[User] Please transcribe this text

[Assistant] Well guys, you had 75 minutes to produce something delicious that would give us a little ooh and a little ah. A little surprise inside. Let's see how you went. Chloe, your first up.


[User] Please transcribe this text

[Assistant] Remember this moment, because this was the moment when you seriously made us three happy chappies.


[User] Please transcribe this text

[Assistant] So sophisticated. You brought the nostalgia into it, the story, which is lovely. That's what food's about. That is surprisingly, amazingly delicious. Thank you.


[User] Please transcribe this text

[Assistant] Tomorrow is a new day and the three of you need to come in refreshed. Come in with one plan, an amazing plan, because there'll be nowhere to hide.


[User] Please transcribe this text

[Assistant] So it's a braised Maryland chicken in an orange sage and cinnamon sauce sitting on a parsnip puree.


[User] Please transcribe this text

[Assistant] Vietnamese mochi cake. The surprise is that you would think it's a sweet, but when you cut inside it's actually savoury.


[User] Please transcribe this text

[Assistant] I just can't even fathom that she's in front of me, let alone having Nigella here for the whole week. I cannot believe it.


[User] Please transcribe this text

[Assistant] I love cooking dishes that showcase a part of me, a part of my heritage, but at the same time allow me to show different technique and I can't wait to showcase that with my jello today. So my passion for ice cream is in the churna and I'm just moving on to my sugar syrup for my handfuls, um, cotton candy.


[User] Please transcribe this text

[Assistant] Once I get a bit of colour on that, I'll pour that on the silkat to start cooling and then I'll start working with the candy to stretch it slightly.


[User] Please transcribe this text

[Assistant] So far, so good. I'm just waiting for my sugar syrup or my cotton candy.


[User] Please transcribe this text

[Assistant] I'm making pişmaniyeh, which is a Turkish hand-pulled cotton candy. Bit longer.


[User] Please transcribe this text

[Assistant] My biggest concern is it takes a bit of skill to do this technique and I usually use lemon juice and my sugar syrup to reduce crystallisation. But I don't have that today. So there's a big risk it may not work. Just hoping that that comes together.


[User] Please transcribe this text

[Assistant] I'm running out of time, so I get it onto the silpat mat. I start pulling in the sides.


[User] Please transcribe this text

[Assistant] Once you pull it, it should look like fine strands of hair and taste like fairy flours.


[User] Please transcribe this text

[Assistant] But, it starts to crystallise immediately.


[User] Please transcribe this text

[Assistant] I can't believe my hand-pulled cotton candy has crystallised.


[User] Please transcribe this text

[Assistant] You look really miserable. I am. What happened? My sugar was crystallizing, so yeah, it just... I'm very sorry to disappoint.


[User] Please transcribe this text

[Assistant] I didn't do so well in the mystery box challenge, not being able to pull off the hand pulled cotton candy, but I get to cook for Nigella again and I know exactly the right dish to make.


[User] Please transcribe this text

[Assistant] Now it's time to take out the metal cones and I'm holding my breath.


[User] Please transcribe this text

[Assistant] They look so good. I'm really happy I've got all the elements to this Middle Eastern version of a Cornetto.


[User] Please transcribe this text

[Assistant] My ice cream's in the churner. My cones are ready. So now I fill my cones up with the chocolate and then with the halva.


[User] Please transcribe this text

[Assistant] They're looking beautiful. They should give you this really supersonic crunch.


[User] Please transcribe this text

[Assistant] My Middle Eastern take on a Cornetto.


[User] Please transcribe this text

[Assistant] Made the kataifi pastry from scratch. Halva and cocoa inside. And date molasses ice cream.


[User] Please transcribe this text

[Assistant] I'm feeling the pressure because I feel like I've still got to prove myself. So I'm gonna put my heart and soul into it today.


[User] Please transcribe this text

[Assistant] So at this point Nigella comes to my bench. Hi.


[User] Please transcribe this text

[Assistant] So all my elements are done. The passion fruit semi-fredo is set. The thyme crumb has an earthy texture. And I'm happy with the salted caramel. It's a really good colour.


[User] Please transcribe this text

[Assistant] Today I've cooked a passion fruit semifreddo with a salted caramel sauce.


[User] Please transcribe this text

[Assistant] Five and a half years after the first attack, the police in West Yorkshire were able to announce a man had been caught.


[User] Please transcribe this text

[Assistant] Just really, raining down on my house so hard. About five times. But I remember it going down there at the back. Raining down on the back. Just, not as hard as the top.


[User] Please transcribe this text

[Assistant] But yeaah, so it was several fractures of my skull and a fracture down at the bottom there as well. Uh, those were the injuries that I sustained.


[User] Please transcribe this text

[Assistant] Two years later, in 1977, there was this unknown attack going around merging women.


[User] Please transcribe this text

[Assistant] My instinct was just telling me that this was the actual man that attacked me. So I went down to the Keter police station.


[User] Please transcribe this text

[Assistant] And they just smirked really, they just thought we were having fun and games today and they just treated it as one big joke. As opposed to taking it seriously.


[User] Please transcribe this text

[Assistant] Cause I wasn't a prostitute. I didn't put any importance on it.


[User] Please transcribe this text

[Assistant] I remember seeing his picture in a paper for the first time.


[User] Please transcribe this text

[Assistant] The police came round. I thought, what was he going to tell me? He said, Peter Sutcliffe has made a confession to Keith Halliwell. He's made two confessions. You being the primary one. I said, will they be charged with my attack? And the police just said, well, there's no point.


[User] Please transcribe this text

[Assistant] And being charged with the attack because he's already been charged with 13 others. I thought, what about me? What about me seeing justice done? I want him to be charged with something that he, there's no doubt that he did to me.


[User] Please transcribe this text

[Assistant] But I didn't realise how angry I was up until the police came.


[User] Please transcribe this text

[Assistant] I came to realise that I couldn't let it affect my life. I don't want to be living a life hating people or...


[User] Please transcribe this text

[Assistant] It's, I want to live my life and, you know, do nice things, think about nice things and, because at the end of the day, they're not worth it. The Yorkship is definitely not worth it, no. No.


[User] Please transcribe this text

[Assistant] She would be able to tell me what he looked like, where he had come from, how she met him, all the things about him that might lead me to get to him.


[User] Please transcribe this text

[Assistant] But one had to be extremely careful not to feed her stuff that you wanted her to tell you.


[User] Please transcribe this text

[Assistant] So we all decided to try to take things forward slightly differently.


[User] Please transcribe this text

[Assistant] There wasn't a lot in there, in her head, about anything. So to draw out from her what she'd seen and get her to talk about it was quite a difficult situation.


[User] Please transcribe this text

[Assistant] I knew all the Bradford and Leeds prostitutes.


[User] Please transcribe this text

[Assistant] I know, because I made it my business to say to them, look you're bloody mad. You know, what you're doing just in on. And you couldn't, you're like,


[User] Please transcribe this text

[Assistant] It was Christmas 77 after the five pound note was from the Protestant in Manchester.


[User] Please transcribe this text

[Assistant] And they came, then I went through the, through everybody about the five pound note.


[User] Please transcribe this text

[Assistant] They obviously interviewed Peter Sarcliffe at the time. They did, yes, and that's the time that Peter took Peter away to, uh, for further questioning. Uh, that was the Manchester police that did that.


[User] Please transcribe this text

[Assistant] It used to be a joke that, uh, you know, he was nicknamed the Ripper. And he used to answer to that sometimes. So it was, you know, it's rather, it's rather sort of... But it's sad now, isn't it?


[User] Please transcribe this text

[Assistant] Well, it was, he went to the office in the works, that was his nickname, which I say is pretty sad.


[User] Please transcribe this text

[Assistant] The motives for murder are many and varied, and often the most bizarre ones are advanced when an accused murderer stands trial.


[User] Please transcribe this text

[Assistant] So it was today at London's Old Bailey, where a jury must decide the sanity of Peter Sutcliffe, the man called the Yorkshire Ripper.


[User] Please transcribe this text

[Assistant] But what about Rocky Rambo? You and he were together at...


[User] Please transcribe this text

[Assistant] Do tell me. Well, there is a man in my life, and I'm going to marry him next week.


[User] Please transcribe this text

[Assistant] He's very handsome, but very shy. He's coming here soon to meet me.


[User] Please transcribe this text

[Assistant] Robert isn't interested in drinking or dancing or meeting girls. He's a very quiet person.


[User] Please transcribe this text

[Assistant] So this is all new to him. Oh look, here he comes now.


[User] Please transcribe this text

[Assistant] Robert, darling, I'd like you to meet an old school friend. Amanda, this is Robert.


[User] Please transcribe this text

[Assistant] Mmm. Wow. Mmm. Oh good, isn't it?


[User] Please transcribe this text

[Assistant] I don't know. I feel terrible. I really didn't mean to knock you over. My tire just exploded and I lost control of my bike. Really it was an accident. Please accept my apologies.


[User] Please transcribe this text

[Assistant] Yeah, that's right. I think we've met somewhere before. We met at Aaron's place last weekend. What a coincidence.


[User] Please transcribe this text

[Assistant] Oh no, I'm so sorry. Are you alright?


[User] Please transcribe this text

[Assistant] I feel terrible. I didn't mean to knock you over.


[User] Please transcribe this text

[Assistant] My tire just exploded and I lost control of my bike. Really, it was an accident. Please accept my apologies.


[User] Please transcribe this text

[Assistant] Yeah, I think we have met somewhere before. That's right, we met at Aaron's place last weekend. What a coincidence. But anyway...


[User] Please transcribe this text

[Assistant] I'm glad to see that you're not badly hurt and I should probably get going. I have a 9 o'clock meeting. But here's my number. Call me and we'll exchange insurance information.


[User] Please transcribe this text

[Assistant] No, I'm canceling my appointment so that I can stay here with you.


[User] Please transcribe this text

[Assistant] I'm so sorry. I feel terrible. Please accept my apologies.


[User] Please transcribe this text

[Assistant] I'm so sorry. I feel terrible. Please accept my apologies.


[User] Please transcribe this text

[Assistant] I didn't mean to knock you over. It was an accident.


[User] Please transcribe this text

[Assistant] I didn't mean to knock you over. It was an accident.


[User] Please transcribe this text

[Assistant] I don't know. I feel terrible. I really didn't mean to knock you over. My tire just exploded and I lost control of my bike. Really, it was an accident. Please accept my apologies. Just let me try to stand up.


[User] Please transcribe this text

[Assistant] Yeah, that's right. I think we've met somewhere before. We met at Aaron's place last weekend. What a coincidence.


[User] Please transcribe this text

[Assistant] But anyway, I'm glad to see you're not badly hurt, and I should probably get going, I've got a 9 o'clock meeting. But here's my number, call me and we'll exchange insurance information.


[User] Please transcribe this text

[Assistant] Tim, Chloe, and Kristen excel. Oh, holy schmoly. Just fabulous.


[User] Please transcribe this text

[Assistant] While Samira, Meta and Michelle found themselves in elimination. Tonight, it's back to where it all began.


[User] Please transcribe this text

[Assistant] And who's time in the MasterChef kitchen will come to an end. You're going home.


[User] Please transcribe this text

[Assistant] Samara, you're doing really well.


[User] Please transcribe this text

[Assistant] Tomorrow night. This is what you want. The first immunity challenge of the year. Getting an immunity pin would be a big advantage for me.


[User] Please transcribe this text

[Assistant] The Wind in the Willows Episode 70 On the Road Again


[User] Please transcribe this text

[Assistant] Oh, thank you, sir, said Toad. Toad jumped into the driver's seat.


[User] Please transcribe this text

[Assistant] The car started down the road. She did it! said the chipmunk. Imagine! said the squirrel. A wash woman is driving a car. Toad went a little faster.


[User] Please transcribe this text

[Assistant] He stole our car, shouted the squirrel. The raccoon tried to grab the wheel. Get your hands off, shouted Toad. They fought over the wheel.


[User] Please transcribe this text

[Assistant] Whoa! Get a load of this guy! Come in central! I think we got ourselves a situation here.


[User] Please transcribe this text

[Assistant] License and registration, please. Have you been drinking tonight, sir?


[User] Please transcribe this text

[Assistant] Step out of the vehicle, please. Sir, what do you have in the back?


[User] Please transcribe this text

[Assistant] Don't take that tone with me. Do you have an invoice for these items?


[User] Please transcribe this text

[Assistant] You are under arrest, sir. You have the right to remain silent. You better not pout, you better not cry. Anything you say can and will be used against you.


[User] Please transcribe this text

[Assistant] You have the right to an attorney. If you cannot afford one, the state will appoint one for you. Do you understand? All these rights that have just been read to you.


[User] Please transcribe this text

[Assistant] It's about time. We've been driving for 12 hours.


[User] Please transcribe this text

[Assistant] Here come the bridesmaids. Their dresses look beautiful.


[User] Please transcribe this text

[Assistant] That's the flower girl and the ring bearer.


[User] Please transcribe this text

[Assistant] I'm pretty sure they're the groom's niece and nephew. Oh, they look so cute.


[User] Please transcribe this text

[Assistant] That's all you ever think about. Food.


[User] Please transcribe this text

[Assistant] Oh, I think the bride's coming now. She looks gorgeous. Wait, what's she doing? Where's she going?


[User] Please transcribe this text

[Assistant] Our first learning algorithm will be linear regression. In this video you see what the model looks like, and more importantly you also see what the overall process of supervised learning looks like.


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[Assistant] Let's use our motivating example of predicting housing prices. We're going to use a data set of housing prices from the city of Portland, Oregon, and here we're going to plot my data set of a number of houses that were of different sizes that were sold for a range of different prices.


[User] Please transcribe this text

[Assistant] Let's say that given this dataset you have a friend that's trying to sell a house and let's say your friend's house is of size


[User] Please transcribe this text

[Assistant] 1250 square feet, and you want to tell them how much they might be able to sell to health school. Well, one thing you could do is uhm,


[User] Please transcribe this text

[Assistant] Fit a model, maybe put a straight line to this data.


[User] Please transcribe this text

[Assistant] Something like that. And based on that, maybe you could tell your friend that, let's say they can maybe sell the house for around $220,000.


[User] Please transcribe this text

[Assistant] So this is an example of a supervised learning algorithm, and it's supervised learning because we're given the, quote, right answer for each of our examples. Uh, mainly we're told what was the actual house


[User] Please transcribe this text

[Assistant] What was the actual price that each of the houses in our dataset were sold for?


[User] Please transcribe this text

[Assistant] And moreover, this is an example of a regression problem, where the term regression refers to the fact that we're predicting a real value output, namely the price. And just to remind you, the other type, the other most common type of supervised learning problem is called the classification problem, where we predict discrete values outputs, such as if


[User] Please transcribe this text

[Assistant] We are looking at cancer tumors and trying to decide if a tumor is malignant or benign. So there's a zero one value to speed up.


[User] Please transcribe this text

[Assistant] More formally, in supervised learning, we have a data set, and this data set is called a training set. So for a housing crisis example, we have a training set of different housing prices.


[User] Please transcribe this text

[Assistant] Let's define some notation that we're using throughout this course. We're going to define quite a lot of symbols. It's okay if you don't remember all the symbols right now, but as the course progresses it'll be useful to have a convenient notation.


[User] Please transcribe this text

[Assistant] So I'm going to use lowercase m throughout this course to denote the number of training examples. So in this data set, if I have, you know, let's say 47 rows in this table, then I have 47 training examples and m equals 47.


[User] Please transcribe this text

[Assistant] And I'm going to use y to denote my output variables or the target variable which I'm trying to predict. So that's this second column here. A little bit more notation. I'm going to use x comma y to denote a single training example.


[User] Please transcribe this text

[Assistant] So, a single row in this table corresponds to a single train example.


[User] Please transcribe this text

[Assistant] And to refer to a specific training example, I'm going to use this notation, x i comma z y i.


[User] Please transcribe this text

[Assistant] And, uh, I'm going to use this to refer to the Ith training example.


[User] Please transcribe this text

[Assistant] This is not exponentiation, right? This xiyi, the superscript i in parentheses, that's just an index into my training set and it refers to the i-th row in this table. Okay, so this is not x to the power of i, y to the power of i. Instead, xiyi just refers to the i-th row of this table. So, for example,


[User] Please transcribe this text

[Assistant] 1416, right, this is second X, and, uh, Y1 will be equal to 460, is this. The first, the Y value for my first training example is what that 1 refers to.


[User] Please transcribe this text

[Assistant] So as I mentioned, occasionally I'll ask you a question, uh, to let you check your own understanding.


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[Assistant] In a few seconds in this video, a multiple choice question will pop up in the video.


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[Assistant] When it does, please use your mouse to select what you think is the right answer.


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[Assistant] We started with a training set, like our training set of housing crisis, and we feed that to our learning algorithm.


[User] Please transcribe this text

[Assistant] Which by convention is usually denoted lowercase h, and h stands for hypothesis.


[User] Please transcribe this text

[Assistant] And what the job of the hypothesis is, is a function that takes as input the size of a house, like maybe the size of a new house that, you know, your friend is trying to sell, so it takes in a new value of x, and it tries to output the estimated value of y.


[User] Please transcribe this text

[Assistant] People often ask me, you know, why is this function called a hypothesis? Some of you may know


[User] Please transcribe this text

[Assistant] The meaning of the term hypothesis from the dictionary or from science or whatever,


[User] Please transcribe this text

[Assistant] For this sort of function for mapping from sizes of houses to the predictions that, you know, I, I think, uh, the term hypothesis maybe isn't the best possible name for this, but it's what, it's, it's the standard terminology that people use in the Q&A now. So don't worry too, don't worry too much about why people call it that.


[User] Please transcribe this text

[Assistant] When designing a learning algorithm, the next thing we need to decide is how do we represent this hypothesis H. For this and the next few videos, I'm going to choose


[User] Please transcribe this text

[Assistant] Our initial choice for representing the hypothesis will be the following. We're going to represent h as follows. We're going to write this as h subscript theta of x equals theta 0 plus theta 1 of x.


[User] Please transcribe this text

[Assistant] As a shorthand, sometimes instead of writing, you know, h subscript theta of x, sometimes as a shorthand I'll just write this as h of x, but more often I'll write it as a subscript theta over there.


[User] Please transcribe this text

[Assistant] And plotting distant pictures, all this means is that we are going to


[User] Please transcribe this text

[Assistant] You know, predict that y is a linear function of f.


[User] Please transcribe this text

[Assistant] Right, so that's a data set, and, uh, what this function is doing is it's predicting that y is some straight line function of x. That's x equals state zero plus state of x. Okay? And, uhm, why a linear function? Well,


[User] Please transcribe this text

[Assistant] Sometimes we'll want to fit more complicated, perhaps non-linear functions as well, but since this linear case is the simpler building block, we'll start with this example first of fitting linear functions and we'll build on this to eventually have more complex models and more complex learning algorithms.


[User] Please transcribe this text

[Assistant] This model is called linear regression, or this for example is actually linear regression with one variable.


[User] Please transcribe this text

[Assistant] So, that's learning regression. In the next video, we'll start to talk about just how to go about implementing this model.


[User] Please transcribe this text

[Assistant] Good to see you back. How are you? How's the hand? I'm good. I had to get stitches, but uhm, in a couple of days, this is all coming off. That's good news. How many stitches did you have to have? Thirteen.


[User] Please transcribe this text

[Assistant] As I'm walking to the judges, I notice that there are two cafes on each end. And they're empty.


[User] Please transcribe this text

[Assistant] You've got the hot smoked salmon with the creme fraiche and then just topped with a poached egg and asparagus. Classic but delicious.


[User] Please transcribe this text

[Assistant] Kristen puts her hand up straight away and I think the team all agree she's going to be a perfect captain for today.


[User] Please transcribe this text

[Assistant] Today I'm working with Hodart doing a cornflake parfait. So it's like a layered breakfast dessert.


[User] Please transcribe this text

[Assistant] Cornflakes are toasted and now they're infusing on the stove in the panna cotta mix.


[User] Please transcribe this text

[Assistant] I want the flavour of the panna cotta to be similar to when you leave your corn flakes in the bowl for a while and the milk starts to taste like corn flakes.


[User] Please transcribe this text

[Assistant] I'm really happy with the flavor of the strawberry sorbet. Tastes just like fresh strawberries, the same as what you have on top of your cereal in the morning.


[User] Please transcribe this text

[Assistant] The Cornflake Parfait is going well at this stage. We've got the nice creaminess of the Cornflake Panna Cotta with the smooth strawberry sorbet.


[User] Please transcribe this text

[Assistant] So the way the layers are working for our cornflake path 8 is that we have the cornflake panna cotta on the bottom with some of that kinefi crumb on top and then we have the rosewater macerated strawberries and then finish with the strawberry sorbet.


[User] Please transcribe this text

[Assistant] As the desserts are going out, I'm super happy with them. The crumb isn't a texture I'm really familiar with. It's really grainy, and I think there may be some concerns that...


[User] Please transcribe this text

[Assistant] Overall the flavours are very yummy and we're getting a lot of orders.


[User] Please transcribe this text

[Assistant] Brendan and I were working together as partners in the salmon dish and we still have so much to do. Being one man down in this challenge is really gonna hurt.


[User] Please transcribe this text

[Assistant] He might be booming and cutting through concrete, but it is awesome.


[User] Please transcribe this text

[Assistant] After the shock realisation of Brendan hurting himself and getting taken to hospital, I think we pulled together really quickly.


[User] Please transcribe this text

[Assistant] Good morning, welcome to the MasterChef kitchen. As you can see, Matt can't be with us again this morning. Good to see a few smiles on your faces. Tough day yesterday and I bet you're absolutely exhausted. But think about what you did.


[User] Please transcribe this text

[Assistant] You fed the Melbourne Football Club at the MCG. And this is the MasterChef experience you wanted, right?


[User] Please transcribe this text

[Assistant] So if you enjoyed that pressure, if you got a buzz from that pressure, regardless of the fact that you're standing here now in black, then you're in the right place. Show us you deserve to be here. Aldo? Yes, Gary? You got everything on the line?


[User] Please transcribe this text

[Assistant] You've got 75 minutes. Open pantry, open garden. We're gonna be tasting everybody's dishes.


[User] Please transcribe this text

[Assistant] And obviously whoever makes the least impressive dish will be going home. Be careful and prove to us that you belong in this kitchen.


[User] Please transcribe this text

[Assistant] Can you stop it? Gary's getting weak at the knees. I'm getting hungry already, that's what's happening. But I'm just worried that, looking at the clock, you're gonna have a chance to cook those char-


[User] Please transcribe this text

[Assistant] Because that's the delicious part, right? But it all comes down to that.


[User] Please transcribe this text

[Assistant] Trying to whip those over-whipped egg whites into that soft mixture. Because the problem with over-whipping the egg whites, folding it into a sponge mixture, doesn't expand properly, does it?


[User] Please transcribe this text

[Assistant] The flavour's not too bad. I don't mind the acidity in that chilli lime dressing. But they're just, they're like little bullets.


[User] Please transcribe this text

[Assistant] He's missing out because he'd like that. Yeah. And I think the reason he'd like it.


[User] Please transcribe this text

[Assistant] And I think the problem with that is she's made a salad, but rather than using lots of colour, it's all very one-dimensional, and the little boil-y bits of, of trotta, uhm, yeaah, it's gotta taste pretty damn good.


[User] Please transcribe this text

[Assistant] She reached that kind of soft deliciousness that makes a trotter really special. She hedged her bets, cooked a trotter, and didn't have time.


[User] Please transcribe this text

[Assistant] A dish that inspired you to fall in love with food. That's what we asked you to do and we gave you 75 minutes.


[User] Please transcribe this text

[Assistant] There were three dishes that stood out in particular.


[User] Please transcribe this text

[Assistant] Beautiful chocolate mousse, lovely crumb, and that little coconut snow.


[User] Please transcribe this text

[Assistant] Absolutely delicious. But as much as we love that interpretation of the lambington, we love that connection with you. You're grand, was it? Yeah. Well done. Well done.


[User] Please transcribe this text

[Assistant] Aldo, we loved that dish. George Giger, when you told the story of poking that panna cotta, but more than that is finding something like Thai food and then to translate that into that panna cotta dish was beautifully well balanced and a very clever little dish. Well done, mate.


[User] Please transcribe this text

[Assistant] Brilliant. We love the radish cake. It was complex, it was interesting. So lots of little bits and pieces in there to love. Beautiful.


[User] Please transcribe this text

[Assistant] You should work on that and turn that into a signature. Brilliant stuff.


[User] Please transcribe this text

[Assistant] Denise, it's a sad day for you, but it's a sad day for us because we know that you're a great cook.


[User] Please transcribe this text

[Assistant] Since you've been with us, you've given us some cracking dishes. Even yesterday, the sopes was brilliant. The chicken in orange and sage sauce. The lamb in your addition.


[User] Please transcribe this text

[Assistant] Your cooking's always been interesting, it's always been challenging, and unfortunately, if you don't get it right, on the most important days, you find yourself gone.


[User] Please transcribe this text

[Assistant] Denise, whatever happens, the very best of luck from us, and I'm sure from these guys. But Denise, it's time to say goodbye.


[User] Please transcribe this text

[Assistant] To now have a chance at winning an immunity pin, it would just continue what's already been a fantastic week.


[User] Please transcribe this text

[Assistant] A pancake recipe is a pancake recipe. It shouldn't be too difficult.


[User] Please transcribe this text

[Assistant] But to make it something spectacular is a bit trickier. What are you vibing? Making a yoghurt sorbet. Oh nice.


[User] Please transcribe this text

[Assistant] And the sorbet brings a lot of freshness and tartness to the dish. I make a simple sugar syrup. I dissolve some gelatin into that and combine that with the yoghurt and get it into the channa.


[User] Please transcribe this text

[Assistant] Remember what's at stake here. You're cooking for one of these shiny numbers. Immunity, you win one of these.


[User] Please transcribe this text

[Assistant] You wear it with pride, and if you get in a little pickle, you can use it.


[User] Please transcribe this text

[Assistant] You're gonna have 45 minutes to bring your best version of a pancake with whatever you want to put with it. Bring us the best pancake and you go through to round two.


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[Assistant] Loki, whatever you choose, oranges or lemons.


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[Assistant] They must be present in a significant way in your dish.


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[Assistant] Wow, I'm intrigued. Alana, St Peter, Matt, you've eaten there. I've eaten there. The food is exceptional. On the flip side, Loki is an awesome contestant.


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[Assistant] That's a cracking start to this lemony tasting. Shall we get the next dish in?


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[Assistant] That's a chunk of fish, isn't it? Smells amazing. Can I? Yeah, that just smells, and the sauce looks awesome. You know it's gonna have bags of flavour.


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[Assistant] This is exactly how I cook it at home. From my mother that taught me to cook the pasta all the way down to my grandson.


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[Assistant] Looks a really, really beautiful consistency, that's for sure.


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[Assistant] I can't believe he's standing in front of me.


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[Assistant] Seriously, Nathan Jones. Incredible. Look at his tattoos. They're awesome. I can't believe he's standing in front of me.


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[Assistant] Well let's do it guys. So I'm on the blue team.


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[Assistant] Which is so not my colour, but we get what we're given.


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[Assistant] I was singing too loudly. I was too pleased with myself.


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[Assistant] I'm a bit too fat to run so much.


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[Assistant] Heads. Back home I work at a butcher. Happy days.


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[Assistant] Part of the brief today is for us to construct a menu that needs to not only be delicious, but nutritious at the same time.


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[Assistant] Two canapés, a main and a dessert is going to require a lot of work.


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[Assistant] Naturally. We decide to use Scotchpillet.


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[Assistant] For the canapes, we've got the beef in the oven, which I'm really happy about. Denise is cooking up her sopes, basically like a little Mexican flatbread, filled with goat's cheese and white bean puree.


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[Assistant] We see the guest start to arrive. It's starting to feel real.


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[Assistant] For the meat canapé, we've decided to make a rare roast beef with pickled celery, shaved parmesan and a balsamic glaze.


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[Assistant] The canapes are due out so shortly. There's so much riding on this beef. The original plan for our canapes is just not going to work anymore. We've got to adapt the dish now.


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[Assistant] Now what we're going to do is serve it into little cubes. Dress it with a balsamic glaze.


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[Assistant] Top it with a bit of pickled celery and then just finish it off with the shaved parmesan.


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[Assistant] We've gotta get the beef out the door. I'm not completely happy with the way it is.


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[Assistant] But I'm really, really happy with the way this whole piece has turned out. It looks stunning.


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[Assistant] It's time to plate the main course. There's a lot of pressure as to how the dish will be plated because it needs to look really beautiful.


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[Assistant] I come to the first Lamerac, I look at it, it's blushing, and I'm really, really happy. Guys, I'm really happy!


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[Assistant] The grain salad is so completely delicious, but you wouldn't believe it's really healthy. And then just to top it off with a really nice cooked lamb rack is just delicious.


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[Assistant] My dish is a lamb rack, so we qualify three ways, a pea puree and a beer and lamb jus.


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[Assistant] Dessert, please make him land. Not doing a dessert for me is risky, as it's outside of my comfort zone, but I'm fully aware that if I want to go well in this competition, I need to perfect all types of savoury cooking.


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[Assistant] So I've only ever cooked lamb rack once before, so I'm not really sure how I'll go. I'm a little bit worried that the lamb should be cooked red.


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[Assistant] I'm just hoping that it is just where it needs to be so that I can get tasted. Hopefully this will give me a chance to get into the immunity challenge.


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[Assistant] So the next step is to start the lamb. I'm gonna start in a really, really hot pan. Just to start to brown up that fat a little bit. Oh, that's looking so crispy!


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[Assistant] Yeah, not too long at all. And then I gotta say that I'm still working on, um, it's... Get in the oven.


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[Assistant] I really hope I can do enough and get in the top five, because I'd love Gordon to take my dish. However, everyone's basically doing land, so I know today it needs to be absolutely spot on.


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[Assistant] So I just used the outer sides, like needed 30 more seconds, which I think is just on the brink of being rare so that I can get tasted.


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[Assistant] I'm completely shocked. Like, I wasn't sure if I've done enough. And I'm just so excited for going and trying my food.


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[Assistant] What have you cooked? Lamb rack with cauliflower puree and then braised cauliflower.


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[Assistant] I just hope now I've done enough to get into that immunity challenge. I did not expect that at all.


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[Assistant] I just wanna do something basic, so I wanna stick with the beef burger.


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[Assistant] Hopefully can make it shine with different elements that add to the actual burger.


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[Assistant] I'm doing a beef burger. I really love like when you have the burger and you have bacon in it, but I've actually got the bacon in the mince.


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[Assistant] Uhm, I'm gonna put some, uhm, jalapeno jam on top.


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[Assistant] Gordon really likes the sound of the dish, so it's really cool to know that I'm on the right track. Today there's a chance to go into that immunity challenge. And I really, really, really want to get there.


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[Assistant] I'm pretty happy with my burger and my side. I think all the flavours work and I just hope now I've done enough to get into that immunity challenge.


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[Assistant] I made a beef and bacon burger with lemon mayo and a jalapeno jam and then a truffle salt onion ring.


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[Assistant] I had the best time of the day with my onion rings. It's awesome. Can this day get any better?


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[Assistant] Matrix multiplication is really useful since you can pack a lot of computation into just one matrix multiplication operation. But you should be careful of how you use them. In this video I want to tell you about a few properties of matrix multiplication.


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[Assistant] When working with just real numbers, or when working with uh, scalars,


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[Assistant] Multiplication is commutative, and what I mean by that is if you take 3 times 5, that is equal to 5 times 3. And the ordering of this multiplication doesn't matter. And this is called the commutative property.


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[Assistant] If a and b are matrices, then in general a times b is not equal to b times a. So just be careful of that. It's not okay to arbitrarily reverse the order in which you multiply matrices. So we say that matrix multiplication is not commutative. It's a fancy way of saying it. As a concrete example,


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[Assistant] It turns out, if you multiply these two matrices, you get the second answer on the right. And, you know, well clearly, these two matrices are not equal to each other.


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[Assistant] So, in fact, in general, if you have a matrix operation like A times B,


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[Assistant] Then it turns out that the matrix A times B


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[Assistant] Right, is going to be an m by m matrix. Whereas the matrix B times A is going to be


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[Assistant] An n by n matrix. So the dimensions don't even match, right? So that's A times B.


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[Assistant] And b times a may not even be the same dimension.


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[Assistant] In the example on the left, I had all 2 by 2 matrices, so the dimensions were the same, but, you know, in general, reversing the order of the matrices can even change the dimension of the outcome. So matrix multiplication is non-commutative.


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[Assistant] Here's the next property I want to talk about. So when talking about real numbers or scalars, let's say I have 3 times 5


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[Assistant] times two. I can either multiply


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[Assistant] 5 times 2 first, and I can compute this as 3 times 10, or I can multiply


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[Assistant] 3 times 5 for us, and I can compute this as, you know, 15 times 2.


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[Assistant] And both of these give you the same answer, right? Each, both of these is equal to 32. So, so if it doesn't matter whether I multiply, uhm, 5 times 2 first, or whether I multiply 3 times 5 first, because sort of a, well, 3 times 5 times 2 is equal to 3 times 5 times 2. And this is called the associative property of row number multiplication.


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[Assistant] It turns out that matrix multiplication is associative. So concretely, let's say I have a product of three matrices A times B times C. Then I can compute this either as A times B times C or I can compute this as A times B times C.


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[Assistant] So just to be clear what I mean by these two cases, let's look at the first one, right, this first case. What I mean by that is if you actually want to compute a times b times c,


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[Assistant] What you can do is you can first compute b times c, so that d equals b times c, then compute a times d. So this is really computing a times b times c. Or, for this second case,


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[Assistant] You can compute this as, you can set E equals A times B, then compute E times C, and this is then the same as, you know, A times B.


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[Assistant] Times c, and it turns out that both of these, both of these options will give you, is guaranteed to give you the same answer. And so we say that matrix multiplication does enjoy the associative property. Okay.


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[Assistant] And don't worry about the terminology associative and commutative. That's what it's called, but I'm not really going to use this terminology later in this class, so don't worry about memorizing those terms. Finally,


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[Assistant] So let's again make the analogy to what we know of real numbers. So when dealing with real numbers or scalar numbers, the number one is, you can think of it as the identity.


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[Assistant] What I mean by that is that for any number z, you know, the number 1 times z is equal to z times 1, and that's just equal to the number z, right, for any, for any real number z.


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[Assistant] So one is the identity operation and sort of satisfies this equation.


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[Assistant] So it turns out that there's, in the space of matrices, there's an identity matrix as well, and it's usually denoted.


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[Assistant] I, or sometimes we write it as I of n by n. We want to make explicit the dimensions. So I subscript n by n is the n by n identity matrix.


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[Assistant] And here are a few examples. Here's the 2 by 2 identity matrix.


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[Assistant] Here's a three by three identity matrix. Here's a four by four identity matrix. So the identity matrix has the property that it has ones along the diagonals.


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[Assistant] And zero everywhere else. And so, by the way, the one by one identity matrix, you know, is just the number one. The one by one matrix is just one in it. So it's not a very interesting identity matrix. And informally,


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[Assistant] When I or others are being sloppy, very often we'll write the identity matrices and final notation, like draw.


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[Assistant] Square brackets, just write 1, 1, 1, dot, dot, dot, dot, 1, and then we'll maybe somewhat sloppily write a bunch of zeros there.


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[Assistant] And uh, it turns out that the identity matrix says properly that for any matrix A,


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[Assistant] A times identity equals I times A equals A. So that's a lot like this equation that we had up here, right?


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[Assistant] So 1 times z equals z times 1 equals z itself. So i times a equals a times i equals a.


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[Assistant] Just let me show you the dimensions, right? So if A is an m by n matrix, then this identity matrix here, that's an n by n identity matrix. And if A is n by n,


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[Assistant] Then this identity matrix, right, for matrix multiplication that makes sense, that has to be an m by m.


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[Assistant] Matrix, because this M has to match up that M.


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[Assistant] And in either case, the outcome of this process is you get back the matrix A, which is M by N.


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[Assistant] So whenever we write the identity matrix I, you know, very often the dimension,


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[Assistant] Right, will be implicit from the context. So these two i's, they're actually different dimension matrices. One may be n by n, the other is n by m. But when we want to make the dimension of the matrix explicit, then sometimes we'll write it as i subscript n by n, kind of like we had up here. But very often the dimension will be implicit. Finally, I just want to point out that


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[Assistant] Earlier I said that a times b is not, in general, equal to b times a.


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[Assistant] Right? That, you know, that for most matrices A and B this is not true. But when B is the identity matrix, this does hold true.


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[Assistant] That A times the identity matrix doesn't D equal to identity times A. It's just that, you know, this is not true for other matrices B in general.


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[Assistant] In the next and final video on our linear algebra review, I'm going to quickly tell you about a couple of special matrix operations and after that you need everything you need to know about linear algebra for this class.


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[Assistant] For the dessert plating, we place the crumb on the right hand side. We're also piping three dollops of the white chocolate mousse, the two types of jelly, passion fruit, and finally we've got two clorails of the mango sorbet.


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[Assistant] Well hello everyone and welcome to EnglishPod. My name's Erica. And I'm Marco. So Marco, how are you doing today?


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[Assistant] Okay, so we've got an elementary lesson about going to the eye doctor. Yes. Well, let's get started then with our vocabulary preview.


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[Assistant] We have three words today in our vocabulary preview. All three words come from our dialogue. Our first word is struggle. Struggle. Struggle. Struggle. So Marco, when I struggle to do something, what does that mean?


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[Assistant] Often when you go to the doctor and you need some medicine, he writes out a prescription.


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[Assistant] Well this guy really has poor vision, hey?


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[Assistant] Next word is far sighted. Far sighted. Far sighted.


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[Assistant] So if I'm farsighted, I can't see very well, right?


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[Assistant] But things that are close are blurry. Okay. And the opposite would be? Nearsighted!


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[Assistant] So this is a really funny sounding expression, one of these weird English idioms.


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[Assistant] Exactly, so it's not like you actually are blind, right?


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[Assistant] Okay, alright, we saw four great words today in our language takeaway. Now I think we can listen to our dialogue another time.


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[Assistant] So we saw a couple useful phrases in this dialogue and I think we can show you how to use these phrases in a few different ways.


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[Assistant] We can use this same expression in a number of different ways. Let's listen.


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[Assistant] Yeah, it's a great way of asking, what's the problem? So now let's take a look at another phrase.


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[Assistant] We heard in the dialogue, the doctor said, head on over to the other room.


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[Assistant] Exactly. Let's hear three examples. Example one.


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[Assistant] So like when you can't tell the difference between red and blue and green.


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[Assistant] EnglishPod.com. Also, if you have questions about today's lesson or any other lesson, please come and visit our website and, uh, ask us.


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[Assistant] Topic, convex mirror. Why is a convex mirror used as a rear view mirror?


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[Assistant] Wow, what an amazing car. But your rear view mirror is missing. Huh?


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[Assistant] See, I was correct. Now put the convex mirror and see the result.


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[Assistant] Look, the image is much smaller, right? Do you know what the difference between the two mirrors was?


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[Assistant] This is because the concave mirror will magnify the object and we will see a very enlarged image.


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[Assistant] Thus, we require a mirror which gives us a wider view of the vehicles behind us.


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[Assistant] In this case, a convex mirror proves to be the right choice. This is because a convex mirror forms a highly diminished image. Thus making the traffic look much smaller. As a result, we can see a large number of vehicles in a very small mirror.


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[Assistant] Now already just looking at you in those jackets. I love it. You look the part and you're immaculate. I mean you are really immaculate. Now let it go. Come out of your comfort zone. Cook your hearts out. One amazing chance today to cook against a pro and kick them up the arse.


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[Assistant] Alright, focus. So be smart with it. Great proteins in the pantry. Match with those incredible vegetables, knock it out of the park.


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[Assistant] Reese, where are you going? What's happening? Work and talk, pick up and just give me some ideas.


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[Assistant] Take advantage of those first 15 minutes. This is where you can nail this competition.


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[Assistant] Got that button, that squash, that's gonna take a lot longer, so prioritize young lady. Rice, literally 18 minutes. Fork it through, let it steam. Prioritize the list of importance. Come on, you got this. 10 minutes gone guys, yes? 65 minutes to go.


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[Assistant] You're 15 minutes in front of those pros, but right now, hey, they're absolutely crapping themselves.


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[Assistant] Our contestants had to choose between fruit and vegetables. They chose...


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[Assistant] The vegetables need to be apparent across the dish. It's not the hero, but they need to be centre stage, understood?


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[Assistant] Young man, you're flying the flag for Scotland. Young lady, one of the most talented pastry chefs in Australia. And young man, potentially.


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[Assistant] The next best young chef in the world. Got it? Yes, Chef. No pressure. Are we ready? Ready. Yes, Chef. Your 60 minutes starts now. Let's go.


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[Assistant] Ginger, you can use. Vegetable root. Please, no fruit.


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[Assistant] So you can either go down there and smash that whole thing through there, or, you go through there like that.


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[Assistant] You take out this centre bone here, or you take off those lovely breasts there, and you've got the two breasts.


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[Assistant] What's the leaks for? What's going through your mind? Oh, I'm not sure yet. You're not sure yet? You've put leaks in your...


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[Assistant] They're kicking ass there. We're the same age, we're from the same town in Scotland, we gotta keep that flag flying high. But I don't want you to win.


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[Assistant] Remember time wise, prioritize. Now look at me. There's no point going to cook rice.


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[Assistant] Remember time wise, prioritize. Now look at me, there's no point going to cook rice now.


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[Assistant] That shouldn't be overcooked, okay? If you're in doubt, start again. Don't kill the food.


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[Assistant] Well done. What a challenge. All of you. Give yourselves a round of applause. Brilliant.


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[Assistant] Gordon, how did it go? Tremendous performance. I think all six had highs and lows. I'm hoping the contestants kicked ass.


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[Assistant] There's something quite magical about the way Reese thinks.


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[Assistant] He goes off-piste, but he's so confident off-piste. Normally, any pro is a little bit agitated. That guy tonight stayed.


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[Assistant] Focused, and he knew what he wanted to execute. He's up against a talented young chef, but there's a talented amateur, dying to become a pro.


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[Assistant] It's them, I've just helped bring it out of them, but they did it. You guys haven't quite realized what you've just done.


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[Assistant] Take this insight and continue climbing this incredible ladder. And who knows, you could make it to the top.


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[Assistant] Some good steely looks, we love that. Welcome back to the MasterChef kitchen and Gordon. Glad to be back, thank you. If there's one thing you can be guaranteed of, when you see Gordon Ramsay in front of you, dressed in chef whites, you know it's going to be an exciting day.


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[Assistant] You gotta stay focused though buddy, you've got a long way to go, huh? Chloe, we can't slow down now.


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[Assistant] Check the consistency. Let's go. You need to stay on top of this. You've done so well. Keep it going.


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[Assistant] Go on, start cutting these circles out, guys. We're gonna make three. Okay?


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[Assistant] Just get all three of them out. You need to move it. Let's go Ben, stay focused. Blaze with the bisque. Nice.


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[Assistant] I think the reason MasterChef is such a good teacher is just the roller coaster of challenges and emotions. Look at what they've been through the last couple of days. Tough, on the three of them, but I think they did okay. They were honest, you know, involved and packed


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[Assistant] Look, I mean, there's obviously going to be a difference. I mean, look how long you've been cooking and you're at the top of the game and have been for many, many years. Uhm, and to see somebody that really, you know, has only just started out in the competition, cooks at home.


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[Assistant] For me though, it's uhm, I'd like more. And that tells me straight away that it's a good dish and he's done a very good job.


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[Assistant] How did you digest the whole challenge and tackle this one?


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[Assistant] Yeaah. But, they're at home watching you going, look at mum!


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[Assistant] Yeah. The depth of flavour that's missing. That richness that's missing. And that's what that crustacean sauce does for the dish. So if I'm eating lobster, if I'm eating marin, I want big flavours.


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[Assistant] Absolutely brilliant, and what Gordon said. Because once you'd cut your fingers, we just thought there was no way you were going to do it. So kudos to you, really.


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[Assistant] And we felt that, you know, in the end, that showed.


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[Assistant] Normally there's only three or four in an elimination challenge, but with all the benches set up, there are nine cooking today and it's gonna be hardcore.


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[Assistant] Time starts and we get to our bench to see the recipe. It's seven bloody pages long.


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[Assistant] Might be seven pages, but I've just gotta understand and read it through carefully.


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[Assistant] I learned a lot from cooking along with Gordon. Really took that advice to be clean and methodical. Just trying to take that same approach.


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[Assistant] Good job, Kristen. Just about to crack on with deboning the chicken.


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[Assistant] Working my fingers in between and making sure that I don't tear anything. Getting all the skin off and still intact. I think I've done pretty well.


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[Assistant] I'm really stoked that George is really liking the look of my consomme. It gives me a boost to kick on with this dish.


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[Assistant] Once the chicken's browned off, I get a mirror pile of veggies in there and start to get some real colour on them. Keep working that back in on the time. And I mean, there to go black. Correct.


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[Assistant] I need to deglaze the pan with some white wine and add some chicken stock. I need to let it simmer for 30 minutes.


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[Assistant] I have to pay close attention. I've really got to get depth of flavor, just like Matt's consomme.


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[Assistant] Once I've set the herb oil aside, I move back to my consomme to get it drained off and ready for the raft. The purpose of the raft is to make the consomme clear.


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[Assistant] And not have any lumps or impurities in it whatsoever.


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[Assistant] 200 grams of egg whites and some herbs and blitz it in the food processor. Pouring the raft into the stock


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[Assistant] It will cook the egg whites and float to the top of the consomme.


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[Assistant] It's time to plate up. I've gotta strain the consomme off and get it in the jug. I only need 30 mils. It all comes down to how clear the consomme is. It's looking really good. Tastes really good too.


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[Assistant] I think being a part of just cooking this dish has just been an amazing experience.


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[Assistant] Hey guys. Just as good as cooking along with Gordon the other day.


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[Assistant] I'm really happy with few of the elements on my dish. Consumé tastes great and pouring it out on the plate, it looks fantastic.


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[Assistant] After cooking with Gordon the other day, it was just a real eye-opener.


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[Assistant] It's just definitely proving to myself that I can and do deserve to be here. I love showing the other guys, you know, what I can do.


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[Assistant] Like it's got that really good crunch from the pine nuts and the pop of the pomegranate seeds. The meat is cooked really well with the eggplant. Yeah, good flavor. Samira?


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[Assistant] Whispered in the dark, this question begins a tale of conspiracy, deception, and moral ambiguity. And in a play where everyone has something to hide, its answer is far from simple.


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[Assistant] Written by William Shakespeare between 1599 and 1601, Hamlet depicts its titular character haunted by the past, but immobilized by the future.


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[Assistant] Mere months after the sudden death of his father, Hamlet returns from school a stranger to his own home.


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[Assistant] And deeply unsure of what might be lurking in the shadows. But his brooding takes a turn when he's visited by a ghost that bears his father's face. The Phantom claims to be the victim of a murder most foul. And convinces Hamlet that his uncle Claudius usurped the throne and stole Queen Gertrude's heart.


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[Assistant] The prince's mourning turns to rage, and he begins to plot his revenge on the new king and his court of conspirators.


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[Assistant] The play is an odd sort of tragedy, lacking either the abrupt brutality or all-consuming romance that characterized Shakespeare's other work in the genre. Instead, it plumbs the depths of its protagonist's indecisiveness and the tragic consequences thereof.


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[Assistant] The ghost's revelation draws Hamlet into multiple dilemmas. What should he do? Who can he trust? And what role might he play in the course of justice?


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[Assistant] These questions are complicated by a tangled web of characters, forcing Hamlet to negotiate friends, family, court counselors, and love interests, many of whom possess ulterior motives.


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[Assistant] The prince constantly delays and dithers over how to relate to others and how he should carry out revenge. This can make Hamlet more than little exasperating.


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[Assistant] Rather than rushing into things, Hamlet becomes consumed with the awful machinations of thinking itself. And over the course of the play, his endless questions come to echo throughout our own racing minds.


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[Assistant] To accomplish this, Shakespeare employs his most introspective language. From the usurping king's blazing contemplation of heaven and hell, to the prince's own cackling meditation on mortality, Shakespeare uses melancholic monologues to breathtaking effect.


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[Assistant] This monologue personifies Hamlet's existential dilemma, being torn between thought and action, unable to choose between life and death.


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[Assistant] But his endless questioning raises yet another anxiety. Is Hamlet's madness part of a performance to confuse his enemies?


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[Assistant] Or are we watching a character on the brink of insanity?


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[Assistant] These questions weigh heavily on Hamlet's interactions with every character, and since he spends much of the play facing inward, he often fails to see the destruction left in his wake.


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[Assistant] He's particularly cruel to Ophelia, his doomed love interest who is brought to madness by the prince's erratic behavior. Her fate is one example of how tragedy could have been easily avoided and shows the ripple effect of Hamlet's toxic mind games.


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[Assistant] Similar warning signs of tragedy are constantly overlooked throughout the play.


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[Assistant] Sometimes these oversights occur because of willful blindness, such as when Ophelia's father dismisses Hamlet's alarming actions as mere lovesickness. At other points, tragedy stems from deliberate duplicity, as when a case of mistaken identity leads to yet more bloodshed.


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[Assistant] These moments leave us with the uncomfortable knowledge that tragedy evolves from human error.


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[Assistant] Even if our mistake is to leave things undecided.


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[Assistant] For all these reasons, perhaps the one thing we never doubt is Hamlet's humanity.


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[Assistant] So the main thing I got out of Golden Week was probably a bit more confidence. I felt...


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[Assistant] I'm working on the chocolate ganache. I'm super excited. I really love the sound of Janine's idea today.


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[Assistant] Great. Yeah, I'm gonna- Make sure it's light and delicious. Thanks guys.


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[Assistant] Okay, so ganache is done. My time is nearly up. And I take the tart out of the oven.


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[Assistant] I'm not 100% sure on the tart shell, like, I'm just not sure if it'll hold nicely, so I'm thinking of turning it into a crumb and then having the Cornell of the chocolate ganache, the Cornell of the ice cream.


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[Assistant] Do you know, I wanted to do a top, but I'm not happy with it, so I want to crumb it and do a deconstructed top.


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[Assistant] Hey, how's it going? Hey, how's it going?


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[Assistant] So, how shall I begin? This is the blurb for the course, the blurb that's been in the Yale catalog for a long time. This is a course on, uh, finance. It has the word markets in the name, uh, which suggests that it's about trading.


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[Assistant] But I think it's a broad course in fi-finance.


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[Assistant] Directing resources across space and time to their best uses. So this sounds broader. I guess the course is broader. I wrote the title of the course many years ago, uh, when I created this course, and it's been a title for it.


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[Assistant] Uh, see what really to me this course is about is how we get things done in our society. That's how we incentivize people, uh, to do things. Now, most of us are in our lives thinking about ourselves, that's human nature, and about our particular place in the life cycle. So, uh,


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[Assistant] You may be a young person who's thinking about getting started in life. Uh, but when you join a enterprise or an organization, uh, you have to do things for the organization and you have to take a different perspective.


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[Assistant] Uh, you have to help manage a productive venture that involves many people. So there aren't that many things that you can do as an individual that are useful. You have to join an organization. This is a fundamental principle of human life.


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[Assistant] Uh, so this is a course about understanding how the institutions work, uh, and how we can predict what will happen.


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[Assistant] So that's what this course is about. I don't consider this a vocational course, because I think it should be of interest to anybody who is interested in how things work. On the other hand, this course


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[Assistant] Comes across as more vocational than most Yale courses. And to some extent I pride myself on that. Although I consider myself an intellectual.


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[Assistant] Uh, this is a relevant course, alright. It's not about how to make money. Uh, you might say it is, I suppose. But, uh, it's about making things work.


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[Assistant] These are the topics, uh, in this course.


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[Assistant] Uh, risk insurance, diversification, history of finance, innovation, efficient markets, behavioral finance. Actually, behavioral finance is a little bit more prominent than you might think from its appearance as number seven on this list.


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[Assistant] Uh, behavioral finance is the application of psychology, sociology, other social sciences to understanding financial events.


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[Assistant] It's a revolution in finance that I have watched over the whole course of it, because I have organized conferences on behavioral finance starting in 1991, working with Richard Thaler at University of Chicago.


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[Assistant] And, uh, we just, uh, we've been doing that for 25 years, but we just, uh, bequeathed that there are regular seminars of professors, uh, to Nick Barberis here at the Yale School of Management.


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[Assistant] And then we talk about debt, the stock market, the real estate market, regulation. Oh, by the way, regulation is an interest of mine too. Uh, more so than most people who teach finance. Because I think that the markets need to be regulated.


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[Assistant] Human beings have a tendency to be manipulative and tricky and finance is used to trick people. Uh, that's why we need regulators. So you shouldn't assume that I want to send you off to Wall Street.


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[Assistant] Uh, I think that you might go to be a member of the, like the Securities and Exchange Commission or something else as a job, and be proud of it. Okay? It's important.


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[Assistant] Then banking, futures, futures market, that has a special meaning in finance.


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[Assistant] Uh, monetary policy, endowment management, investment banking, option, money managers, exchanges, public finance, non-profits, and finally, that last lecture will be on the purpose of all this. Uh, so that's this course.


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[Assistant] So, uh, I wanted also to, uh, just reflect on the relative, I said this course looks more vocational in a way, but I don't consider this vocational school. This is, I like to say useful.


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[Assistant] One thought, perspective I wanted to give you was, how important is finance anyway? Unless you go into academia, you will get a job somewhere in the real world. So where are the jobs?


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[Assistant] Well, I looked up on the Bureau of Labor Statistics with the publication of the U.S. government on their website. They have data on just how many people are in different professions in the United States.


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[Assistant] And they also have a forecast. So what I'm showing, the latest data is for the year 2014, uh, and it has the number of people in thousands.


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[Assistant] So, uh, you note that at the top I've got finance, these are specific finance professions, not all finance professions. Financial analysts, uh, financial managers, personal financial advisors. They all have hundreds of thousands of people.


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[Assistant] But I wanted you to note, what about the other majors that you have here? I'm not diminishing them, but, uh, economics, uh, economists, uh, not so many.


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[Assistant] But you might also be interested in astronomy. I actually love astronomy. When I was a kid I thought I'd be an astronomer. But I had to reach reality. There's lots of exciting fields where there are almost no jobs. So there's, how many astronomers are there?


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[Assistant] Uh, sociologists, political scientists, or mathematicians. This is not to diminish your majoring in those fields, but you just don't expect to get a job in those fields. Uh, I also put down at the bottom, massage therapist, okay.


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[Assistant] I didn't know that was a profession, but there's, uh, projected to be about 200,000 massage therapists in the United States, uh, in 2024. So we don't have a massage therapy, uh, uh, major here, but, uh, that's a sign of, uh, of, uh,


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[Assistant] How the market makes things important. Now Rana Farrohar might be right about this. There's something wrong with having so many finance people. Maybe we need more massage therapists than finance people.


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[Assistant] But there's a sense of reality that I, I think that part of the reason that there's so many of them is that they deal with important issues that can't be quickly, uh,


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[Assistant] It can't be more easily solved. We need, we need all these people.


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[Assistant] That's why I take some pride in this course in being connected to the real world. There are real job opportunities in finance. And they're also, I think, in the new industrial revolution period, they will still be, I think this is one of the fields that is not going to be


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[Assistant] The problem with finance is that there is a high inequality in these, in these, uh,


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[Assistant] In this field, some people make a lot of money. On the other hand, you have to give it away. This is another thing about this course. If you make a lot of money in finance, it's a game, you enjoyed it, now give most of it away. That's going to be a theme.


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[Assistant] But, it was the green team that came in last. Tonight, Darren Purchase!


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[Assistant] So delicious. Absolutely delicious. But for one, It's not a disaster, but it's not there. That's a real shame. It will be their final curtain. You are going home.


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[Assistant] Bring us a dish based around chicken wings. With Sashi already wearing one immunity pill.


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[Assistant] It's going to be sunny to use your sunglasses or it's going to be cold to have an extra card. It can give you some time good information and some time not. Let me tell you.


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[Assistant] My best app is my grandmother.


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[Assistant] But she can predict the next 12 months it's going to be a good rain season. Or not.


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[Assistant] She can tell you just by observing her environment, by observing the wind direction, the cloud position, the bears' migration, the size of fruits, the plant flowers.


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[Assistant] That's how she know better the weather and the ecosystem where she lives on. I'm coming from a pastoralist community, who are cattle herders. We are nomadic. We move from one place to another one, to found water and pasture.


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[Assistant] Help us to live in harmony with our ecosystem. We understand each other. For us, the nature is our supermarket, where we can collect our food.


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[Assistant] And they are farmers. They do not depend from the end of the month's salary.


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[Assistant] The shrinking resources, you have many communities that fighting to get access.


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[Assistant] It's impacting our environment, but changing our social life. Because the role of man and woman in this region is different.


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[Assistant] Man supposed to feed his family, take care of his community. And if he cannot do that, his dignity is under threat.


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[Assistant] So climate change take our minds far away from us. That is the migration.


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[Assistant] Of course it's sad for the hosting country, who are developed countries, who have to adapt to host the migrant coming. But how about those who are left behind? The women and the children?


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[Assistant] Who have to play the role of man, the role of woman, who have to take care of the security, of the food, of the health, of the entire family, children and all peoples. So those women, for me, they are my hero.


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[Assistant] Because they are innovators. They are solution makers.


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[Assistant] They are changing the little of the resources into the big-for-them community. So those are my people.


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[Assistant] Our knowledge are not only for our communities, it's to share with each and others who are living with us.


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[Assistant] And then they are like, oh, there is no cloud. How do you know it's going to rain? I'm like, yeah, it's going to rain. We pack our stuff. Suddenly heavy rain start coming.


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[Assistant] We do have knowledge, but we do not combine ecological knowledge and where the knowledge are together.


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[Assistant] So that's how I started working with meteorological scientists, peoples and my communities to give the better information to get peoples adapt to the climate change.


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[Assistant] I think if we put together all the knowledge system that we have, science, technology, traditional knowledge,


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[Assistant] I use a tool that I really love a lot. It's called a 3D participatory mapping.


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[Assistant] Participatory because it can bring woman, man, youth, elder, all the intergenerational peoples.


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[Assistant] Then it's use a science-based knowledge and community come together, they build this map, they figure out all the knowledge that we have about where is our sacred forest, where is our water point, where is our corridor, where is the place that we move during each season.


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[Assistant] We say, well, may you call the woman come and have a look. They say, yes, sure, because they already done the first one. When the woman come and then they look at the map, they're like, no.


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[Assistant] Combine those three knowledges and give the better resilience to the peoples who are getting the impact of the climate change.


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[Assistant] And we need the decision maker to change. Scientists tell them. And we tell them. And we do have those knowledge. We have 10 years to change it.


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[Assistant] 10 years is nothing. So we need to act all together and we need to act right now. Thank you.


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[Assistant] It was a dark, rainy night, said Rat. Our friends were sitting by the fire. Toad listened closely. A pack of wild wooders hid outside. The weasels came in the front. The ferrets came in the back. It was a surprise attack, said Rat.


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[Assistant] What did Mole and Badger do? asked Toad. Nothing, said Rat.


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[Assistant] Your house is a mess, said Rat. The weasels eat all your food. The ferrets drink all your drinks.


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[Assistant] They sing awful songs. Listen!


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[Assistant] Hopefully I'm trying to go for it. Interesting. I want to make history, so whatever they throw at me, I'm ready.


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[Assistant] 45 minutes sounds like a lot of time, but I have marinated them, fried chicken wings, need to do sauce on the side to go with it. It's going to be a tight 45 minutes.


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[Assistant] It's uh, my homestyle way of doing it. I do this at home usually. And with the sambal sauce on the side. I only made one change to the recipe. The sambal sauce should not be too spicy and overpowering.


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[Assistant] The sambal should taste spicy, at the same time sweet. It gotta be perfect.


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[Assistant] I only have 20 minutes left. I need to start cooking my chicken wings. One chicken wing for tester.


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[Assistant] So everything is coming in place. I hope the judges love it.


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[Assistant] My chicken is done. Sambal is ready. My pickled cucumber is side to go with the sambal.


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[Assistant] So, did I tell you about my New Year's resolution? I've decided to go on a diet.


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[Assistant] But this time, I'm going to stick to it. I really mean it. Trust me, Carol, I'm gonna be a new man in one year's time.


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[Assistant] So, did I tell you about my New Year's resolution? I've decided to go on a diet.


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[Assistant] Exactly. I'm going to cut out all that junk I eat. No more chips. No more soda. No more fried food.


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[Assistant] I'm gonna stick to it. I really mean it. Trust me, Carol, I'm going to be a new man in one year's time.


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[Assistant] This time, I'm going to stick to it. I really mean it. Trust me, Carol, I'm gonna be a new man in one year's time.


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[Assistant] Hello, Fairbrook Consulting, how may I help you?


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[Assistant] Oh. Actually, Tuesday's no good. Sorry about that.


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[Assistant] Hello? Fairbrook Consulting, how may I help you?


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[Assistant] No. Unfortunately, she's booked solid on Thursday. How does next Monday work for you?


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[Assistant] Oh. Actually, Tuesday's no good. Sorry about that.


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


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[Assistant] Actually, I've got something scheduled on Monday. Can she do Tuesday? Sure. Tuesday's perfect. May I ask where you're calling from?


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[Assistant] Sure, Merton Financial Advisors.


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[Assistant] Yeah, let's do this. I'm putting it out to the universe right now. This is Khan Week. I'm gonna win this pin and see how far I can go.


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[Assistant] I see the clashes and I'm assuming round one is going to be a taste test, which freaks me out because I've done one before.


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[Assistant] Didn't do too well at it. So hopefully this is a little bit different.


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[Assistant] Yeaah, we go strawberry picking every year around my birthday. It's my favourite, favourite thing to do.


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[Assistant] I'm competing against two guys that have already got pins. I'm not just doing this for myself at this point, I'm doing it for everyone else. Like, they can't get another pin because that would just totally change the game.


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[Assistant] I feel a little bit bad for Rhys, but I need to stay focused now. Rhys, you're up. Ah, fit. Coriander. You're right, of course you're right.


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[Assistant] It's ridiculous. It's another Asian ingredient that I know so well. It's belacan, it's shrimp paste. Belacan. You are correct.


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[Assistant] This is definitely Khan Week so far. Let's keep the momentum going.


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[Assistant] I've seen so many of the other contestants try this on and they've looked amazing in it.


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[Assistant] This is Jin's backyard. This is his playground.


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[Assistant] I'm picking more strategically today rather than what I'm more comfortable with.


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[Assistant] I'm choosing an ingredient that I think Jin might not be comfortable with.


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[Assistant] That is a surprising decision. Yeah, I'll absolutely convince 100% you're gonna go with peanut butter. I think that it would throw gin off. I don't think that many chefs are familiar with using Vegemite.


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[Assistant] I was petrified before about the closhers, but now that I know my ingredient, I'm focused. All I'm doing right now is thinking about what I'm gonna make to win this immunity pin. Cut! Are you ready?


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[Assistant] An idea, I make this chicken broth that's really lovely. It's got, uhm, chicken dumplings and some smoked chicken in it.


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[Assistant] So, for my dish today, I'm gonna take out the fish sauce in my broth and sub in vegemite instead. And hopefully that brings out similar kind of flavours that I need for the dish.


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[Assistant] Today I'm doing a vegemite and chicken broth served with chicken, mousse dumplings and smoked chicken. The broth really needs time to develop in flavour, so I need to get the chicken bones and the chicken wings on there, browning away first.


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[Assistant] Um, so I'm gonna get some colour out of them. Get them really, really brown, just so you get the flavour of the chicken through it. And then I'm gonna deglaze them. Okay. And then start working on layering flavours through it. Yeah, so how do you know when to add the vegemite? So I'll do the aromats first, actually.


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[Assistant] And then go in with the Vegemite at the end, try and balance it out. Interesting.


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[Assistant] Smoking chicken I think really brings another total different aspect to the dish. I've chosen to do it with some rice, um, aromats like cinnamon, star anise and orange zest. I think that's really gonna tie it all together.


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[Assistant] I've chosen to cook with Vegemite and I'm doing a chicken and Vegemite dish. I'm cooking chicken mousse dumplings, smoked chicken, a chicken and Vegemite broth, and mushrooms three ways. How we going?


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[Assistant] There's back notes of Asian flavours in my dish, but none of them are too overpowering because I really still need that Vegemite shine because there's a Vegemite challenge. I just need to make sure that everything is really well balanced.


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[Assistant] I deglazed the broth, now I have to let it simmer. I need that water to really reduce down. And add some Vegemite in.


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[Assistant] I've got the mousse in the fridge. It's ready to go. I need to get on with my dough now.


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[Assistant] There's 30 minutes to go. I've got about a million things going at once.


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[Assistant] I've got a broth, I've got a smoked chicken, I've got dumplings, I've got mousse, I've got mushrooms, three ways.


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[Assistant] It's round two of immunity. I'm cooking against Jin Choi from Harley's Veranda restaurant. You enjoying yourself?


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[Assistant] I actually am. This is crazy, but it's so much fun. Vegemite is the main component to today's dish. So I'm cooking chicken and Vegemite.


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[Assistant] I've got about a million things going at once and I'm just second guessing myself, but hopefully the veggie might make sense in my dish and it really shows.


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[Assistant] I need to make sure that the Vegemite isn't too strong so it's overpowering but not light enough that it's just not there. Now you'll be able to really whisk in the Vegemite. I need to make sure it's just on point so it shines through.


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[Assistant] I've left my dumpling dough out too long and it's starting to dry up so I need to make sure that I form those dumplings really fast now because if it gets too dry they'll just break open. Let's split that one.


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[Assistant] I've had such a strong idea from the beginning, but now it's down to crunch time. Got a million things happening. I just need to get them done.


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[Assistant] It's imperative that these dumplings work, and some are splitting shans on my back. Come on, come on, come on. And I'm so stressed, but I just need to get it done.


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[Assistant] A lot of flavours going on right now. There's a new marminess from the Vegemite. There's the chicken happening. There's a saltiness that comes from the broth as well.


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[Assistant] There's not much time left at all. I have to start plating. I've got the peas on. The dumplings are out. The chicken's done. Yeah, that's it. That's it. Yeah, just nice pieces.


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[Assistant] But I have no idea how Jin's dish tastes. It looks great, so it's all up to the judges now.


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[Assistant] I have seen it around the beaches that I usually take my kids for a walk. I have no idea what it's called


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[Assistant] I will never forget the pig face. It will haunt me for the rest of my life. Pig face!


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[Assistant] For Kanto to get his dumplings right, he needs to have a beautiful silky dough.


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[Assistant] Khan has got so many elements on the go, and all of them have to be perfect.


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[Assistant] You, left. You, in there. Let's go, quickly. You, in there. You, in there. You two, in there. In. In. Stop. Didn't say where. In.


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[Assistant] One, two, three, four, five, six, seven, eight, nine. You two, in. Let's go. Right.


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[Assistant] Listen up. You guys are the blue team. You guys are the red team.


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[Assistant] Today, all of you are making a three course dinner. Blue team, you're cooking for 50 diners. Red team, you're cooking for 50 diners. Both teams will make an amazing entree, followed by a stunning main course, and then you round it off with an incredible dessert. Understood? Yes, sir.


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[Assistant] Take a look around and just understand how big these teams are.


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[Assistant] Blue team. Who's the leader in that team?


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[Assistant] The team that cooks the best is clearly safe on to the next round of competition.


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[Assistant] Sadly, the losing team, you know, goes straight into elimination.


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[Assistant] That clock is ticking. We are into our two hours prep.


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[Assistant] Okay, we are filling this room with the most amazing diners. And guess who's running the hot plate?


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[Assistant] Right. All of you. Get excited. I wanna see you at your best. I wanna see an incredible menu. Three incredible dishes. Understood? Understood.


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[Assistant] Red team, blue team. Twelve minutes gone. One hour, 48 minutes prep. Left.


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[Assistant] Halfway guys. Sixty minutes of prep remaining.


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[Assistant] I want it plated at the front, once you've got it, yes? To the front, please. On to the hot plate, let's go.


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[Assistant] Get your team together and start being a bit more thoughtful, because right now, hey, I'm thinking of shoving this place down. Now.


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[Assistant] Hey, Blue Team? Yes, Chef? 15 minutes from now, I want to see one dessert. Got it. We don't want to be in time, Kristen.


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[Assistant] I was hoping when the panna cotta are done, two of you can jump onto the entrees. Yes. I was hoping. How long for the panna cotta? Nearly done chef. Brendan, where's the main course please? Come on.


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[Assistant] It's like a rubber glove. And we need crispiness on the salmon. We need some flavour.


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[Assistant] You can cook better than that, that salmon was terrible. Pan, nonstick, oil, school of salmon, three minutes. Dessert, where are we?


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[Assistant] Brandon, red team stop. Why are you cooking the dumplings? Look out there!


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[Assistant] Reese, dessert please. Yep. How long, Reese, please? 30 seconds. Thank you.


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[Assistant] No, that's all, it's two things. Let's go, come on. Three minutes until I guess sit down.


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[Assistant] Red team, blue team, look at me, all of you. Our guests are arriving.


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[Assistant] Red team, blue team. Look at me. Our guests are sitting down. Oh jeez. Service has started.


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[Assistant] We tighten up, we really focus on the pork now. Yes, Gordon. Is he starting to cut that pork? He should be. Okay, yep. He needs to start cutting the pork.


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[Assistant] Reece, we're doing four at a time. We need to be stunning, okay?


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[Assistant] Let's go, let's go, let's go. Put the tray down and work with both hands please.


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[Assistant] I got twelve more salmon I need. I'll go.


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[Assistant] Done, last one, guys. Let's go. Good. Well done. Thank you, blue team.


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[Assistant] Yeah, not, not too much time to talk to you in the past. We're obviously busy with the teams.


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[Assistant] Like any frantic manic service, it's crazy back there but gliding like a swan across the dining room.


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[Assistant] Tonight there are areas where you made it more difficult for yourselves than necessary. A team needs to stick together.


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[Assistant] Every member of every team should be able to turn around and look right through the kitchen and understand what everybody's doing. Do that and you finish strong. One, two, three individuals come off pieced.


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[Assistant] The wheels fall off and it becomes harder for everybody else.


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[Assistant] Blue team, don't breathe a sigh of relief just yet. I won't be here next time you come back, but it's not the end of the Gordon Ramsay week. I have a very big surprise for all nine of you.


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[Assistant] In our team we've got quite a strong Asian influence, so I'm thinking let's play to our strengths and go for that kind of theme. Alright, let's go back to Entrez. I know heaps of us are great at dumplings.


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[Assistant] Let's go guys. If there's any problems just come to me and we'll sort it out, okay?


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[Assistant] Let's go Red, push, okay guys? Jenny, let's go, let's go, come on. Do you think they're ready?


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[Assistant] 30 seconds Brendan, let's go. Jenny, down the back, down the back, come on. Lighting up here.


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[Assistant] Come on, let's go, push. As many as you can, just push, push, push. Come on, guys. Chloe, entree, let's go.


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[Assistant] We're running out of time, we set up a production line, we get all hands on deck, and we start plating these dumplings.


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[Assistant] For mains today we've got crispy pork belly with a Thai chilli jam, jasmine rice and a Thai salad. How young are we mains? Uhm, he wants 15 minutes to taste a plate.


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[Assistant] Gordon's chasing that tester for the main now and I mean we're not even close to ready. The pork's just cooked but the chilli jam's not even there.


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[Assistant] We're nearly there, we're nearly up to uhm, 180. Uhm, we just need to get onto the poaching so we can get them out to service.


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[Assistant] Alright, let's go guys. We're gonna plate here. Yep. Garnish up the front, just finish off, okay? Yep.


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[Assistant] It's scary, but at the same time, like the adrenaline of this service, it's so much fun right now. I'm just pushing the team.


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[Assistant] I don't want to let the team down today and be responsible for them going to elimination.


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[Assistant] Go please. We had a great start earlier. Entrees were flying out and we were doing so well.