[User] Please transcribe this text

[Assistant] For the sake of this video, we'll define majors as tournaments with a few top 10 players and a larger amount of top 100, like Smash Summit, Shine, and Pound. Super majors will be defined as having many top 10 players, many top 100 players, and then some, like Genesis, Super Smash Con, and Big House.


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[Assistant] Here's a list of all the characters that have worked successfully or won a relatively recent major or supermajor without the use of secondaries. At the very least, this amount of characters, seven, should serve as an almost objective minimum to the amount of viable characters. Right?


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[Assistant] Here's where we reach the posited questions first roadblock, and it's because of this


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[Assistant] The first major a Pikachu ever placed first at was Smash Summit 8 in 2019. On his way to being crowned champion, Axe, then ranked 10th in the world, took out Wizrobe, Zane, Mango, and Leffen.


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[Assistant] Why? Well because Axe dodged his problem matchups, of course. Those problem matchups specifically being Hungrybox's Jigglypuff, who Axe has only beaten once in his entire career, and Plup, whose main Sheik, has a notoriously favorable matchup against Pikachu.


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[Assistant] Their line of thinking goes like this, if Pikachu didn't go through one or both of these players, then Axe just got lucky, and his win is either a fluke, doesn't matter, or is only possible because of his fortuitous bracket.


[User] Please transcribe this text

[Assistant] And while I agree that Axe did have a fantastic racket to succeed in the event, and I fully understand why some might have this line of thought, let me explain why it's horribly, horribly flawed.


[User] Please transcribe this text

[Assistant] And luckily for Wizzrobe, he didn't have to face Mango, whose Falco has only lost to a Captain Falcon once. Ever.


[User] Please transcribe this text

[Assistant] And yet, no one argues that Captain Falcon isn't viable for this reason. Here's another example. In January, solo Marth main Zane won Genesis. But there's one catch. He didn't face Axe, who can probably count the number of times he's lost to Marth in the last 10 years on one hand.


[User] Please transcribe this text

[Assistant] And when Mango1 get on my level that year using only Falco, he didn't face Hungrybox's Jigglypuff, who Mango has since given up trying to beat with Falco in favor of Fox, who historically does much better in the matchup. Do you see where I'm going with this?


[User] Please transcribe this text

[Assistant] Regardless of which characters or players were dodged when a character wins a major or super major, the champion has to go through several of the world's best players to win anyway. And a victory is a victory.


[User] Please transcribe this text

[Assistant] Another odd claim I've heard toward people like Axe is that because his character's success is largely only credited to one person, their character isn't actually viable. And to this I say, what?


[User] Please transcribe this text

[Assistant] What allows Axe to win extremely important tournaments are the tools Pikachu grants him. Tools that other characters, like Bowser for instance, just don't have.


[User] Please transcribe this text

[Assistant] Insanely skilled players like Axe just use what Tools Pikachu has with incredible proficiency. Just like everyone else in the top 10 does with their respective character.


[User] Please transcribe this text

[Assistant] Anyone can pick up Pikachu like Axe and, given enough time, dedication, and hard work, utilize those same tools that Pikachu gave Axe to win with to win on their own.


[User] Please transcribe this text

[Assistant] Now let's re-Google the definition and this time closely inspect this first word it uses, capable.


[User] Please transcribe this text

[Assistant] Capable of working successfully. Capable implies potential, not necessarily that it already has worked successfully. Having already won a tournament isn't what makes a character viable, though that obviously proves they are. In competitive video games, people measure viability by their potential to win significant events.


[User] Please transcribe this text

[Assistant] Because though Pikachu can win prestigious events, he doesn't have nearly as much potential as, say, Fox, Jigglypuff, and Marth.


[User] Please transcribe this text

[Assistant] This is also why Fox, Jigglypuff, and Marth are commonly placed right next to each other in tier lists currently. Even though they don't win the same amount of tournaments, they're perceived as having close to the same potential. Here's an example.


[User] Please transcribe this text

[Assistant] Though only a handful of characters out of its massive roster have actually won majors in Super Majors, Smash Ultimate players will put characters that haven't won in the same tier as characters who have. Why? Because of their potential.


[User] Please transcribe this text

[Assistant] As such, we'll be expanding our definition of viable to has already won a major or supermajor, or has shown demonstrable potential to, given an exceptionally skilled character specialist.


[User] Please transcribe this text

[Assistant] So here's where you can choose to be optimistic or a bit more pragmatic as we go through the remaining characters and decide if they're viable or not.


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[Assistant] Luckily for Melee, we have a lot of past results to work with, and we can easily choose a quantifiable method of determining viability beyond these seven characters.


[User] Please transcribe this text

[Assistant] So along with top player head to head, let's start with an extremely difficult feat for any character out of major or super major. Top 8. Championship Sunday.


[User] Please transcribe this text

[Assistant] If a character can get to top 8 and has beaten top players before, there's a realistic chance they could win a major or supermajor when being played at top level.


[User] Please transcribe this text

[Assistant] Using this metric, the list of possibly viable characters greatly expands. But their success varies. Sheik, for example, has never won a major or supermajor solo. Though Plup, a Sheik main, has won several majors and supermajors using Fox against Hungrybox.


[User] Please transcribe this text

[Assistant] Omza, a Yoshi main, has taken multiple sets from top players like Hungrybox, Mango, Axe, Mew2King, and Plup. And it's kind of surprising when he doesn't reach top 8. And while Ganon has enjoyed a small amount of top 8s at bigger tournaments, he doesn't have much success beyond that.