[User] Please transcribe this text

[Assistant] The point of the entire argument is that, uh, you don't need new theory to understand deep networks. The existing theory works just fine. You just have to apply it in the right way and appreciate the fact that you're not fitting arbitrary data. You're fitting data with very specific patterns, very specific learnable patterns. Okay? You're not fitting a hash function.


[User] Please transcribe this text

[Assistant] Cool. Uh, so here is one take home message from this calculation. Uh, let us ask ourselves, there are many, many weights in the network. How many are really constrained?


[User] Please transcribe this text

[Assistant] So we can pluck out a quantity which is roughly speaking the elbow of this particular eigen spectrum, uh, that looks as follows. The number of eigenvalues of the Hessian that are larger than epsilon is not important. It is the scale of the prior.


[User] Please transcribe this text

[Assistant] Then because of the shape of the eigen spectrum, you are not using all the degrees of freedom available to you. You do not have enough information to constrain all those degrees of freedom. Typically in practice, only about half a percent, not 50%, half a percent of the number of weights are actually constrained.


[User] Please transcribe this text

[Assistant] Okay, so when someone says I fit a network with 1 million weights, they're really fitting a model with about 5000 degrees of freedom and it shouldn't be a surprise at that point that we can get good test error.


[User] Please transcribe this text

[Assistant] So here is a cartoon of this entire business. If you think of the manifold of functions that are expressed or that are expressed on this data by the network,


[User] Please transcribe this text

[Assistant] Uh, the learning typically happens in the stiff part of the eigen-spectrum. If you take the Fisher initialization, the weights predominantly move in the stiff subspace.


[User] Please transcribe this text

[Assistant] They don't move in the sloppy subspace for two reasons. One is because these are optimization problems that are low dimensional, yes, but they're incredibly badly conditioned. So even if you take a quadratic with an aspect ratio of 10 raised to 6, you're not going to be able to minimize that very easily.


[User] Please transcribe this text

[Assistant] But it doesn't matter because, uh, the sloppy digs of freedom do not affect your predictions much. You're already getting the 95% accuracy and the remaining five is, uh, is coming from the sloppy parts.


[User] Please transcribe this text

[Assistant] Okay, so you find learning corresponds to you initializing somewhere in the interior of such a manifold and then fitting the long sides of this. And we call such manifolds hyper ribbons. They are very long in some directions and then there are many, many, many directions where the ribbon is very thin. It's just like the ribbon that you use in everyday life.


[User] Please transcribe this text

[Assistant] So over the last year or so, we've been basically making this picture more and more rigorous, uh, and this is the subject of two papers. Uh, the first one will be presented at ICML, uh, in a couple of months, and the second one we just put out an archive, uh, last week or so.


[User] Please transcribe this text

[Assistant] Here is how I will explain that. So, I would like to understand the space of probability distributions that are expressed or parameterized by the network.


[User] Please transcribe this text

[Assistant] Uh, when it learns, okay? Uh, this is an infinite dimensional object. So p of y given x, y is an output, x is an input, w are the weights, is a function of x. I can plug in any x into this that I want, I get one number.


[User] Please transcribe this text

[Assistant] It's not very easy to understand such an object. One, because it's a big function and two, because the likelihood is a complicated function of the weights. That is really the grief of the entire business.


[User] Please transcribe this text

[Assistant] Uh, we do a pretty cheap trick, uh, to get around this. It's a little bit like, uh, someone told you to take a function analysis class, uh, you did not take it. So you take the function, you measure it at a fixed finite number of points, and then now you pretend that you have a vector and forget that you're dealing with a function. Okay?


[User] Please transcribe this text

[Assistant] In our case, the points at which we want to measure the likelihood are pretty naturally selected. These are simply the training samples.


[User] Please transcribe this text

[Assistant] So if you think of ImageNet, ImageNet has 1 million samples, so n is 1 million.


[User] Please transcribe this text

[Assistant] For each of these samples, you are predicting 1000 numbers, 1000 probabilities for each of the 1000 classes. So you have 1 million times 1000, which is 1 billion dimensional vector. That is a representation of the model that you have learned.


[User] Please transcribe this text

[Assistant] Doesn't matter what architecture you have, doesn't matter how you train this model, so long as two networks have this exact same vector,


[User] Please transcribe this text

[Assistant] Uh, in this space, let's say that you have a billion-dimensional space. It's not a vector space, but it's a product manifold of, uh, of spheres, uh, of thousand-dimensional spheres on which the probabilities lie and one million product of such spheres.


[User] Please transcribe this text

[Assistant] On this manifold, two points are kind of special. The first one is what we like to call the truth. Uh, it is the one hot probabilities of all the samples, which is the solution of the training set. This is what we want to fit at the end of the day.


[User] Please transcribe this text

[Assistant] Uh, at the beginning, people like to initialize their networks, uh, so that the network predicts one over thousand, one over thousand for every class, for every image, right? That is what we call ignorance.


[User] Please transcribe this text

[Assistant] So the name of the game when you train a network is, uh, you begin training at this point called ignorance. You end training at this point called truth.


[User] Please transcribe this text

[Assistant] And then you are now doomed to live in this billion dimensions and the question is how you get there.


[User] Please transcribe this text

[Assistant] Uh, we like to use what is called the Bhattacharya distance. The Bhattacharya distance, if you haven't seen it before, it is for the purposes of this calculation, you can just think of symmetrical divergence.


[User] Please transcribe this text

[Assistant] Uh, the, the reason to use this is as follows. So in these dimensions, anything that you use to measure distances between points goes to hell pretty quickly. It saturates. So if you take the Hellinger distance in these dimensions, it will always saturate. Uh, so you have to use things that are not metrics.


[User] Please transcribe this text

[Assistant] The Bata-Zehra distance or the symmetric KL divergence is not a metric. It's a distance. It's positive, but not symmetric. Uh, the KL is not symmetric, but, uh, it, it doesn't satisfy the triangle inequality.


[User] Please transcribe this text

[Assistant] Uh, but we have figured out ways to work around that. Uh, so here is what we are going to do. Uh, I'm going to train hundreds of thousands of models in this space and then project them down into lower dimension spaces to understand how the training process behaves.


[User] Please transcribe this text

[Assistant] Conceptually, it's a lot like doing PCA, principal component analysis. We use something called as multi-dimensional scaling, slightly more old-fashioned, uh, but, uh, this is, uh, cal- same calculations PCA essentially. PCA preserves Euclidean distances between points. MDS preserves, uh, your favorite distance. In this case, the Bhattacharya distance between points. Okay?


[User] Please transcribe this text

[Assistant] Now another thing that is pretty cool and technical about this is that typically MDS is very popular in the bioinformatics literature.


[User] Please transcribe this text

[Assistant] We all know that MDS eigenvalues need not always be positive. They can also be some negative eigenvalues. So you're embedding into Minkowski spaces with imaginary coordinates and bioinformatics people typically like to throw away such imaginary coordinates. We believe that there is meaning to them and so I'll show you what exactly is this meaning.


[User] Please transcribe this text

[Assistant] But here is the setup. We take many, many networks, train them, calculate all these big vectors, project them down into lower dimensional spaces and they will see what they do. Okay. So here is a picture. Every point is one neural network.


[User] Please transcribe this text

[Assistant] Uh, there is about, there is six different architectures, fully connected networks, uh, CNNs, uh, Transformers, uh, Small Res Nets and Large Res Nets. Uh, they all begin training at essentially the same point up to statistical fluctuations called ignorance. P0 is that point.


[User] Please transcribe this text

[Assistant] Uh, and what I've done is I took about, uh, these six architectures, trained with, uh, SGD, uh, SGD with Nestor Acceleration, with Adam, uh, different batch sizes, different learning rates, with rate decay, without rate decay, with augmentation, without augmentation. About 2300 different configurations of networks.


[User] Please transcribe this text

[Assistant] And, uh, when you plot the first three dimensions of this embedding, what you notice is that this is CIFAR 10, so the space in which these points live, these probability distributions live, is 50,000 samples times 10 outputs. So half a million dimensions, okay.


[User] Please transcribe this text

[Assistant] In this half a million dimensions, the top three dimensions capture about 76% of the variance.


[User] Please transcribe this text

[Assistant] This is telling you that in spite of the huge diversity in what these networks are, they live in what is basically a three-four dimensional manifold. I can write you down a description of each of these points in three-four coordinates and it would be a faithful description. I wouldn't be cheating.


[User] Please transcribe this text

[Assistant] In the sense that pairwise distances would be preserved up to this much. Okay?


[User] Please transcribe this text

[Assistant] So a large model and a small model, they don't learn different things. They not only learn the same thing at the end when they fit the data, but they also learn it in the same way.


[User] Please transcribe this text

[Assistant] We can calculate, uh, distances between trajectories, uh, uh, in the original space. And we can show that the two networks, large ResNet and small ResNet, they travel along the same manifold. The larger one is a bit faster.


[User] Please transcribe this text

[Assistant] So when people say that large networks work well, all that they are really saying is that the small network, I did not train it well enough. If I had trained it, perhaps it would work as well. Distillation, pruning are all evidence of such a statement, right?


[User] Please transcribe this text

[Assistant] And that would be in some sense the shortest path to take between the ignorance and truth. These networks don't take that path, they all take a slightly different path and somehow the same one. Okay.


[User] Please transcribe this text

[Assistant] Uh, typically when you train networks with Adam, you will see huge swings in the probabilities that are predicted for each of these images. But the cool thing here is that these points, uh, if you were just to train them further, you would reach zero error. So all the networks in this entire experiment have zero training error, barring like a couple of dozen.


[User] Please transcribe this text

[Assistant] You just train them further, they will reach the correct solution. Okay, this is just the diffuseness of the manifold.


[User] Please transcribe this text

[Assistant] So the training process explores a very low dimensional manifold in spite of this huge dimensionality, yes.


[User] Please transcribe this text

[Assistant] Cool. So, uh, uh, now let us project the same manifold in the top two dimensions. So this is PC1 and PC2. And what I want you to think about is, uh, is that the second eigenvalue, uh, in this particular imp, uh, uh, uh, experiment of multi-dimensional scaling is negative.


[User] Please transcribe this text

[Assistant] So this is a Minkowski space where this is a complex coordinate and this is a real valued coordinate. So distances in this space, they go as delta x square minus delta y square because y is imaginary. Okay.


[User] Please transcribe this text

[Assistant] P star is the point where everyone is headed. You can imagine that there is a light cone that comes out of P star.


[User] Please transcribe this text

[Assistant] We know that the error 0 is reached long before the loss becomes small. And so all these different networks, they try to fall on the same light cone.


[User] Please transcribe this text

[Assistant] 500,000 dimensions and these probabilities are different in tiny, tiny ways. So you take one image and one network predicts 0.7 and 0.1, the other one predicts 0.65 and 0.12. Uh, the visualization method is showing you the difference. I'm plucking out signal from these large spaces somehow.


[User] Please transcribe this text

[Assistant] Okay, this is how the test manifold looks like. Uh, the manifold has basically the same shape, but then there is larger differences in trajectories of different architectures.


[User] Please transcribe this text

[Assistant] In this case, you can actually see the truth. In the previous plot, you couldn't see the truth on the same 3D plot. Here, this is the truth. And if you think a little bit about what is happening, all these networks, they should be close to the test truth, right?


[User] Please transcribe this text

[Assistant] And then corn mixtures or large resonates have smaller errors, so it will look a little closer to the testosterone. So you can think of the truth as the bullseye that you're trying to hit. And bad models are far away from the bullseyes, good models are close to the bullseye, and you would imagine that there's a big circle in which the bad models are spread around.


[User] Please transcribe this text

[Assistant] Uh, because they cannot get any closer. Uh, that's not really the case. The fully connected networks...


[User] Please transcribe this text

[Assistant] This is a very clear evidence of this. The manifold here is a tiny bit higher dimensional. In this case, it is about 63% in the top three dimensions, but the structure is basically the same. We know that these branches come from, let's say, augmentation versus without augmentation, but there is very little differences. Okay.


[User] Please transcribe this text

[Assistant] Uh, the same thing happens on ImageNet, uh, we did not train as many models in this case, only three architectures, uh, but the manifold is again low dimensional, uh, and basically all conclusions that you, we talked about are consistent.


[User] Please transcribe this text

[Assistant] Okay, so in this space, so the way we usually work, we've been doing this for a good year, year and a half now, uh, we draw these pictures, uh, we form hypotheses.


[User] Please transcribe this text

[Assistant] Uh, and then do all the analysis in the original high dimensional space. So that we don't get fooled by the pictures because interpreting Minkowski spaces is very hard. We have spent lots of months trying to do it. Uh, yeah.


[User] Please transcribe this text

[Assistant] Uh, so we have to define some unique notion of time for all these networks. And the way we do that is, uh, we project all the projectors on the geodesic and then imagine a constant velocity particle that travels along the geodesic and assign the time of the constant velocity particle to each of the networks. So ResNet might make much faster progress towards the truth.


[User] Please transcribe this text

[Assistant] After 50 epochs, then a small fully connected network, and then the ResNet will have a larger value of progress after 50 epochs. Okay? And so we can draw these dendrograms. I don't expect you to read this, but what I want to show you is these are dendrograms of trajectories of different configurations.


[User] Please transcribe this text

[Assistant] I just focused on this one. These are all fully connected networks trained with different optimization algorithms. And you notice that when I clustered my dendrogram like this, all the architectures lit up together.


[User] Please transcribe this text

[Assistant] So architectures is the predominant thing that distinguishes trajectories in these spaces. Within each cloud of architectures, the optimization algorithms cluster themselves into separate clusters.


[User] Please transcribe this text

[Assistant] Uh, but basically different architectures is what determines the differences in the learned models. Training hyperparameters of training or hyperparameters regularization basically do not matter. Yeah.


[User] Please transcribe this text

[Assistant] The distance from the geodesic doesn't contribute to the time. It, uh, but the, uh, if the geodesic is, imagine the geodesic is a straight line, it is a straight line and then the trajectories can go in different directions. So if you are kind of moving orthogonal to the geodesic, then you will not make progress. That is, that is, yeaah.


[User] Please transcribe this text

[Assistant] And you see that the geodesic is far away from everyone. But the cool thing again is that all the architectures are close by. Okay.


[User] Please transcribe this text

[Assistant] Cool. Uh, here is a slightly different experiment, uh, of the same kind. Uh, the red line here are models trained on the full ImageNet. Okay. Uh, and the green line, for instance, is a model trained only on all the categories in the vertebrate phylum. This is a subset of ImageNet.


[User] Please transcribe this text

[Assistant] Trajectories of models trained on different subsets of image net still lie in a three, four dimensional space. So in the top three dimensions, the explained stress in this case is about 88%.


[User] Please transcribe this text

[Assistant] So this tells you that not only is the manifold of networks trained on the same task, low dimensional, the different tasks themselves,


[User] Please transcribe this text

[Assistant] Uh, the end points of these trajectories are proxies or what the task is are themselves, the tasks themselves are low dimensional. The reason we are good at doing fine-tuning or transfer learning or metatask learning or meta-learning is because we are solving this three, four-dimensional, uh, problem secretly. Okay.


[User] Please transcribe this text

[Assistant] Uh, we can also do this very cute trick where this is the ontology of the classes in WordNet. These are the categories of ImageNet. Uh, you can take the distances between trajectories obtained from this analysis and then reconstruct the ontology.


[User] Please transcribe this text

[Assistant] The visual classification task has a priori nothing to do with the ontology that was created from language, uh, and but they seem to be consistent with each other.


[User] Please transcribe this text

[Assistant] You can also do, in this paper, in the ICML paper, we showed a lot of things related to this. For instance, meta-learning or episodic meta-learning and supervised learning learn the same thing. Episodic meta-learning is just horrendously inefficient in how it gets to the truth. So we should, there is no need to do meta-learning.


[User] Please transcribe this text

[Assistant] Uh, we also showed that self-supervised learning and supervised learning learn the same thing. Self-supervised learning doesn't go all the way to the truth. It stops midway, uh, because we don't really know where the truth is. We don't know the true labels, right? And you can do all kinds of analysis by this. Uh, the, uh, the, uh, the way I would, correct, summarize these pictures is that


[User] Please transcribe this text

[Assistant] The manifold of probability distributions is looking like a hyperribbon, but the different tasks that we are interested in solving, they also project to the same parts of a hyperribbon.


[User] Please transcribe this text

[Assistant] And this is why you do not need to change your model very much when you go from one task to the other task. All you need to do is modify the model in the sloppy dimensions. The sloppy dimensions are the one that are actually helping you transfer the model. And this you can make precise pretty easily. Okay.


[User] Please transcribe this text

[Assistant] Uh, I won't worry about this result, uh, I can tell you later, but let me conclude, uh, a bit. So uhm,


[User] Please transcribe this text

[Assistant] As I said, the success of deep learning is telling us new things about data.


[User] Please transcribe this text

[Assistant] Uhm, the second one is a tiny bit more philosophical, so it is very surprising why there is so much structure in the data.


[User] Please transcribe this text

[Assistant] Uh, and if you think a little bit like a physicist, uh, there is matter, there is molecules in the inside the table, they give the table certain properties like stress, strain, and why these properties arise is definitely a question of physics.


[User] Please transcribe this text

[Assistant] What function we attribute to objects, the fact that images have objects, uh, rooms have chairs and chairs have some function is of our doing. So the semantics that we attribute to data is really our choice. We don't go around counting the leaves on a tree.


[User] Please transcribe this text

[Assistant] We don't go around giving labels to cats that depend on the number of hair they have.


[User] Please transcribe this text

[Assistant] Uh, so we created these learning problems. They are easy because you want to identify this bunch of molecules in the next image as being the same cat. And it shouldn't be so surprising that we can learn the same structure in an artificial network. The problem is easy to begin with. Okay.


[User] Please transcribe this text

[Assistant] So in a very vague sense, I would say that typical problems are learnable, and what is not learnable, you don't do.


[User] Please transcribe this text

[Assistant] So that's just right off the bat. The second part, which is this embedding gives us the low-dimensional structure. Would some other embedding not give it? Yes, you can create embeddings that wouldn't give you this low-dimensional structure, but it is a little bit of a question of,


[User] Please transcribe this text

[Assistant] Uh, so, uh, we are not, uh, married to but at a certain distance. We are not married to this specific way of doing things. Uh, but it is, uh, it is true that there is this structure.


[User] Please transcribe this text

[Assistant] Abraham Lincoln lay dying in a hall bedroom of a cheap lodging house directly across the street from Ford's Theatre where Booth had shot him. As Lincoln lay dying, people said,


[User] Please transcribe this text

[Assistant] There lies the most perfect ruler of men that the world has ever seen.


[User] Please transcribe this text

[Assistant] I studied the life of Abraham Lincoln for ten years and devoted all of three years to writing and rewriting a book entitled Lincoln the Unknown.


[User] Please transcribe this text

[Assistant] I believe I have made as detailed and exhaustive a study of Lincoln's personality and home life as it is possible for any human being to make.


[User] Please transcribe this text

[Assistant] I made a special study of Lincoln's method of dealing with men. Did he indulge in criticism? Oh yes.


[User] Please transcribe this text

[Assistant] He not only criticized, but he wrote letters and poems ridiculing people, and dropped these letters on the country roads where they were sure to be found.


[User] Please transcribe this text

[Assistant] Shields, sensitive and proud, boiled with indignation. He challenged Lincoln to fight a duel.


[User] Please transcribe this text

[Assistant] Lincoln didn't want to fight, but he couldn't get out of it and save his honor.


[User] Please transcribe this text

[Assistant] On the appointed day, he and Shields preferred to fight to the death.


[User] Please transcribe this text

[Assistant] But at the last minute, their seconds interrupted and stopped the duel.


[User] Please transcribe this text

[Assistant] This accident taught Lincoln an invaluable lesson in the art of dealing with people. Never again did he write an insulting letter. Never again did he ridicule anyone. And from that time on,


[User] Please transcribe this text

[Assistant] He almost never criticized anybody for anything.


[User] Please transcribe this text

[Assistant] Any fool can criticize, condemn, and complain. And most fools do.


[User] Please transcribe this text

[Assistant] A great man shows his greatness by the way he treats little man.


[User] Please transcribe this text

[Assistant] It's like him picking at it in the day versus how quickly can it heal in the night. And so it's become a tick for him where he's like scratching. It must be itchy.


[User] Please transcribe this text

[Assistant] You've done a lot. We saw, I mean, it's not a competition, but I'm pissed. Uh, I posted my tea guy video where I made the play and, um, and then you came through with a post of you.


[User] Please transcribe this text

[Assistant] I don't know, I don't know the answer, because I think, uh, in a politically correct world we can't, and it's got to a point where we can't discuss any of those things. But then I don't know how advantageous that is.


[User] Please transcribe this text

[Assistant] We're getting your food for you. You don't have to leave the house. We get to come and deliver it.


[User] Please transcribe this text

[Assistant] And the person that created this charity was so, so upset because everything on the list was pop tarts, was waffles, was high sugar. And it's like at a time when.


[User] Please transcribe this text

[Assistant] I mean, most of us are at some level trying to.


[User] Please transcribe this text

[Assistant] It being the way, you know, how I thought an insecurity might play out, you know, like insecure about your body is a different version to insecurity about an internal processing. And so that internal processing could be people pleasing, which is an insecurity. But for me, it's like,


[User] Please transcribe this text

[Assistant] Uh, doing stuff right or being perfect, whatever that version of whatever you think that is, I think is quite accurate. I don't know how to articulate it quite well, but it's the image. It's the, how people see you. It's the, you know, it's like a, what was that?


[User] Please transcribe this text

[Assistant] Emphasis on achieving, you know, like the path that we choose ends up being one of.


[User] Please transcribe this text

[Assistant] Yeah, well I said yellow and I just was taking a punt. I was like, yeah, yellow. And she's like, yeah, it's yellow. I've got it on my desk. So I've just asked her to send me a message with a photo of something. She said back, she said the one that she's got on her desk is like talking about


[User] Please transcribe this text

[Assistant] It's like, uh, you know, Jill and Bill are moving from Tamworth down to Victoria this week and they're like, it's, that's the news.


[User] Please transcribe this text

[Assistant] 160 a month of subscriptions solely for bits and pieces. How many are active as in you're consuming at a, let's do it percentage wise.


[User] Please transcribe this text

[Assistant] It's a cinema. It's like an ad, a hand drawn ad for a movie.


[User] Please transcribe this text

[Assistant] Wow, Legates, American Mighty Dolar Knight tonight. Wattlepaths Palace, St Kilda.


[User] Please transcribe this text

[Assistant] Perfect flo- like this is just ads. Wow, it's all hand drawn. There's no printing of photos on here. That is cool.


[User] Please transcribe this text

[Assistant] Do you think in the future people are going to be more prime to be paying at the subscription level for everything? So for all, all of their favorite creators?


[User] Please transcribe this text

[Assistant] Black logo, which is unpaid and red logo, which gets full feed is really interesting. All these sort of new models that.


[User] Please transcribe this text

[Assistant] Go online and put down Hillary Clinton illness. Take a look at the videos for yourself.


[User] Please transcribe this text

[Assistant] Well hey and welcome back to Heimler's History, and furthermore, welcome to the first video covering Unit 5 of the AP U.S. History curriculum, which is squarely nestled in the time period 1844 to 1877. And baby, in this video we're about to manifest some destiny, so if you're ready to get them brain cows milked,


[User] Please transcribe this text

[Assistant] Let's get to it. So, westward expansion. Now, in the end of the 18th century, the first half of the 19th century, there was hardly a notion that more stirred the guts of Americans than westward expansion. At first it was expansion west of the Atlantic coast, then it was expansion into the Ohio River Valley, then came the Louisiana Purchase, and Americans expanded into that like mad.


[User] Please transcribe this text

[Assistant] If you weren't expanding west, were you really an American? Westward expansion was just kind of our thing. But in July of 1845, a newspaper editor by the name of John O. Sullivan gave this most ancient of American impulses a name


[User] Please transcribe this text

[Assistant] Manifest Destiny. So in defining Manifest Destiny, O'Sullivan gives us two pieces of information. Number one, what Manifest Destiny is, namely to possess the whole continent from sea to shining sea. And the second piece of information he gives us is to tell Americans who gave them that


[User] Please transcribe this text

[Assistant] So the idea of Manifest Destiny is the notion that Americans have a God-given right to have a nation that extends from the Atlantic Ocean to the Pacific Ocean, and later that impulse would include islands in the Pacific and the Caribbean.


[User] Please transcribe this text

[Assistant] Westward expansion also made sense to people looking for new economic opportunities.


[User] Please transcribe this text

[Assistant] When Congress passed the Preemption Acts during the 1830s and 1840s, it made vast tracts of land available for cheap to anyone who wanted to buy it and set up a homestead and get to farming it. And because it did require some boom boom to actually make a trip out west, this migration was largely made by the middle class and not the poor. The third reason people moved west was for the purpose of religious refuge. Now if you remember back to the last unit, we talked about the Mormons who fled the Midwest states because of persecution, largely due to their practice of polygamy and settled in the Utah Territory.


[User] Please transcribe this text

[Assistant] Okay, so those are the main reasons Americans pursued their Manifest Destiny and moved west. But the idea of Manifest Destiny also made its way into the Halls of Power to, case in point, the election of James K. Polk. That happened in 1844, and Polk was a big believer in Manifest Destiny, and as such, he had his eye on a couple of territories that he was frothing at the mouth to add to the Union, namely Texas and Oregon, and let's look at both. Regarding Texas, Americans have been settling that territory since the 1820s, but at that time, Texas still belonged


[User] Please transcribe this text

[Assistant] By 1830, there were three times as many Americans than Mexicans living in this territory, and all those Americans were in general Southern Protestant and slave-owning, or at least sympathetic to the cause of slavery. Now this will be important to keep in mind because in 1829, the Mexican government made two requirements of the immigrants living within their borders. First, it was decreed that they must convert to Roman Catholicism, and second, they outlawed slavery. And these two requirements were, to put it mildly, intolerable to the Americans who had settled there.


[User] Please transcribe this text

[Assistant] Well, at this point, Texas claimed its independence, but Mexico didn't recognize that independence, and so when Texas applied to the United States for statehood,


[User] Please transcribe this text

[Assistant] That complicated things a little bit. The first two presidents who could have done it, Jackson and Van Buren, both said no to annexation because of the very real possibility that doing so would cause a war with Mexico. John Tyler worked to admit Texas, but ultimately annexation was denied by the Senate. So let's leave Texas lingering in independence for a moment, but don't worry, we'll get back to it. We also have to talk about the Oregon Territory. So at this point in history, both the British and the Americans laid competing claims to this territory. The British claimed it was theirs because they had established a profitable fur trade there and settled


[User] Please transcribe this text

[Assistant] We want it. Add to that, American missionaries and farmers have been moving to the territory and settling there in far greater numbers than the British. And so how do you solve this problem? And that brings us back to the election of James K. Polk in 1844. Now as a big believer in manifest destiny, he wanted America to annex both Oregon and Texas. Should we throw California in there too?


[User] Please transcribe this text

[Assistant] Let's throw California in there too. After all, it is our destiny.


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[Assistant] Now, since Polk had run on this annexation platform, he interpreted his election to be a mandate from the people to bring those territories into the Union. So his predecessor John Tyler went ahead and used the waning months of his presidency to push through the annexation of Texas, and Polk's people went ahead and made an agreement with the British concerning Oregon, and after the Senate had ratified the treaty,


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[Assistant] The Oregon Territory was divided at the 49th parallel. Now the annexation of Texas is going to be no bueno with the Mexican government, and that is going to lead the United States into war. But alas, that will be the topic of the next video. Well alright, that's what you need to know about Unit 5, Topic 2 of the AP U.S. History Curriculum. If you need help getting an A in your class and a 5 on your exam in May, then click right here and grab a review packet. Also, if you believe it is the manifest destiny of Heimler's history to spread over the whole of YouTube, then subscribe and we shall claim our destiny together, Heimler


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[Assistant] They're all very friendly with each other, I replied cautiously. The gypsy seemed to know a lot about Thornfield.


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[Assistant] I'd like to stay here looking at you forever but I must stop acting now. Was I dreaming? What was happening?


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[Assistant] The old woman's voice had changed and become as familiar to me as my own. Well Jane, you know me, asked the familiar voice. And struggling with the old clothes, Mr. Rochester stepped out of his disguise.


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[Assistant] It's great to add, you just moved to Los Angeles, right? Yes. From Paris, which has got to be, is that a little bit of a shock to move to LA from Paris?


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[Assistant] Why do you think that is? Is it just a cultural thing or is there some kind of sadness? Is it considered rude to be friendly to others in Paris? Uhm, I don't know. Based on my experiences, yes, it does seem like it is. That is the case.


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[Assistant] How long did it take you to learn the rules of living in France?


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[Assistant] Because I have a solution for fans who are looking for something beyond the Marvel and DC universes. And I hope some movie executives are watching this and taking notes. Because ladies and gentlemen, I present to you next year's Summer Blockbuster, Johnny Strong.


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[Assistant] The whole Johnny Strong series is chock full of adventures that are begging to be adapted to the silver screen, and where better to start than with issue one, which is called Night Moves.


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[Assistant] The bad news is that this is some big monster.


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[Assistant] People need to take this storm.


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[Assistant] With great seriousness.


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[Assistant] I would like her to come to Madeira to live with me and to inherit all my property when I die.


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[Assistant] Why did I never hear of this? I asked amazed.


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[Assistant] I hated you so much that I wrote back to him telling him you had died of typhus fever at Lowood.


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[Assistant] That was my revenge on you for causing me so much trouble. She cried angrily.


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[Assistant] Dear aunt, I said, don't think about that anymore.


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[Assistant] I was only a child. It's not surprising I was a nuisance.


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[Assistant] You are always so angry and violent. Such a wicked child. Not as wicked as you think. I would have loved you if you'd let me. Forget it all and kiss me now, aunt.


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[Assistant] But it was too late for her to break the habit of dislike, and she turned away from me. Poor woman. She died soon afterwards, keeping her hatred of me alive in her heart, and no one at Gateshead cried for her.


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[Assistant] Well if you also want to read about Napoli, you could also watch a video about it. We did a video a while ago, in October, about what makes Napoli so good. That's true. James Warren Castle gave me lots of tips. Yea. To make the video.


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[Assistant] They have a bit of a gap, but I think it's, they're not even halfway through. It's 19 games is halfway, isn't it? 19 is halfway. Yeah, so they're not there yet. No, they're not. I think they look very good. They have all the momentum and confidence just now. That's what you need. It's very, very important. They look really organised.


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[Assistant] Uhm, like they're strong tactically, but that's only a small part of it. I think it's more of the confidence they have and the belief and the keep winning games that should be tough. And I think they largely control this game.


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[Assistant] The reason that they could probably win it now is that City are having one of those seasons where it's like, they've achieved so much already, they're maybe just in a little bit of a transition, they've got Erling Haaland, a bit of a change of system, maybe there's just one of those, and they keep dropping points that they shouldn't, and they don't have the confidence, but that could all change, like,


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[Assistant] I can see real, like, weird similarities between how Arsenal are doing this now to how Leicester won the league. And it's, I mean, they've got an injury to Jesus, which is the only real injury they've had to deal with as far as I can think of, right, so far.


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[Assistant] And eh, that could be the real thing, like in previous seasons they've had, like, I think Odegaard's been missing, and Party's been missing, and all these sort of people that really help that team work. They've avoided that so far, so everything they want to do is working. They've also, like, fostered this, ehm,


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[Assistant] You know the steps they've tried to take or Teta's tried to take from that, uhm, Amazon documentary. We're trying to, like, get the crowd closer to the players. That's definitely helped. So now, like, the stadium just seems more alive. When I used to go to the Emirates quite a lot when I first moved down to London, it was always really quiet and it seems a lot louder now. And the fans just seem more up and at it.


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[Assistant] Up and at them. But what you also get is that, uhm, it's like a seed mentality thing, that thing that Alex Ferguson always wanted, and there's always people talking on Twitter I keep seeing, or just talking about how Arsenal, like, no one expects them to win, like, everyone's against them, everyone's against them. There's no conspiracy against Arsenal.


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[Assistant] Yet there's this thing where like, they shouldn't, I don't think many people predicted they would win the league this season.


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[Assistant] They've also got the two teams who should be at the top, Liverpool and Man City, in my opinion, who are nowhere near their best. City, not that far off, but you know, they've dropped points that they maybe shouldn't do. Legion to Man United's a big one. Uhm, and then Arsenal are the best of the rest by far, and they deserve to be ahead because they're playing really well, they're really cohesive.


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[Assistant] They're managing to avoid injury problems and it's a tight unit that are working really well and all those things together tend to be what you need. They're very hard to get all those things at once and they've got that.


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[Assistant] Hasn't scored a goal for Arsenal since 10th, no wait, what was that month, the 1st of October? Was that the 10th month? That's the 10th month. There we go, thank you. So that's the last time he scored for Arsenal, it was against Spurs actually.


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[Assistant] And then, since then, he hasn't scored any goals. Then he got injured obviously, so he's missing. And in Ketia, I think Thierry Henry spoke about him in a recent game, and I agree with what Henry says in that, in Ketia looks like a really good squad player, and you can see he's got attributes there that he could go and become a decent striker for Arsenal, but I haven't seen enough of in Ketia in games I've seen to him.


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[Assistant] So far, to think that he'd be the real top level that they'd need. He's a really good squad player.


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[Assistant] Yeah, he's doing things in different games now and his scoring record is really good at the moment, so he's getting chances in finishing them. But he's doing a lot of things really well for that team that suit how Arteta wants that forward to work. It works quite well.


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[Assistant] This is what, I mean, how does, is that something he improves over time? He's dead young, isn't he? How old is he in Katia? He's 23. He's the same age as Darwin Nunez. So, like, you think...


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[Assistant] Well, I don't know if we learned that much about Spurs from this game other than what we already knew is that they struggled to create because they rely an awful lot on wingbacks being part of the forward line and then everyone else is meant to defend in a certain way and


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[Assistant] He wants a lot of high intense runs. He wants you to do a lot of off the ball work.


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[Assistant] In the hope that that then grinds out the result and you can get forward from that, but you need really good wing backs that they want the same people like Pedro Poro. It sounds like, like he's going to be so good. That guy get him in now is great. So anything to get him or then just them free. So make a huge difference because they'd get another high quality right wing back. So they've got Matt Daugherty. He's fine.


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[Assistant] And then, like, Arsenal were able to play their exact normal system, but then just drop Saka back into a wing-back role when they need to, to have the five to cover them, so then that negates what Spurs want them to do going forward. Human, Sun has not been the same player this season.


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[Assistant] I think you can, you can definitely get your, so what teams will do in the week before a game match is they'll have one day they'll, they'll arrange a match between their first team and either the second 11 or the youth team.


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[Assistant] Who are set up exactly as the opposition will, and you know how spurs play. There's very little variation in how they play, it just depends on how well the individuals do.


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[Assistant] But the hope for Conte is that it's defensively solid and it gives them a threat on the counter. But you see the Arsenal's defensive line was a little bit deeper in this game just to stop those team, the players who were really fast getting behind us did in the game that they won 3-1 I think it was early in the season.


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[Assistant] And I think what you see with Spurs is that players aren't responding as much to what it is they have to do. Like when you look at Arsenal,


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[Assistant] Well, I think it's not even just getting, like, better players. It obviously is, but it's getting the right players to play the way you want to or the right characters. And Conti always seems frustrated. He seems to realise that the ceiling is about fourth or fifth for what he's got unless they invest heavily. And I can imagine it's very frustrating being a Spurs fan.


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[Assistant] Continually knowing that you're just never going to be able to compete with everyone else around you, but you sort of are. Then you watch teams like Newcastle fly up above, obviously they have a lot more funding in the background.


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[Assistant] Going on. And then, if you look at it again, comparing the two clubs, Arsenal and Spurs, Arsenal waited with Arteta, were patient, and the club were aligned. So, what Arteta wants to do is align with what Edu was doing. They didn't bother spending more on Mudrik because it didn't align with what the vision was. That's exactly what they do.


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[Assistant] Spurs, uh, don't have that, seem to have that, again, cohesion between the management and what the actual club wants to do, and you can sort of see it play out in the pitch. Fans very unhappy at the moment.


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[Assistant] Yeah, they would, they would, because you're always stuck, and it's just like, if you're a supporter and you, like, put a lot of what your identity is and who you support, and that's what your weekends are spent doing, and your weeknights watching this team, and they never go anywhere, it's a point, it's a point in life.


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[Assistant] You just sort of trip along doing nothing. You're never going to achieve anything. It's all right. And then the thing I was going to finish off with, but if you look at Arsenal versus Spurs, is that Arteta, that'll work with Arteta. Spurs sort of had that with Pochettino. They had that and then it didn't work anymore for Pochettino. And then they got rid and now they're just sort of. What was that list of things you just said?


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[Assistant] The Aberdeen Joe Lewis was very, very good. He was probably the best goalkeeper in the league for a long time at Aberdeen. I love how there's always an Aberdeen thing. Well, I think you learn a lot about football from watching Aberdeen. Really shit teams, like often. Because it's such a low level, you can really see the difference between someone who is alright and someone who is good.


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[Assistant] Well, they might be. They're not too far off it.


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[Assistant] Anything can happen with a couple of wins and I don't know. They're alright, they're winning those games in a row, that helps. They're starting to get a bit of momentum going between them as well. Marks Rashford's playing very well.


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[Assistant] I think what you can see is that the players believe that what Ten Hag wants them to do is the correct thing, and they buy into it. And eh, he's raised levels of players and dropped the ones who were awful. It's like, McGuire's out, gone, Luke Shaw's playing at centre back.


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[Assistant] Yeah, he's decent enough. Like, it's difficult squad management because you have the- is he captain of England? No, it's Harry Kane, isn't it? He's captain of Man United. It's really difficult to manage that.


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[Assistant] Well, it's, I mean, it'll change in different phases of the play and different bits of the pitch, but the first time in City are building, the whole idea is to stop them playing into the players who can control the game, like Rodri, De Bruyne, Silva.


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[Assistant] Foden, this is hardly got a touch. You look at touch maps, em, Holland's touch map is basically in the centre circle because he kept, he started dropping deep trying to get on the ball to keep touches.


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[Assistant] Yeah, and it's, and then it's, to do with the way Man United played, like, not everyone's involved actively, they're not, you don't see them tackling or making interceptions, but just by being in the right position at the right time, the spacing's perfect.


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[Assistant] There's, there's two sides to it, because it's, this temple was much faster, and that's what they needed to do, but to be able to do that, you have to have clear passing lanes, free, and players in space be able to do that.


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[Assistant] And it's, they started a bit slow, they're in a little bit of a dip at the moment in City, they're not playing with the same speed and energy and aggression that they normally do, but I think that'll come back, I think they'll finish strong. Yeaah. Yeaah, you saw that, so it's a little bit of Man United did play in a certain way to make them play badly, but City didn't help them.


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[Assistant] They, if you play Holland in behind those chances, sure enough he might get...


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[Assistant] You think you'd score and that'd be how you want to play, but that's not how Guardiola wants to control the game.


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[Assistant] Because if you put, if you put the balls through every single time, uhm, the defense will just drop off you a little bit and then maybe try and deny them. But basically what I'm trying to say is that if you get in behind, it might then come back the way towards you and you'll concede in the counter-attack. So you want to control the game, get your players in the right position so you've got your rest defense there so you can


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[Assistant] Easily then, just have control of the pitch and stop the opposition being able to counter you.


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[Assistant] So, uh, Bernardo Silva's quite guilty for it a lot, like he'll take the ball forward, haul, and I remember one particular run where Haaland just like sprints, he's at fool's pace, and if the ball comes in, he's in behind.


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[Assistant] No one else is in position to be able to deal with it if it goes wrong. So it's all about being safety. Like safety first, you can push up the pitch and get in it. And then...


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[Assistant] What they're trying to do is add this amazing striker to what City already do and how they've controlled games and won titles in the past.


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[Assistant] You don't want it to suddenly change to being only on the counter-attack playing him in. I mean, it's a way you can win games. But you want to add that to make yourself better. And if he keeps making that run, defenders are going to get tired. Eventually they'll just not think the ball's coming and that's the time to switch off. And then he's cleaned through and that's how you get your goal to win. But you still get control of the game. I think that's why they're doing it.


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[Assistant] I saw, well, because it was a 3pm kickoff, wasn't it? Yes. So unless I went to the pub, I know that has the illegal TV. Uh, I couldn't watch it. But the, um, no, I saw the highlights and I've watched twice now. Okay. Jürgen Klopp described it as like the worst game, not just at Liverpool, that he's had.


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[Assistant] But then they had a problem with Brighton before, they've lost to them before. And I think they've been worse in previous games from what I've seen from the video that I've watched. They're just all in that mess.


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[Assistant] That's a strong Liverpool team they put out. Like in theory it's their best midfield, Fabinho, Henderson and Thiago. I'd say that's their strongest midfield. Uhm, and you'd think the weakness would come on the left side defensively because it's Thiago who's not the strongest at trying to stop that sort of stuff. But you've got Robertson and Kanati, I think is a brilliant player and Matip is a good player.


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[Assistant] You've got a Master's in it? Yea, I do, so I've written one of them wherever it's told. What's the difference between a thing and a thing?


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[Assistant] What's the difference? So as a primary distance, it's a degree programs that require these projects. Students in a masters degree will write a thesis, whereas students in a doctoral degree will do a dissertation.


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[Assistant] A rare moment where I don't find something funny. Yeah, I think that's terrifying. No, no, it is terrifying. And they had, like, they had one of the directors in a headlock. Yes. Like, that's genuinely, we talked about this a few times, like the invisible walls of safety are starting to fall down. There's a lad who kicked Ransdale in the back of the head. Oh, and in his body.


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[Assistant] It's, it's really dangerous that you think all these things, what happens until someone really gets hurt or something like that. Like these, that boy, Jerry Mina, there's a video of him talking to some, like a bunch of lads all filming on their phone. That's terrifying. Like this guy's a young man.


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[Assistant] I mean, you can't take all the good stuff with fans unless you don't have the band, but then there's that thing, like Everton fans are such a bad...


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[Assistant] Uhm, they were not confident in the management of Lampard, or anything's happened with the last few transfer windows, the players they brought in, whether that's bad.


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[Assistant] And the system they play doesn't look particularly fun, they keep moving players around, lots of injury problems as well. It's just a bad place to be.


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[Assistant] I think they're so similarly weighted as well, so that if you put, I mean, like Aston Villa versus Leeds to me is quite a similar game. Like, some of the players are really good, some of them are average, but...


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[Assistant] And all that happens is that they mash into each other for about 60 minutes, then someone makes a tiny error or is a penalty.


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[Assistant] So you go Carlos at Villa, really, really depending on him to make a big difference and then go get injured. So you can't have that sort of thing. There's loads of little decisions that go against you. When you're that evenly weighted, it's really hard to...


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[Assistant] Make the small differences, but then, yeaah, you put in someone like Lopetegui and already


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[Assistant] Like, wolves look a bit better. Like straight away with that. And like, Unai Emery, you can see very clear things that he's changed at Aston Villa. But you get this, I think I talked about this last week.


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[Assistant] Is that they come in, and if the first couple of games go well, the players will be like, oh I believe in this, this might work, and you can really get the momentum behind it. Whereas if Lampard comes in and goes, right guys, you've got to work really hard now.


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[Assistant] playing this like 5-4-1 that offers very little other than crosses into the box or like a disjointed midfield at centre back group doesn't look that strong.


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[Assistant] They're like, oh my god, I've got to grind this out. And then you start getting like scared at pressure and you come out of your stadium and you're getting surrounded by fans who are going nuts and you hear about stuff in the boardroom. That must be not fun. So how do you possibly get happy to be able to come into it?


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[Assistant] I mean, I know I keep, I always talk about Football Manager and it's not actual real life, but a lot of that game, being good at it, it's just getting the players to have good morale, that's all it is. Taddocks don't matter, if you have good players and you have the morale up, that's basically how you win stuff. And I think, for a long time I thought I was stupid, but now I'm starting to think that there's a lot of psychology to that that I never really thought of. Having said that,


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[Assistant] Oh no, I totally agree. Like, if you put, if you took Thomas Frank or Deserby or, well, Marco Silva out of Fulham, and you put them in Everton, I think they'd be better. I don't want to absolutely bury Lampard, because I'm talking about margins.


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[Assistant] Sure, but there's, there's certain things that those coaches would have that I think you may be lacking other managers. I don't know enough about, uh, as we call them, Luton Jones, the center manager, eh, to know, I still, I still have...


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[Assistant] Remember that video we did in IRL with uhm, uh, oh I've forgotten his name, uhm, Bartek? We never made it. We did, we went out. Did it? Yes. Did it? Did alright, yea.


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[Assistant] Yeah, what's his name? Bartek, Bartek Silvestrak, Bartek Silvestrak. He's a kicking coach. That was his title. He was at Brentford for a long time.


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[Assistant] So he like, he works with a lot of players, um, outside of their training to develop their free kick and their general ball striking skills. And he says that Messi's not a very good ball striker. So like, I think that doesn't sound right, but this guy, professional ball striker,


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[Assistant] Coach, works with all these players. And eh, the player he says the best of all time at free kicks is Juninho Permambucano. Brazilian, he was genuinely amazing.


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[Assistant] And then, after talking to him for a while, he said that Ward-Prowse is the only player who really has that technique and what makes you good at free kicks and that ball striking is consistency of always hitting the ball in the same way and being able to put it in either


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[Assistant] Second striker or attacking midfielder, that's really useful. He's a freak. A dead ball freak. A lot of work went into that.


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[Assistant] Barcelona are amazing against Real Madrid. Gavi was unbelievable. Uhm, like just, he's 18. I can't believe how good this guy is at 18. It's crazy. Like I love Pedri. He was also brilliant. He does all these, he's very iniesta like some of the things he does with his like double touch and stuff. Gavi or Pedri? Pedri. Pedri. But Gavi was just running the show. Yeah.


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[Assistant] Oh, they just couldn't get close to him, and uh, yeaah, I don't remember watching the player so good, so young. Pedray maybe, I guess?


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[Assistant] Yeah, but then Pedris is a slightly different kind of player and Gabi makes things happen slightly further up so it's more exciting. It's fun to watch, I mean they're top of the league Barcelona as well and that's them who won the Super Cup and so you'd think that might be a little thing to help them kick on and know they're going in the right direction.


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[Assistant] Yeah, this was bad. So there's a couple of like big, like referees, I know people moan about the refereeing in Premier League say it's an all time low, they've got no idea. No idea. Refereeing in Scotland is, ehm, embarrassing.


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[Assistant] And it has been for many years, just like, ludicrous decisions all the time, all the time, all the time. But what you had, like, Rangers beat Aberdeen in the League Cup semi-final, it was the League Cup semi-final weekend, both games played at Hampden, Scotland's quite wet.


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[Assistant] Celtic and Kilmarnock played on Saturday, chopped the pitch up like it was a rugby game, and there was a penalty not given to Killy, which is clearly a penalty. The defender comes straight through the back of a guy waiting for the ball and flattens him.


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[Assistant] I think it's a surprising decision, but also I don't think it's surprising at all in Scotland. I don't think there's some sort of conspiracy with the old firm either, by the way, before anyone starts thinking that. I think it's just incompetence.


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[Assistant] And then, eh, in the Sunday game, it's not incompetence, but it's just embarrassing in that VAR, the connection just stopped basically. The connection. So there was just no VAR for...


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[Assistant] Scales. Do you think that might have possibly been a red car which would have levelled the things because the Aberdeen captain had got himself sent off for trying to put Fashions of Cala out of the stadium with a tackle.


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[Assistant] Conspiracy. Conspiracy. There is no conspiracy, it's just that certain referees are not very good in Scotland. Like, I go harsh on it, just to make myself sort of laugh at it, because it's ridiculous. It's also pointless supporting the Scottish club apart from me, it's just pointless, absolutely pointless.


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[Assistant] There's no point. If we'd beaten Rangers and got through to the final, we'd have to beat Celtic and we wouldn't do that. You need to have everything go your way.


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[Assistant] And it was a great experience, but after four years, we felt as writers it was, it would be better to push ourselves out of the nest.


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[Assistant] Respectful of the words on the page. They wanted to make that work. They had confidence in what we were doing.


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[Assistant] You know, I don't know whether I'm excited about this or I don't know how to feel because, you know, you can't really, you can't really project. I can't say, well, since it's taking this long, we good.


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[Assistant] Or since it's taking this long, this looks bad. Yeah, we had like they didn't waited you all the way out. You don't know which way it's going to go. And I think


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[Assistant] I've been saying this all along. When they had David Bell. I've been saying that when they had, uh, uh, Anthony Schwartz. I've been saying that when Donovan Beeple Jones was cool. Here's the thing. You can't count.


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[Assistant] On receivers, first or second year players to come out there and hit the ground running and just be ready to go. There's a ramp up period, right?


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[Assistant] You got guys that are coming in college and in college you can get in and out of your breaks. You just got a different gear from such people.


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[Assistant] I know what type of speed and game time time it is.


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[Assistant] You get out here and you get with the veterans, you start to notice something. Hold on, I can't pull away from cats like I used to. Where my separation? I gotta, I gotta go 95% just to get what I need to get done over here. And then what happens? You don't have any acclimation period. Then it comes to hamstrings. Then there's a growing injuries.


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[Assistant] You need a time to learn as a veteran how you need to develop your body and get your body ready so you can get to the season. See, a lot of rookie cats get out there one, two days, all of a sudden they're on the side with the bike and the Gatorade. Now, you looking at what Anthony Schwartz


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[Assistant] The Gatorade sipping that cool, that cold Gatorade. That ain't gonna do nothing for you. And if the Cleveland Browns got two, I understand if they third round picks. But you gotta, Anthony, you know, David Bell has a stress fracture in his foot.


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[Assistant] That, I don't, I mean, he's a nice ball player. Donovan Peoples-Jones, okay. And you look, you got the rookies that is coming in here, that you looking to, no. Go get you a receiver and stop playing around.


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[Assistant] Your veterans are looking around. Miles Garrett just made the comment yesterday. Hey look, it don't matter what we need to do. The goal and the plan is to win games regardless of what it is. So he's looking at Andrew Barry. He's like, hey, hey, hey, now I know we focus on Deshaun.


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[Assistant] How much do- does the receiver's knowledge of routes?


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[Assistant] The route tree. How much does that help in scheme to scheme? So say for instance, you play in Seattle. If you play in Seattle, you play receiver with Seattle, could you go to San Francisco and say, okay, well, this is kind of like this a little bit. Or is there some time period that you got to get ramped up and learn to playbook?


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[Assistant] In the words of Conceited, slow it down, I just dissed you. Do you need me to put it in subtitles or something? You talk about vibes, right? This is, this is the most, everyone knew this.


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[Assistant] There's two factions. There's people that was in Baker Mayfield's camp. He just so happened to have the people that were mutes. Guys that didn't talk. The chub like him, the offensive line like him. Cool. But then you have a whole nother faction.


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[Assistant] Lay it. And most, one of the most vocal people in the locker room was John Johnson III. And his, now I wouldn't say disdain, but when, when, when Odell Beckham Jr. left,


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[Assistant] It just was this, either you on this side of the camp or you on that side of the camp. And when you, they started seeing Odell Beckham Jr. out and they said, yo, people left, showed up at the airport crying, sending letters. I said, y'all crazy and Baker over here chilling. And then for Miles Garrett, he really signified it. He said, yeah.


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[Assistant] You know, Baker said he woke up feeling dangerous. He had a lot of feelings. And guess what? He's telling him the vibe was not on and popping. I gotta get the guy agree.


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[Assistant] Here's a feeling, and I try to give this to different people when they say how is it when you talk about winning. When you a player, you invest that much time of your life in stuff you don't like. I gotta lift weights, I gotta wake up at six, I gotta run, I gotta be accountable. The only thing that makes any of that worth it is winning.


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[Assistant] We love each other, but that feeling you get.


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[Assistant] But you won though. You making all them deposits in the bank. All them deposits. You putting all that money in every single week.


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[Assistant] But it's worth it when you go out and you got that down payment for that house. You give them that cash, you just be like, I ain't even worried about it. And they be, y'all been on teams where y'all done been on teams that were so good. They had the synergy so well.


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[Assistant] And you know, and you know, when you plan for Ohio State, you just, y'all, y'all like, there ain't really nobody that's going to beat us. No.


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[Assistant] He's gotta do it better. Joe, I'm gonna tell you something right quick. Let me holler at you Joe. Now, now listen.


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[Assistant] You got a bunch of, you got, you got world class athletes over there.


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[Assistant] You got every, you got the makings of a top three defense.


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[Assistant] You got two dynamic air rushers, you got the most dynamic linebacker in JOK, you also got three safeties that's interchangeable, Denzel Ward, Newsome can play inside and outside, AJ Green, you got link that corner, they got six three corners. Now listen, if you come out here, I know something, you come out here against the Carolina Panthers.


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[Assistant] I know what Baker Mayfield does and does not do well. We've all seen it.


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[Assistant] He does not diagnose blitz as well. He does not operate well out of the shotgun. And if you show him a pre-snap look and then give him a post-snap look, he out here patting the ball, throwing the ball, doing spin moves, throwing it behind his back.


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[Assistant] I think Miles Garrett has set the tone. And by the way, he did a better job. I talked to him. You don't just generate pressure by blessing.


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[Assistant] You can do stunts up front. You can move Miles Gaird around, put Miles Gaird and Jadebe County on the same time, same side. You can kick Miles Gaird down to a three technique. You can bring J-O-K off the edge, right? There's all kinds of things that you can do with four. Just don't make them say every single play, I have to diagnose.


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[Assistant] Respect. Respect. Respect. We were sitting here. We was talking your cup of tea. We talking about the defense and we was talking about.


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[Assistant] Uh, the, this, the idea of John Johnson saying that, hey, all the guys is back. All the guys is moving around. We feel a better vibe. Uhm, when you're playing on the defensive side of the ball,


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[Assistant] Oh, you did? Yes. Well, you know, I think this is going to be, see, this is going to tell De'Quel exactly who the Cleveland Browns, uh, coaching staff is, right? We've been talked about a lot about Deshaun Watson, and I want to make it clear, right? Coaching counts.


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[Assistant] Like, your game plan counts. You know, how many times, how many times have you been on a team where you've gone into a game and you just knew by what the plan was that week?


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[Assistant] Where do you think that, you know, explain to the people how much a coaching game plan counts on Sundays?


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[Assistant] Like, you see what I'm saying? Like, it's a fact. And on top of that, the whole COVID debacle, yeah, I'm back today, but not really. That's not what he said. He lied about me. He never said that.


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[Assistant] You lose at home all the time. Every year the Packers got cone-filled advantage throughout the whole playoffs. You lose to Eli Manning.


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[Assistant] You lost to, you lost to Tom Brady. Then you came back and lost to Jimmy Garoppolo. Wait, no passing game. They ran the ball. They put receivers emotions and ran the ball and you couldn't get, you got Devontae Adams. You got Aaron Jones. You got Dylan in the backfield. They got multiple weapons and guess what? You never get it done. You haven't won since 2007.


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[Assistant] Do they have, do they have, do they have a description of what a tier one quarterback consists of? No, you take it however you want. You take it however you want? You take it however you want.


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[Assistant] Seven rings. Let me ask you, if Patrick Mahomes sit out a year, tier one. He's got a ring. He got a ring. Josh, Josh Allen sit out a year. Nope. I guarantee he's still tier one. He's still tier one.


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[Assistant] Oh, so that was tier five. So did they have a, did they have a tier four description? Oh yeah, I didn't see these descriptions.


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[Assistant] I, well, in that case, I would agree with that for Baker tier three. By the way, I'll give you it. You mentioned James.


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[Assistant] Let's be clear, let's be clear, go ahead and wrap this up.


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[Assistant] They got a problem. Everybody, everybody is a capitalist and free market guy until it comes to black players. Let's just be real with it, right? Let's go ahead and just say that.


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[Assistant] Because if you're talking about video game players, if you're talking about golfers at the live tournament, if you're talking about all these people making all this money.


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[Assistant] It ain't never no problem until $230 million dollars. You know, the market go up. Sam, Sam, what is the guy, uh, for, for the Eagles, Sam, no, the, for Oklahoma, he played, never played. He's the last big dude with the contract.


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[Assistant] Corporations don't want taxes. I want the least amount of regulation. But when we come to a sport, it's, oh my, well, we got to have guard rails. Let's get guard rails on the NIL. We don't want to, well, no one wants to get too rich. Come bring me my cut first. Give me my money. And then we might let you get some of this table scraps.


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[Assistant] He was literally a Hall of Fame player. He's a Hall of Fame player. It's crazy how the rules have changed.


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[Assistant] It was time to move on. You think so? Oh yea. Hey, but I've always said this and people say what they want. Yea. Baker Mayfield is by far


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[Assistant] I'ma go, I'ma go, only, I got one sign something, that's it. So I got, I got Paul Warfield, gonna do that one. We gonna do, uh, Jim Brown, we gonna do that one.


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[Assistant] Uh, I gotta put Josh Gordon in there. Got to. Uhm, and then.


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[Assistant] I'ma go back deep. Eric Turner. He was the J.B. Ronnie lot here. So Eric Turner. Fuck about him. And uhm, I'ma do, this is tough man, cause I like, I like Leroy a lot. I think it's a tie between Leroy and Eric.


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[Assistant] Cause them was the dude, them was the backs at the time, right? But I could've did a lot of other, but yeaah.


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[Assistant] You know, you know, I think sometimes really diehard guardians fans don't understand it, right? Because baseball people are baseball people. They want to support baseball. They want to support the guardians, right? And so when, when people that are in the fringes say, well, listen, man, you call me.


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[Assistant] When they decide to act like they want to win. And you say, but, but they're competitive. They do want to win. No, no, no, no. See.


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[Assistant] Let me just show you this, right? Right. Have you ever, like, you go home and your wife, right, you know she don't want you spending no money, right?


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[Assistant] We ain't, we're not looking at that. The Indians, the guardians have to come in and say, look,


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[Assistant] I understand this is a Brownstown. I understand that the Cavs is, we, we compete with the Cavs, but we gotta make moves because the Cavs is making moves. There is Garland, Mobley, and I always want to say that economically you're competing for those entertainment dollars.


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[Assistant] You said Jose Ramirez gave money.


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[Assistant] I watch more games just as many in many games in terms of day by day with the Cavs who were NBA Finals champs.


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[Assistant] And with the Indians at the time, I watched and went to at least 10 games and watched a substantial amount, 30, 40 games on TV. Now that's because I knew what I was watching. They was competing at the highest level.


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[Assistant] I mean, black rappers have a very defined shelf life. Like, if you make it past 40, you good.


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[Assistant] Listen, I would donate all my money, get it together with other people, and we will eliminate, we will eliminate endless terms in the United States Senate.


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[Assistant] We will get rid of that tomorrow. I need, I need to lobby the hell out of that because I tell you what, half the reason these people, veterans is out here with no, no place to go living under bridges is because y'all like wars, but don't like taking the people care of the people who participate and they up there just sitting around, hanging out, drinking tea.


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[Assistant] I don't hate it celeb. I don't hate it. Let me see. I gotta find somebody else.


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[Assistant] Actually no, like I would sleep, I would sleep more, like I feel like, uh.


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[Assistant] That this is actually correct, right? I verify that I have the winning ticket. Then what we do, we contact a lawyer. I'm getting a lawyer in a security firm. My lawyer's security firm.


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[Assistant] Make sure everything is good. And I contact every one of my, every one of my family members in second cousins, eighth cousins, whatever. They all show up. We will be in one location. I will run a PowerPoint presentation.


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[Assistant] This is how much you get if you are a niece, cousin, nephew, inner circle family.


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[Assistant] If you are a, if you are a child or if you are, are in an era where you, you are between the ages of 10 and 18,


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[Assistant] I got 200 million. The rest of that goes into some sort of annuity. Then I got a lot of family members in the Philippines. You know how I got 12


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[Assistant] Daughters, right? Would you, would you give them the money? They're of age, right? They're never slightly responsible, so would you give it to her now?


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[Assistant] And by the way, you guys have, you guys have, uh, daughters, uh, I would have a beautiful, uh, agreement drawn up by my lawyer team that it doesn't matter who you marry, they are not entitled to any coins over this way. Oh, that's a fact. No, no, no.


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[Assistant] Man, like when I was at OU, OU is a big Halloween, everybody dress up. So I was dressed up and my girlfriend at the time, man, she like passed out drunk, bro. So I had to like carry her back to her spot. But like I'm you can't have no like big black dude. I'm about to say this ain't a good look.


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[Assistant] She was, yeaah, she was mixed. She was light-skinned. Where were you at? Okay, okay. Where were you at? I was at OU in Athens. Ohhh. Yeaah, it was bad.


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[Assistant] You know, see, here's the thing, man. I, well, I'll give you, I'll give you this. You know, I'mma just freestyle this one. See, a lot of people don't get, man.


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[Assistant] You know, you, for a lot of athletes, your best years is 18 to 25.


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[Assistant] And that, that, that means more to me than football. Cause when I was done and didn't even make it to the league, didn't even make it to the highest level.


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[Assistant] Your next move can always be your best move. You got so much time in front of you. You got so many different things that you can do. And if you ask somebody today, what do you know Garrett Bush from? They're not going to say McKinley football. They're not going to say Ohio University football.


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[Assistant] They gonna mention what I'm doing now today. They'll say the barbershop. They'll say ultimate cleaver sports shop. They say locked on Brown's podcast. That just goes to show you. You got you.


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[Assistant] Athletes, we are not just athletes. You got a lot to offer. You got more to offer. And I'm telling you, your future and your career is going to be better in this than it was in that.


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[Assistant] So I'ma just let you know, keep grinding because you got with something that a lot of people don't. A lot of people can only do football or talk, you know, hang out and do sports. You can do both.


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[Assistant] And you can make just as much money and be as successful in this than you is at that. So just keep doing your thing and you'll be there. Appreciate it.


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[Assistant] I think he was just stating that as a leader he would have stepped in and hopefully been able to help as a number of the individuals that were in the school, the coach and other adults. And even a lot of the students stepped up and helped protect other students. I think the point he was making is that he would have wanted to have played a role in that as well.


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[Assistant] Death sentence for European democracy and a betrayal of American interests and ideals. Unquote.


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[Assistant] Hey everybody, I am Cinnamon Cooney, your Art Sherpa, and today I'm going to show you how to paint this adorable corgi bum bum, little corgi puppy bum bum, step by step, fully explained, every technique, every color mix for beginners. To help me do that is my husband John.


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[Assistant] He's gonna make sure that when I'm demonstrating a technique or explaining how to do something, the camera's pointed directly at what I'm talking about so you can see it and duplicate it at home.


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[Assistant] Now maybe you're here because you are a proud corgi parent or giving a gift to a corgi parent. This is a perfect lesson for you even if you're very, very new to painting. I've got all the beginner resources and they're all free for you.


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[Assistant] Check the description down below if you need more information or directions to our website for all those resources. They're all down there. Now maybe.


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[Assistant] You're part of the beginner acrylic painting course. And if you have been taking part of that, this is the last painting in the series. This is painting number 10. So you've done the seven fundamental introduction paintings and the 10 paintings that every beginner should do before they are out there to become a fully ready to go one hoot certified painter.


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[Assistant] Congratulations for getting here. Uhm, I have some instructions for you at the end of the video that you should definitely follow.


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[Assistant] Whatever brought you here, first time painting, or taking part of the course.


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[Assistant] You know what John? There's nothing to do but take everybody and come back and show them the first step.


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[Assistant] I'm going to take a number 10 bright brush and I'm gonna get it lightly damp. I don't want it to be particularly wet. And I'm gonna load up with a little black. Maybe. Should've gone.


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[Assistant] Just a small amount of black and I'm going to make a good amount of a very light gray, John.


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[Assistant] I picked light gray because this was a very neutral color.


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[Assistant] You could do a pink, a yellow, a very light green.


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[Assistant] Any kind of background that helped tie it into somebody's decor more. So it's a place I think that a beginner could really customize it and not find themselves too troubled by that part.


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[Assistant] I'm going to make my gray, I'm going to do brush strokes up and down.


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[Assistant] I'm gonna take a little black over the right. The reason I take a small amount of black to the white


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[Assistant] With very little pigment where it takes a lot of weight to change the black. So it's a paint management strategy.


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[Assistant] I'm just brushing up and down. It doesn't have to be completely uniform. It can have streaks in it a little bit. Not transparent streaks that, uh,


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[Assistant] And it's nice. It gives it a nice little background. When I was designing this, I initially


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[Assistant] So sometimes on the little previews, you'll see me make creative decisions for you guys, the students to make your experience easier. We're all evaluating go, Oh, y'all are not going to love this.


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[Assistant] Or it's not gonna come out for new painters and I know that from my experience. So I'll change it up so you have a good experience at home.


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[Assistant] I'm just going up and down. Notice I'm not taking my brush all around in a bunch of different directions. I'm painting in vertical, up and down brush strokes, and that really helps the finished look of this background.


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[Assistant] Up and down on the white of the brush, up and down.


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[Assistant] When I get all of my canvas covered in a light gray, you can see it's a pretty light gray.


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[Assistant] I am going to thoroughly dry it with a hair dryer.


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[Assistant] You can air dry or use a hairdryer at home, but thoroughly dry it. If you're here during the live video, pause the video if need be, so you can hair dry it and then, uhm.


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[Assistant] Come back and continue on with this. Uh, pausing during a live video won't mess with the chat, so you get your social time and your painting time, which is the best part of both worlds. Don't you think, John?


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[Assistant] Alright, I'm gonna draw mine, you draw yours, and we'll come back and I'll show you the next part of this painting.


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[Assistant] So in this stage with the canvas fully dry, I would normally want to take a chalk tool like the Dritz chalk tool, right, which is a tailor's tool with just cartridge chalk in it. You could use chalkboard chalk here, it would be just fine. But it's a type of thing that I can sketch and erase.


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[Assistant] However, it is very light for you guys to see at home and I want to show you how


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[Assistant] To uh, sketch this in. So I'm gonna use white paint.


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[Assistant] Uhm, for you at home what you would do is you would use your chalk following along and then go over and white paint. But I'm gonna show you from the white paint. Does that make sense, John? Right, and that's just so you guys have, have some visibility on what's going on.


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[Assistant] If you're not comfortable with this stage, you could also use the traceable here, and that's available on the website free.


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[Assistant] The first thing I'm gonna want to do is I'm going to want to kind of come around and sketch a little round bum bum. I'm about three fingers over from both sides.


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[Assistant] And a little bit above the halfway mark of my, uh, canvas, if I divided the canvas in half, just a hair off my halfway mark, and I may even move it down.


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[Assistant] I'm gonna bring it down. Make sure you've got about two or three fingers from the bottom.


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[Assistant] And almost where the circle would join, right, if you were to join the circle, I come back and make a little paw.


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[Assistant] And once I've made my pause, then I can come across.


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[Assistant] And that's that sort of little laying down with paws back positioning.


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[Assistant] Now up top again, you need some space from the top, so let's make a mark.


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[Assistant] I'm going to, and I'll show you, you have a little bit of a circle here about this size. It's like a very small apple. Right?


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[Assistant] So when you know where that placement is, I'm going to take my air curve stroke coming up.


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[Assistant] And loop back in. If drawing is not your skill yet, that doesn't mean you're not an artist. That's a separate set of skills that you can develop over time. And that's why I provide traceables, because if you're not ready to draw yet,


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[Assistant] That's okay. That might be in your two or three hoot journey down the road.


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[Assistant] Today you just do what's comfortable for you. Now I'm not going to do the little flick outs of fur quite yet that are going to be here.


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[Assistant] Kinda giving, giving our corgi a little jaunty feel.


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[Assistant] And that's because I want to be able to sort of paint those out in just a second. Right now I want to get a good line on the little muzzle. So I kind of put a little bump in the nose. And then I'm going to swing back.


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[Assistant] To the mouth, the mouth comes back not too far, it's just about two and a half fingers.


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[Assistant] I'm bringing a little tongue down. Coming out the side.


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[Assistant] Coming off the back of the neck, if you think that the little corgi goes like that, then you can


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[Assistant] And bring that there. And once you have all this in, then you can be like, oh, I think that there should be some little bit of fur kind of come in there. Now, we know that there is a bit of a little blonde


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[Assistant] Eyepatch here, and initially I was gonna do my daughter's dog Shortcake, but Shortcake is the


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[Assistant] It's not the Pembroke. What's the one that's the three colors? There's the Welsh and the Pembroke. It's the Welsh, right?


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[Assistant] You'll see when we do the bones, brown is a challenging color to get to sometimes on primaries. So I didn't want to make you go through a lot of that with the dog. Now from the top of the bum bum,


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[Assistant] I'm gonna come down, oh gosh, like three and a half fingers. And we will make a little


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[Assistant] Implied tail, a little curved kind of column of strokes implying that tail. And then right here coming up.


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[Assistant] We'll do that. And the reason we do that is because, guys, it's like a heart.


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[Assistant] Corky's little bums look like a heart. You may have already known that, but maybe you didn't. I'm gonna make little circles right here for the paws. Alright.


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[Assistant] While we're here, we can also take a minute to do a little bit of sketching for ourselves too. So I'm going to grab my white.


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[Assistant] And I'm going to make a diagonal line here on this corner and a diagonal line on this corner. Notice that I'm leaving space top and bottom.


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[Assistant] Make a little circle. A few little circles. About the same size circles on this side.


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[Assistant] That's just a little thing we can do and then we'll put our hearts in now because it's so easy to erase white.


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[Assistant] And again, you can do all of this in shock. I'm just making little circles here.


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[Assistant] And then I want to play some heart thoughts around here. So a trick I'll tell you about hearts.


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[Assistant] I think it's fun to have them be directions. I make a vertical line that's about the length I want of the heart. And then I join both sides.


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[Assistant] This is very big. You don't have to do the hearts. I just really like the corgi love.


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[Assistant] And also lets me make sure that I don't get it too far away from me.


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[Assistant] I can even take this moment to paint in the hearts white. And that will help my colors later be brighter.


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[Assistant] That's a little trick with, uh, student paints is if you paint white underneath them.


[User] Please transcribe this text

[Assistant] Which is important. Sometimes you need to be able to change your mind. This one we'll see when we layer it. But doing the white in now will really help us. Now, how have you enjoyed this course, John? I haven't.


[User] Please transcribe this text

[Assistant] I really enjoyed the experience of the video production. Really kind of cleaning it up and bringing it all together. So that all the resources are, uh,


[User] Please transcribe this text

[Assistant] Kind of cohesive and, and, and height, you know.


[User] Please transcribe this text

[Assistant] You think? I think that's gonna be fun. I'm doing all vintage, uh, this year. You might be doing this course at a different time.


[User] Please transcribe this text

[Assistant] That's okay, I have 1800 other paintings, so, you know, I'm sure you'll find something.


[User] Please transcribe this text

[Assistant] And again, the white will just help our colors feel bright. That's what it does is it just gives us a nice surface.


[User] Please transcribe this text

[Assistant] Layers, sometimes hearts are fun if they layer.


[User] Please transcribe this text

[Assistant] And again, you could do my pouncers here if you didn't want to do the hearts. Oh yea. It would be a good place to do pouncers.


[User] Please transcribe this text

[Assistant] Pouncer circles, or a confetti look, you know, like throw confetti around, throw kind of around like it's confetti kind of story.


[User] Please transcribe this text

[Assistant] There we go, but we have a nice arrangement of hearts now. And we can see kind of our whole sketch.


[User] Please transcribe this text

[Assistant] And we're like, wow, this is balanced. Now I'm not too worried about actually doing this white because it's gonna be brown, but we could just to, just to be responsible.


[User] Please transcribe this text

[Assistant] It's gonna be interesting teaching you guys how to make a brown from primaries. That's a skill that you're gonna take away and use elsewhere.


[User] Please transcribe this text

[Assistant] That is fun stuff for you guys to learn later if you think this painting gig is great. Alright, that was a pretty good step.


[User] Please transcribe this text

[Assistant] We got everything sketched in. You could do all of this work with the traceable if the freehanding was not your joy. That's okay. When we come back.


[User] Please transcribe this text

[Assistant] I'm going to show you what's next. It's a good idea to dry so you don't drag the wet paint, but it's not something you have to do. So we won't make a big notation on it on the step.


[User] Please transcribe this text

[Assistant] But if you have trouble dragging your hands, you may want to dry. Alright.


[User] Please transcribe this text

[Assistant] The next part I'm gonna come in and kinda put the white fur in and I think I'm gonna use my half inch angle just cause it's a nice good sized brush that's not too big and I have a lot of control when I use it.