Waching daily Oct 12 2018

Hello, this is Risa from Anjurisa Welcome to my channel

In this video, I will show you how to make this handmade headband for baby using my fabric flower tutorials

Before we start, consider pressing the SUBSCRIBE button so you won't miss any update

These are the materials we need to make this headband

I have made this fabric ruffle flower tutorial, you can watch it here

For this little fabric flower, you can click the link here

To make this mini bloomy rose, you can click here for the tutorial

and we're going to need stamen

A piece of lace

Felt fabric

An elastic band

and some tools like hot glue gun, scissors, and pliers

First, attach these two little flowers together

Like this

Attach the fabric ruffle flower next to the small flowers

Cut the stamen with pliers

and put the stamen between these little flowers

Attach the lace

I will cut the elastic band before attaching it to the flowers

Our baby headband is finished!

Thanks for watching, if you enjoy this baby headband tutorial,

please like, comment, share, and SUBSCRIBE~

For more infomation >> Handmade Headband for Baby - Tutorial by Anjurisa #6 - Duration: 4:20.

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Steve Rogers Gym Scene | The Avengers (2012) Movie Clip - Duration: 2:51.

you won't be attacked oh my god

this guy's still alive

don't whippin slept for 70 years sir no celebrating seeing the world I went

under the world was at war I wake up they say we won

we've made some mistakes along the way some very recently you here with a

mission sir I am trying to get me back in the world

I'm trying to save it hide your secret weapon now Howard Stark fished that out

of the ocean when he was looking for you he thought what we think the tesseract

could be the key to unlimited sustainable energy that's something the

world sorely needs who took it from you he's called Loki he's not from around

here there's a lot we'll have to bring you up to speed on if you're in the

world has gotten even stranger then you already know at this point I doubt I

think would surprise me ten bucks says you're wrong

does a debriefing packet waiting for you back at your apartment is there anything

you can tell us about the tesseract that we ought to know now you should have

left it in the ocean

you

For more infomation >> Steve Rogers Gym Scene | The Avengers (2012) Movie Clip - Duration: 2:51.

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👋😃👋[LIBRAS] Cine Gibi 5 "Luz, Câmera, Ação!" (FILME COMPLETO) | Turma da Mônica - Duration: 1:11:34.

For more infomation >> 👋😃👋[LIBRAS] Cine Gibi 5 "Luz, Câmera, Ação!" (FILME COMPLETO) | Turma da Mônica - Duration: 1:11:34.

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Embeddings - Duration: 14:44.

Hi I'm Sally Goldman and I'm a research scientist at Google and one of the main things I work on is recommendation systems.

And one thing really fundamental to doing these recommendation systems is embeddings and I'm going to talk about those today.

As a motivating example I'm going to look at the problem of collaborative filtering.

So let's say I have a million movies and I have a half million users, and for each user I know which movies that user has watched.

The task is simple: I'd like to recommend movies to users.

To solve this problem I'm really going to have to learn some structure, something that let's me say these movies are similar to each other, so if you've watched these 3 movies then this is a good movie to recommend.

So as a simple starting point, let's try to take these movies and just put them along a line of one dimensional embedding.

So I will say I have maybe to the left I'll put animated movies and as I move to the right, I'll have more adult-like movies.

This starts to do nice things.

I have Shrek and The Incredibles, those are both animated movies for kids and if you watch one the other one is a good recommendation.

But then I have the The Triplets of Belleville which is an animated movie but really Harry Potter, though not an animated movie, I think is really a much closer movie to The Incredibles.

The Triplets of Belleville is not really oriented for kids as much, it's not sort of a blockbuster movie that a lot of people go to see.

And on the other side for example I'd say Blue and Memento are probably better recommendations for each other than The Dark Knight Rises.

So just having a single line, as much as I try, it's going to be really hard to capture all the intricacies in movies that make people like one versus another.

So what if we add another dimension and now I have 2 dimensions?

So what if I bring the blockbuster movies up towards the top and the more art house movies down?

Now I've achieved some of the things I've wanted.

I've got Shrek and The Incredibles and Harry Potter kinda nearby and they're all pretty similar movies and in the bottom right I have Blue and Memento.

And you can imagine that there's a lot of other aspects you'd want to capture and you'd want more than 2 dimensions, and we would.

In reality we could imagine 20, 50, even 100 dimensions to sort of do these embeddings.

But let's stick with 2 dimensions because I can draw it.

So let's add a few more movies to this and I went ahead and added some axis.

I have the X axis which is sort of more children oriented movies to the left and more adult movies to the right.

And the Y axis, more blockbuster movies to the top and more art house films on the bottom.

And you can see a lot of nice structure here and you can see that movies nearby each other are kind of similar and that's really the goal of what we want.

Now I'm drawing this geometrically but I do want to make sure everyone understands that there's a very simple way to represent these embeddings and that's what's going to happen when I learn them in a deep neural network.

So just using Shrek and Blue as an example, each of these is just a single point in this two dimensional space and the way we write down a point is just a value on the X axis and a value on the Y axis.

So for example Shrek is just the point minus 10.95 or Blue is 0.65 minus 0.2.

So each movie here can just be represented as two reels and the similarity between movies is now captured by how close these points are.

And although I'm only going to draw 2 dimensions, in reality you do want to do this in D dimensions, 2 isn't going to be enough to capture everything.

Implicitly as you think about what you're doing, this is really assuming that interest in movies can be captured by D dimensions.

I'm allowing D different aspects to be selected and then I can move the movies independently among these D aspects and use that to now bring similar movies nearby to each other.

Each movie now is just a D dimensional point, I can write it down as D real values and the cool thing is we can actually learn these embeddings from data and we can do this with a deep neural network without adding a lot of new things to what you've already seen.

There's no separate training process needed, we're just going to use back propagation exactly as before and the embedding layer is just a hidden layer and we'll have one unit for every dimension you want in your embedding.

Supervised information is going to allow us to tailor these embeddings for whatever task you're after.

If you want to do movie recommendation, then we want these embeddings to be geared towards recommending movies.

We will need some sort of training signal, we'll look at some concrete examples but in this example if a user has watched a set of movies then to some extent those movies are similar to each other and should be nearby and we'll aggregate this of course over lots of data.

Intuitively these hidden units are learning how to organize the data in a way to optimize whatever metric we've decided to put as the final objective of the network.

So now let's go back and look at how would this actually be input to the neural network.

The matrix I show on the right is sort of the classic way we think of collaborative filtering input.

I have one row for every user and one column for every movie and a check in this simple case indicates the user has watched the movie.

So now let's think about how we do this within TenserFlow.

Each example is really just going to be one row of this matrix, so let's focus on the bottom row that I've highlighted in yellow.

If there's a half million movies I don't really want to list all the movies you haven't watched, it's so much more efficient to just write down the movies you have watched.

And when I do back propagation I'll be computing dot products and I'd like that also, the time, just to depend on the movies you have watched.

So to achieve this we're going to use the following input representation and to do this we're going to have 2 phases.

The first pre-processing phase we're going to build what we call a dictionary.

A dictionary is just a mapping from each feature, in this case each movie, to an integer from 0 to the number of movies -1.

So I'll just do this in the order I've shown them in the columns.

So column 0 I'll call movie 0, column 1 movie 1 and so on, and this is a one time thing we do as pre-processing.

Now I can efficiently represent that bottom example as just the 3 movies that user did watch, I don't need to worry about all the other ones.

I do it kind of as a pictorial view but in reality it's just 3 integers - 1, 3, 999,999 - because those are the indices for the 3 movies that user has watched.

Okay so now that we have the input representation we can now look at how this fits into the full network and I'm going to use 3 different examples to help illustrate it.

The first example I want to look at is the problem of predicting a home sales price.

So this would traditionally be done as a regression problem.

I'd like to optimize the square loss between the predicted price and the true sale price.

So the thing that I really would like to create an embedding layer for here are the words in the sale, the house description ad.

Because although there are a set of words, I really need to understand what words are similar in terms of figuring out the size of the house so I may say this is a spacious house or I may say it's roomy.

Those are words that are used that kind of capture the same thing and so I want to begin understanding how these words that real estate agents put in ads helps us understand something about the home.

So we have lots and lots of words that might be in an ad, and any given ad has 100 words or so, and so again we really do want the sparse embedding just like we talked about but my vocabulary is over words versus movies.

I'm going to learn a 3 dimensional embedding in this little toy example just so I can draw it, again in reality you'd probably want a lot more than 3 dimensions.

And I'm always in these examples going to draw my embedding layer as green, it's really a hidden layer, in this case 3 units because I want a 3 dimensional embedding.

I also may have other input data like the latitude, longitude, number of rooms and you can add all that, I just used latitude and longitude as an example.

And then in pink I'm showing the fact that we can have whatever other hidden layers we want, these are just your standard hidden layers, you can have as many as you want.

You can decide how many units and then at the end they'll go into a single unit that [unintelligible] the regression problem will give us a real value and will optimize the L2 loss with the sale price.

In the process of doing back propagation just like you've seen, the embedding layer will be learned.

As another example, suppose I want to learn to classify handwritten digits.

So I have the digits 0 to 9 and I have some training data where there's actually a label of the correct digit.

So here this sparse thing I want to create an embedding of is just the raw bitmap of the drawing, whether there's a white or black, so 0 or 1.

I can introduce whatever other features I'd like and again I have an embedding layer which I'll stick with keeping them 3 dimensions, so the representation of the digital will go into that.

In pink I show we can have whatever additional hidden layers and in this case we'll have a [unintelligible] layer.

We're gonna have the 10 digits and basically learn a probability distribution over the digits of how probable we think it is that this is each of the digits.

I can take the one hot target probability distribution from what I know the right answer is and optimize a soft max loss.

In the process of doing this, in training with back propagation, I will learn to embed the images.

And now let's look at the example we've been studying of collaborative filtering, the movie recommendation problem.

This is actually interesting, it brings up an aspect we haven't seen yet which is where is my training data here, right?

I just know for each user there is a set of movies, so how do I know what the right movie to recommend is? What am I going to use as the label?

What we do is, suppose the users watch 10 movies, we use a simple trick.

We'll randomly pick 3 movies and hold those out, take them away and those are the labels, so those are the movies I'd like to recommend, they're good recommendations because you watched them, and I'll take the other 7 movies and use them as my training data.

Once I've done that, this is very similar to what we just talked about with the character recognition.

I'll take the 7 movies that are my training data and we know how we can get the sparse representation, we'll bring them into the embedding layer.

We can take whatever other features we want, maybe the genre, maybe the director, whatever else we want to take about the movie or the user and then we can bring those into additional hidden layers and we'll have a logit layer.

And note this logit layer is big, instead of 10 different nodes like in the digit prediction, if I had a half million movies there's gonna be a half million of these.

There's issues with that, it's out of the scope of this discussion.

But we will get a distribution over those half million movies of what movies we think you'd like, we will then optimize the soft and max loss with the held out movies that we know you do like.

And in doing this in the back propagation and just the standard training, we will learn the embeddings of the movies like we talked about.

So I do want to come back now and just make sure it's clear how what we learned in the deep neural network ties to the geometric view I gave at the beginning.

Let's look at the deep network on the left and let's take a single movie.

Right if you think of the input layer, each of those nodes at the bottom represent as one of these half million movies, I've picked one movie and just made it black.

In this example I said I had 3 hidden units so I was going with 3 dimensional embedding.

So that black node will have an edge connecting it to each of those units; I used red for the first one, magenta for the second and brown for the third one.

When you're done training your neural network, those edges are weights, each edge has a real value associated with it, that's my embedding.

The red is my X value, the magenta is my Y value and the brown is the Z.

So this particular movie would be embedded in a 3 dimensional space as 0.9, 0.2 and 0.4.

As with any deep neural network there are hyperparamaters and one of the hyperparameters we have in the embedding layer is how many embedding dimensions, how many hidden units do you want in that layer?

Higher dimensions are good because it allows us to tease apart more distinctions and therefore we can learn better relationships.

On the downside, as I increase the number of dimensions there is also a chance of overfitting and it's going to lead to slower training and the need for more data.

So a good empirical rule of thumb is the number of dimensions to be roughly the fourth root of the size of my vocabulary, the number of possible values.

But this is just a rule of thumb and with all hyperparameters you really need to go use validation data and try it out for your problem and see what gives the best results.

An embedding can also just be thought of as a tool.

One of the things we get from these embeddings is we map items - movies, texts for example the words in the housing description - to these low dimensional real vectors in a way that similar items are nearby.

It creates structure into these items that really we didn't have any structure and the structure is in fact geared towards what you're trying to do with it.

We can also apply embeddings to dense data, for example if I look at the way audio or soundtracks are represnted, it's already dense.

But we don't have any meaningful metric, I don't know how to say this audio is similar to that.

And so we can use embeddings just to learn a similarity metric among already dense data, and even further we can embed diverse types of data - texts, images, audio - jointly and learn a similarity metric across them.

For more infomation >> Embeddings - Duration: 14:44.

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Classification - Duration: 7:26.

So we've talked a lot about regression.

But sometimes what we want to do with a machine learning model is make a classification.

Is it A or not A, is it spam or not spam, is the puppy cute or not cute?

Now we can use logistic regression as a foundation for classification, by taking our probability outputs and applying a fixed threshold to them.

For example, we might decide to mark something as spam if it exceeds a spam probability of 0.8.

That 0.8 is our classification threshold.

Now once we've chosen to make a classification threshold, how are we going to evaluate the quality of that model?

We need some new metrics, our regression metrics aren't sufficient.

One classic way of evaluating classification performance is to use accuracy.

And by accuracy we mean count all the things you got right and divide it by all the things that there were.

Basically what percentage of the things did you get correct.

Interestingly enough, even though accuracy is a very intuitive and widely used metric, it has some key flaws.

In particular, accuracy breaks down when we have class imbalance in our problems.

Imagine if we were to try and use accuracy to assess the quality of a model that is predicting ad click-through rates for display ads.

In display ads, our click-through rates are often 1 in 1,000, 1 in 10,000 or even lower.

So I might have a model that has absolutely no features in it except for a bias feature that tells it to predict false, always.

this predict false always model would have an accuracy of 99.999% in display ads predictions, but would add absolutely no value.

Clearly accuracy is doing something wrong here.

So to deal with class imbalance problems, we need a more fine grained way of looking at the way that our models predict onto positives and negatives or different classes.

So we can think about these different kinds of successes and different kinds of failures along a 2x2 grid that has true positives, false positives, false negatives and true negatives.

To help us understand these, let's remember the story of the little boy who cried wolf.

Now this little boy is a shepherd, a wolf comes to town, if he correctly spots the wolf that's a true positive.

He sees the wolf, he says "wolf", true positive saves the town, good job.

Now a false positive is when that little boy says "wolf" but there really wasn't a wolf.

That is a false positive, it makes everybody annoyed.

A false negative may be even worse.

A false negative - there was a wolf coming along and the little boy was asleep or didn't see it and the wolf went in and ate all the chickens.

That's really no good at all.

A true negative is when the boy did not cry wolf and indeed there was no wolf, everything's fine.

So we can combine these ideas into a couple of different metrics.

One of them is precision which is when the little boy said "wolf", how many times was he right?

How precisely was he able to say "wolf"?

Recall on the other hand is of all of the wolves that tried to come into the village, how many did we get?

Now what's interesting is that these things are often in a little bit of tension.

Because if you imagine that you want to do a better job at recall, the right thing to do is to be more and more aggressive about saying "wolf" even when you just hear a little noise off in the bushes.

So we can think of that as lowering our classification threshold.

But if we want to be really precise, the right thing to do is to only say "wolf" when we're absolutely sure so we might think of that as raising our classification threshold.

So these two metrics are often in tension and doing well at both of them is important.

It also means that whenever someone tells you what the precision value is, you need to also ask about the recall value before you can say anything about how good the model is.

Now precision and recall are both well defined when there is one specific classification threshold that we've chosen.

But we might not know in advance what the best classification threshold is going to be and we still want to know if our model is doing a good job.

Well, a reasonable thing we could do would be to try and evaluate our model across many different possible classification thresholds.

And in fact we have a metric that looks at the performance of our model across all possible classification thresholds.

And this is called an ROC curve, Receiver Operating Characteristics curve.

And the idea is that we evaluate every possible classification threshold and look at the true positive and false positive rates at that threshold.

We then draw a little curve that connects those dots and the area under that curve has an interesting probabilistic interpretation.

It goes like this:

If I were to pick a random positive example, closing my eyes I pick one out of our distribution, and I pick a random negative example, what is the probability that my model will correctly assign a higher score to the positive than it does to the negative?

In a sense, what's the probability it gets that little pairwise order incorrect?

Turns out that that probability is exactly equal to the probability value of the area under the ROC curve.

So if I see a value of 0.9 area under ROC, that's the probability that I'll get that pairwise comparison correct.

One last measure to think about is prediction bias.

Now prediction bias is defined by taking the sum of all of the things that we predict and comparing them to the sum of all the things we observe.

Basically we would like the expected values that we predict to be equal to the observed values.

If they're not, we say that the model has some bias.

A bias of 0 would show that the sum of the predictions equals the sum of the observations.

Now bias is a very simplistic metric in that it's easy to fool.

We could have a model that has almost no value to it, it just predicts the mean of all the class probabilities to create a zero bias model.

However, it's a useful canary.

Because if one of our more complicated models does not have zero bias, it means that something is going on.

It gives us something to dig into as a way to debug our models.

So if our model does not have zero bias it's definitely cause for concern and allows us to maybe slice the data and see what areas the model is not doing a good job of having zero bias on.

However just having zero bias by itself is not an indicator that the model is perfect, we need to keep looking at other metrics for that.

We can look at more fine grained use of bias by looking at a calibration plot.

With the calibration plot, what we do is we take groups of data, we bucket them up and look at the mean prediction versus the mean observation for things in that bucket.

Obviously we do need to have buckets of data to make calibration be meaningful.

For example if I'm looking at flipping a coin, any given coin flip will either come up exactly heads or exactly tails, basically exactly 1 or exactly 0.

But my probabilistic predictions will be 0.5 or 0.3 or some value in between 0 and 1.

So it only makes sense to compare those mean predictions to mean observations if I aggregate across a sufficiently large number of them.

For more infomation >> Classification - Duration: 7:26.

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Training Neural Nets - Duration: 2:54.

So when we think about how to train neural networks, what do you need to know about, say, back propagation?

One thing you don't need to know about back prop is how to implement it.

That's one of the brilliant things that TensorFlow does for us, is it takes the internals of back propagation and does that all for us underneath the hood.

But there are some important things to know.

The first is that back prop really does rely on this idea of gradience, things needs to be differentiable for us to be able to learn on them.

One or two small discontinuities in our various functions are fine, but in general we need differentiable functions to be able to learn with neural nets.

Other things that gradients can vanish.

If our networks get too deep, so if signal to noise ratios get bad as you go further and further down the model and learning can really become quite slow.

Ray lou's can be useful there; there are also some other strategies that we won't talk about in this class.

But in general you do want to think about limiting the depth of your model to sort of the minimum effective depth if you can.

It's also important to know that gradients can explode; if our learning rates are too high, we get these sort of crazy instabilities, we can get NaNs in our model.

The thing to do there is to try again with a lower learning rate.

Last thing to know is that ray lous can die.

It's possible that because we have this hard cap at zero, if we end up with everything below that value of zero there's no way for gradients to get propagated back through and we'll never be able to pull ourselves back up into the land of living ray lou layers.

So keep an eye out for those and again try again with a different initialization or a lower learning rate.

At training time, it's often very useful for us to have normalized feature values when they come in.

If things are on roughly the same scale, this can help speed the conversions of neural nets.

So the exact value of the scale doesn't really matter; we often recommend negative one to plus one as an approximate range.

It could minus five to plus five, or zero to one, it doesn't really matter so long as all of our inputs are on roughly the same scale.

Finally, one last trick that's useful in training deep networks is the idea of an additional form of regularization that is called dropout.

And dropout is kind of a funny idea.

When we apply dropout, what we're saying is that with probability P we take a node and we essentially remove it from the network for a single gradient step.

On different gradient steps, we repeat and we'll take different nodes to drop out randomly.

So the more you dropout, the stronger regularization you have.

And you can kind of see this clearly where if you drop everything out you have an extremely simple model that is essentially useless.

If you drop out nothing, you allow the model to have its full complexity and if you have dropout somewhere in the middle, you're applying some sort of useful regularization there.

Dropout is one of the key advances that has enabled a number of the strong results that we've gotten recently that has pushed deep learning to the forefront.

For more infomation >> Training Neural Nets - Duration: 2:54.

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School Suspends Vaccination Program After Reports Of Unauthorized Immunizations - Duration: 5:38.

A Florida school board has suspended, it's on campus vaccination program following the

reports that several students receive flu shots without parental consent.

Joining me to talk about this is RT correspondent Brigida Santos.

Brigida, what can you tell me about this story?

Let's begin with the facts behind the story and then just kind of kinda drill into it

a little bit.

Well, several students at Jay Elementary School in Santa Rosa County reportedly received flu

shots without permission from their parents.

And in fact, some parents reported that the shots were actually administered outright

against their wishes.

A mother named April Burgess said she signed the school's consent form, but wrote on it,

quote no flu shot.

She also said she purposely left the yes box unchecked where it had asked whether her child

should receive the flu shot.

Now, when she asked Healthy Schools Inc., which is the company that runs the on-campus

program why this happened, she was told that she had consented just by simply turning in

the form.

How has the school tried to respond to parent's complaints?

That's gonna be part of the story, isn't it?

The part of the story is there's been parent complaints, there's a lot of material out

there about the vaccines, whether it's accurate or not, a parent should have the right to

make those kinds of decisions for their child.

Of course on the other side, they say no, that's really not fair because your child

is in school with my child, and if that child has the Mumps and passes it on to my child,

I'm not happy about that.

What's your response to how has school has dealt with parents on this issue?

They've suspended the program until they can ensure that the vaccination process meets

their standards.

Although it's really unclear what exactly those standards are, because there was reportedly

very little to no oversight.

And, a statement from the school superintendent says Santa Rosa district schools was not involved

in the planning or advancement of the flu vaccinations, nor did we administer any communication

of approval with parents about the vaccines.

And yet the vaccines did take place on campus.

Jay Elementary is now placing the blame on the Santa Rosa health department, which sponsors

the Healthy Schools student vaccination program.

So it's very odd that they didn't seem to know what was going on here.

No surprise there.

How is the Healthy Schools Incorporated, how have they responded to the incident?

As I look at the story, actually there's more than two sides to it.

But you have these sides that are looking at the vaccination issue.

Now you're hearing it tied into Autism.

We're not here to determine whether that's accurate or not.

There are plenty of people who believe it is.

Plenty of people thinks it's crazy science, but in between what we're finding, whether

or not you're moved on either side by this, is you have the industry hard at work trying

to shore up the criticism of the immunization process.

And I guess Schools Incorporated is caught in the middle of it.

How are they responding to the incident?

So a company spokesperson confirmed the reports and has released the following statement;

"The moment we became aware there was an issue, we immediately took steps to isolate

and correct the problem.

All consent forms are now being quadruple checked during the data entry process before

each clinic, and since we've added these additional measures there have been no other issues.

The company is also apologize to the parents and told them that their children are at no

medical risk despite having these vaccinations without permission".

Okay.

Yeah.

But it's one thing to be told that, but there are plenty of parents ... I've had to follow

this literature very, very closely.

I've actually been asked to get involved in litigation.

I'm not there yet.

I'm not at the point to where I'm going to jump into the litigation because now, the

latest is that there's a Rico case that's been brought in Georgia and it's kind of interesting

in that it actually includes the Federal government in a lot of different ways.

And so I'm looking at this thing and I'm saying okay, is it reasonable for a parent to say,

I'm not sure, therefore I don't want to do it.

And it seems that this story, if I follow this story that whether it was intentional

or not, the parents been taken out of the process, that leaves the Schools Incorporated,

really leave them kind of exposed.

And, if this does pick up, if this Rico case for example were to prevail, and we were to

see that the Federal government actually was involved in this process with the immunization

industry, there could be a problem here for the people that are not at least granting

the parent's wishes if something ends up happening to the child.

If Autism is subsequent to that, whatever it may be, the parent than raises that in

the future.

So, schools really better pay attention to this.

I'm wondering, is there a federal requirement for am immune, tell me about it.

The federal requirement for child immunization.

Okay, so there's no federal vaccination law, however, all states require school children

to be vaccinated against certain communicable diseases.

Right.

Which usually include Measles, Mumps, Rubella, Hepatitis B and Chicken pox, but not the flu,

so parents in this case have a right to be upset.

A vaccination is a medical intervention and yes, vaccines do work but again, the parents

should be allowed to have a say whether their child gets or doesn't get the flu shot.

And also, what if some kids already had the flu shot and then they got another flu shot.

It doesn't seem like that would be a good move either.

Brigida, thanks a lot.

Let's follow this story some more 'cause in the end it should be the parents that have

a right to make decisions like this if it's based on any kind of inclination of science

at all.

Thanks for joining me.

For more infomation >> School Suspends Vaccination Program After Reports Of Unauthorized Immunizations - Duration: 5:38.

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Multi-Class Neural Nets - Duration: 3:43.

So up until now, we've talked about classification for binary class problems.

Is something spam or not spam? Is the puppy cute or not cute?

And logistic regression, with a classification threshold, is very well-suited to these sorts of binary class classification problems.

But in the real world, we're often not choosing just between two classes, sometimes we need to pick a label out of one of a range of classes.

For example, is the object animal, vegetable, mineral or man made object?

Is the color red, orange, green, blue, indigo or violet?

Do we have a picture of an apple, a car, a banana, a dog, blah blah blah.

There's lots of areas where being able to do good multi-class classification is a useful thing.

Now, interestingly enough, we can build off of some of the technology that we already have with binary class classification.

One classic way of doing this is through the one versus all multi-class classification.

So essentially what we do is we have one logistic regression output node in our model for every possible class.

So one node might identify "is this an apple?" Yes/No. Another might say "is this a picture of a bear?" Yes/No.

A third might say "is this candy?", yes or no. And we have one output node for every possible class that we're looking at.

We can do this in a deep network by having different output nodes at the outset of the model and share the internal representation through the rest of the model so these can be trained reasonably efficiently together.

In some problems we know that an example will belong to only one class at a time.

For example, a given fruit is either a banana or a pear or an apple.

In this case, we'd like the sum of the probabilities of all of our little output nodes to sum to exactly one and this can be achieved by using something called Softmax.

Softmax is essentially a generalization of the same logistic regression that we used, but generalized to more than one class.

When we have a single label, multi-class classification problem we use Softmax.

This encodes some helpful structure to the problem and allows us to use those outputs as well-calibrated probabilities.

In other cases we might have a multi-label classification problem.

For example, an image might contain both an apple and a banana in it.

Or it might contain three different dogs, or a dog and a person and we'd want to be able to identify all of those different labels in the same example.

And in that case we do need to use a one versus all classification strategy, where each output is computed independently and the outputs do not all necessarily sum to one.

When we're training a multi-class classification, we've got a couple of options here.

We can use full Softmax, just straight out of the box and this is relatively expensive to train.

You can think if you have a million classes then you essentially needed to train a million output nodes for every single example.

Now it's possible that if you're trying to disambiguate between the dog being a labrador and a poodle, that knowing that it's not a toaster is actually quite an easy thing.

And so we can a little bit more efficient there by doing something called candidate sampling, where we train the output nodes for the class that it belongs to and then we take a sample of the negative classes and only update a sample of the output nodes.

This is quite a bit more efficient at training time, it doesn't seem to hurt performance very much in a lot of cases; obviously at inference time we still need to evaluate every single output node.

For more infomation >> Multi-Class Neural Nets - Duration: 3:43.

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The History of Red Dead Redemption & Beta Version - Duration: 34:27.

What's up, people?

Here we are with a new episode of Hot Topic focusing on something a bit different from the usual.

I'm Gary7 MT for the GTA Series Videos crew and in honor of the upcoming release of Red Dead Redemption 2,

we're delving deep into the red dead series' history.

From its birth to the key of its success and, of course, we'll try to analyze the beta and removed content from the two already released titles of the series,

Red Dead Revolver and Red Dead Redemption.

Before going into the details, thanks are in order to Monokoma, Firex and all the users and staff members at Unseen64.net,

MobyGames.com, TheCuttingRoomFloor, GTAForums, RedDeadForums, Reddit and the Red Dead Wiki.

It's thanks to them and their passion that we're able to prove theories,

locate the right sources and even find new things we're able to show you.

Here you go.

Looks like you still got some business with them brothers.

They ain't what you call kindly fellows.

Open the damn door, woman!

Rockstar San Diego are the creators of Red Dead but before they were known as such,

the California studio was known as Angel Studios founded by Colombian artist Diego Angel in 1984.

The company originally produced 3D work for various media, the first of which was a volcano animation for Scientology's Dianetics.

Dianetics by L. Ron Hubbard.

Still, the studio's 3D effects are best known from films like "The Lawnmower Man"

and music videos like Peter Gabriel's song "Kiss that Frog".

Angel Studios shifted its focus toward the video game industry only in the 90's,

joining a group of companies that would develop video games for the Nintendo 64 console.

From 1996 to 2000, Angel Studios both ported and developed games for Sega, Nintendo, Microsoft and Capcom

- titles like "MR. Bones",

"Midtown Madness" and "Resident Evil 2".

Capcom offered Angel Studios an opportunity to create something entirely new,

following the acclaimed success of Resident Evil 2's porting.

The title's codename was "SWAT" and Angel Studios first envisioned the project

as a single player split-screen title where you controlled a 4-man SWAT team.

This title's premise was quite similar to hired guns,

an Amiga game developed by the GTA Series' original developer "DMA Design", known today as Rockstar North.

Capcom video game designer from 1984 to 2003, Yoshiki Okamoto, author of another western title, Gun.Smoke,

was put in charge of the angel studios project.

His personal fixation with the genre in general and one Western movie in particular called "Blindman"

with the one and only Ringo Starr, believe it or not, changed the project entirely.

SWAT ceased to be the game's title, but rather became a codename for Spaghetti Western Action Title.

And this is where the history of Red Dead Revolver began.

Capcom and Angel Studios announced the game and showed it to the public during a few events using images and videos.

What was shown was heavily programmed and not actual gameplay because,

due to the troubled development, the game was unplayable.

Chris Bratt's YouTube show, "People Make Games", exposed more about the initial concept and status of the title

thanks to Dominic Craig, one of Red Dead Revolver's Lead Designers.

In his opinion the game wasn't fun because the shooting mechanics were weird:

partially inspired by Japanese action games and partially by "Panzer Dragoon" and "Tenchu: Stealth Assassins"

- with the latter being the very first stealth game ever produced.

Capcom not only financed the project during the first years, but like we said,

also sent some of their developers and lead artists to California.

With Okamoto as project leader,

while Akiman designed all the characters in the game using the developers as models.

Because of Bratt's video we learned that the character of Pig Josh was based on Lead Designer Josh Needleman-Carlton,

Mr. Kelly was based on Michael Kelly the Lead Engineer

while Perry shared not only the name but likeness, of Particle Artist Chris Perry.

The liaison between Angel Studios and Rockstar Games began in 2000.

This was when Angel Studios developed and released under the Rockstar label, Midnight Club: Street Racing,

Smuggler's Run and Smuggler's Run 2.

On November 20th, 2002, Take-Two interactive announced that it had acquired Angel Studios

for a combined cash and stock value of 34.7 million dollars.

By the end of 2002, Capcom had already been funding the project for three years

and started getting cold feet culminating with their complete backing out of it after Take-Two's acquisition.

Unlike many corporate buyouts, for Capcom, that acquisition was far from bad news

- this is because at the time the Japanese publisher was already courting Take-Two and Rockstar Games

to obtain the rights to publish the Grand Theft Auto series in Japan.

In June 2003, the deal was finally sealed and Rockstar Games announced a partnership agreement with Capcom

to localize, publish and distribute the blockbuster title GTA 3 for PS2 and PC in Japan.

Following their purchase, Angel Studios was renamed Rockstar San Diego

and Rockstar Games executives reviewed the studio's projects in development to sort out what was worth keeping.

Dan and Sam Houser once remarked that one project that always caught their eye was "a cowboy game that looked very good."

"For the time it looked visually spectacular, but speaking to the management guys there,

it was a complete mess.

It didn't really exist yet as a game." according to Dan Houser.

"Capcom were prepared to walk away from the project,

so we said we'd finish it and all they ever wanted was the rights to publish it in Japan

if we ever did finish it - which they never thought it could be."

Despite being unplayable, Rockstar Games started work on the game

after sending the Capcom designers home and taking over the development.

They salvaged whatever good they found and scrapped almost everything else.

The original version was more like a classic arcade "on rails" shooter with fast paced gameplay,

while the final version ended up being more an action-adventure title with a bit of free-roam in the levels

and a definitely slower but more rewarding gameplay.

According to Dominic Craig, the controls were the first thing redone with a more robust cover system,

but the narrative remained the game's primary flaw.

At that time Rockstar were more narrative developers,

while Capcom's interest focused more on gameplay.

What they ended up doing was stealing from Western movies from the 60's and 70's, environments and characters,

and blending them all together into the story of a bounty hunter seeking revenge on his parents killers.

Again thanks to the "People Make Games" episode, we now know

that the game's narrative was originally heavily inspired by the film, "High Plains Drifter"

in which Clint Eastwood reprises a role similar to the one from Leone's Dollar Trilogy.

Go ahead.

Thus the story is of a mysterious cowboy seeking vengeance on behalf of a murdered man.

Now while implied, it is never confirmed that this cowboy is in fact

the same man back from the grave.

In the first draft of the story, Red was supposed to die with the rest of his family at the very beginning of the game

and return from the beyond to satisfy his own personal vendetta.

Red's name was supposed to be "Red Hand" due to his burned hand being wrapped in a red bandana,

which would serve as an identifying mark to fear.

Not just those responsible for his family's death but all outlaws as well.

From the original idea to what we got at the end, technically speaking, the game was scrapped and rebuilt,

surely using the same assets, but with different visuals, graphic style,

HUD, animations and more.

Various things in the original title have been completely dropped by the way.

Starting from a snowy level,

and more frequent use of the horse.

Jack's Dead-Eye ability in the final game was originally Red's ability

- and maybe even the power-ups were all available to Red

after reaching specific criteria like any arcade game.

The multiplayer was already part of the game, but we lost some special abilities, like flying.

Still from "People Make Games", Dominic Craig also talked about the train chapter of Red Dead Revolver.

He explains that Capcom's original level was like a Mario title with a big heart shaped coach

and a princess character in it with armed enemies with Gatling Guns shooting at you

as you rode by on your horse.

Thanks to the original trailers, some of the differences between the Capcom version and the final version are made manifest.

Other than these videos, not much is left from the beta version of Red Dead Revolver, except a logo,

artwork and some images - and while we're on the artwork tip, here's some trivia from Bratt's video.

Red Harlow's face in the game's cover art was apparently inspired by Owen Wilson's screaming face

from the 2000 film "Shanghai Noon's" poster the developers just happened to have hanging on the office walls.

Wow.

Despite the enthusiasm and effort that went into developing it,

not everybody had faith in Red Dead Revolver.

According to a rumor shared by Chris Bratt, Rockstar's idea was to publish the game under the "Global Star Software" label,

Take-Two's low-budget publisher for second-tier titles.

The point was to avoid the game being released as a "Rockstar title".

Due to favorable reviews and almost a million copies sold between PlayStation 2 and the original Xbox,

very little time passed between the release of Red Dead Revolver and the first glimpse at a sequel.

Originally, Red Dead Redemption was to be a direct sequel of the first game being named "Red Dead Revolver 2".

We can see that Red and John somehow share the same facial scars.

According to Dominic Craig, originally the plot for Red Dead Redemption was meant to center around Red's son,

with the boy being angry at his father who's been a wanted man ever since he killed the governor.

After he obtains some semblance of a normal, happy, life,

of course the bad guys show up and shoot that all to hell.

At that point the protagonist starts his revenge mission - to find his dad again.

Craig's idea was more a "Once Upon a Time in the West" sort of story.

He wanted an action title that felt like a "Spaghetti Western ",

while Rockstar's vision was more "The Wild Bunch"

- a tale of wanted criminals from a time that unbeknownst to them, has already passed.

We're gonna stick together, just like it used to be!

When you side with a man, you stay with him, and if you can't do that, you're like some animal. You're finished!

We're finished. All of us!

The very first time Rockstar showed Red Dead Redemption was in 2005

with this brief teaser at the Sony E3 press conference

- which was really more of a tech demo that showcased the lighting effects and new graphics.

After this teaser, four more years passed without news, screenshots or videos

until the game was officially announced on February 3rd, 2009 with its Red Dead Redemption moniker.

With over 15 million units sold as of February 2017, and an average score of 95% from world reviewers,

Red Dead Redemption is universally acclaimed as one of the greatest games for both PlayStation 3 and Xbox 360.

Like its predecessor, the game was never released for PC - and according to leaked documents,

ex-developer statements and more, a troubled development is something that also marked Red Dead Redemption.

Built in different compartments it used at least three or more different versions of the RAGE engine

forcing the developers to create new tools for compatibility and more.

But we're not interested in technical rabble but the leftover goodies, so let's get to it.

Let's start with the game's logo.

Thanks to Aaron Rix, Rockstar San Diego's ex graphic designer, we do have some concept logos for Red Dead Redemption

before the final version made the cut.

We also have some digital compositions with illustrations by George Davis

featuring in-game items like the special rosary given by a nun after reaching the maximum honor,

the 2D design of the promotional playing cards and some in-game graphic designs of stores,

journals, signs, posters and more for the game's world.

In Steve Hartman's portfolio, a 3D artist for Rockstar New England - formerly Mad Doc Software

- we can see building images in the game clearly taken using internal tools to manage camera position.

All these buildings look like finals

- even the on-screen radar's identical to the one used by Rockstar in the final build of the game.

On Sinclair's YouTube channel instead we see a small clip of the gate exploding in Cochinay

- the clip shows the model of the area and the explosion without any effects or texture applied.

Meanwhile a beta radar appears in images from Jason Muck's portfolio.

He was the sole Senior Environment Artist specializing in vehicles, props, and weapons for Red Dead Redemption.

This radar was bulky, and lacked any transparency effects whatsoever.

The icons were way different too with the poker table marked always with the ace of spades card,

the nearest safehouse with a classic house icon and the stagecoach with the wheel of a cart.

Other icons were a pitchfork in a green circle, a silver circle inside a red circle

and a big black circle inside another red circle.

What all these icons are supposed to stand for, we have no idea.

On another shot the radar is more familiar

- the only difference is the color of the stamina bar being dark blue, instead of light blue.

On another screen we see an unknown icon showing a golden bull skull - maybe indicating cattle

- and two other rounded ones with a B and F inside - the first one's for Bonnie or Seth Briars,

while the F may be for Luisa Fortuna or some cut character.

What's interesting is that there's no way to have a pending mission in the game for Bonnie or Seth

while also having one for Luisa.

Another noteworthy point is, on the radar we can still see placed on the shore a white and a red icon

mimicking either the wheel of a stagecoach or steamboat.

These icons could mark the docks where the player would be allowed to use the steamboats

or even dock rafts, canoes and other boats.

Thanks to Muck's portfolio we can see the general style of the game at this point in its development was completely different,

a more classic western, than a gritty, violent one.

The High Power Pistol didn't have the engravings or the handle in mother-of-pearl and apparently,

the rifle was attached directly to the bandolier, not shoulder strap.

Thanks to promotional images, videos, and files from inside the game,

we can see a younger or at least less detailed John with a slightly slimmer face,

Abraham Reyes' hair was slightly shorter and he was sporting a goatee without the big mustache.

Allende's facial hairs were different too and the character was supposed to be definitely fatter

according to the very first artwork.

Ah, perhaps I should tie you to a horse and let it drag you around town,

or let the dogs fight you, huh.

Thanks to pre-release sketches by Hethe Srodava, former Rockstar Senior Concept Artist,

we can see how Luisa Fortuna has slightly changed - the starting points to the final design.

And a recent sketch of John Marston - recent because the original concepts are all in Rockstar's hands.

Except for drawings of the main character, the artist had chances to share more of his work,

like this one depicting the first rendition of the Treasure Hunters gang

- or maybe originally they were part of a grave robbing gang opposed to Seth.

We can also see various images of NPCs and side characters that made it into the final game

- some in Red Dead Redemption, others in Undead Nightmare.

Some are unchanged, others instead are very different, like the Sasquatch shown in this sketch

and six other possible variants of the creature in this one - perhaps this indicates six choices that had to be narrowed down

or that the idea was to make all six sasquatches that you have to kill in the game somehow unique.

We eat berries and mushrooms, you fool.

Or we did. Now, none of us are left.

Some maniac's been murdering us.

Various other characters had a different voice actor or simply a different accent all together.

Nobody needs to kill anyone Bill.

You do so love to talk in riddles, Mr. Marston.

You do so love to talk in riddles, Mr. Marston.

The Elegant Suit lacked the hat according to artwork and an official screenshot.

I hate to take money from a lady, miss.

While the US Marshal Uniform was more a Sheriff Uniform

- the original badge was shaped like a Sheriff's.

Targeting changed a bit.

The original reticle resembled the GTA 4 version with the health segments inside

- this feature was cut from the single player, but it's still available in multiplayer.

The Dead Eye reticle was also different, just like the marks set over the enemies during this ability's use.

And while we're still on weapons, if we take a look at the weapons wheel shown in the gameplay trailer reveal of Red Dead Redemption

we see originally there were only six of the eight weapons slots:

pistols, lasso, shotguns, rifles, sniper rifles and the knife.

The two missing are the fist and throwing items that in the original concept

could totally be placed as a sub-selection of the one showing the knife.

Speaking of differences - without delving again into the various steps of the minimap

- we can see that originally while wanted, the amount of the bounty and the last committed crime

was shown in the top right of the screen with the word "Wanted"

- and yes, there's also the black background missing.

The honor bar was smaller and without the various segments indicating the grade of Marston's honor.

Money owned was simply placed on the left middle of the screen.

The inventory was totally different with all icons inside a red border.

Now let's analyze other beta aspects of Red Dead thanks to this shot

from this gameplay reveal of Red Dead Redemption from 2009.

Without considering the developer's annotation on the selling page,

we can see here how things were a bit different in this build of the game.

The "Basic Campsite" for example, despite being placed in Kit, was a Consumable

considering the "x2" written on the icon, meaning that while the player could always use the improved camp-site,

the basic site could run out of resources and needed to be purchased at stores like ammo to be used again.

We can also see other things used in the final game

like the Pleasance Deed for the Stranger mission "Water and Honesty", the Nosalida package from "Poppycock"

and the "Letter from Sam" obtainable in the last encounter of the mission "California".

If not tied to a removed Stranger mission to be discussed later,

the Sacred Relic could be the first rendition of the Rosary given by the nun in the game after reaching the maximum honor.

The treasure box is still a mystery.

Maybe it's the original reward for the Treasure Hunter Challenge or something completely different.

One more departure from the final version of the game is that the player was supposed to be able to buy not only a bandolier,

but a double bandolier as well.

Another leftover from GTA 4 was the original icon marking the location to start missions.

The Cheats option was originally shown directly in the main menu, not under the Options menu

and the font used for the subtitles was different, more similar to the one already used in GTA 4.

Considering the E3 2005 teaser trailer for a possible comparison,

we can see that the small town shown at the end of the video is similar to Armadillo from the final build,

only smaller and with slightly different building models.

Also, at some point in the development, there were no buildings at the end of Armadillo.

The MacFarlane's Ranch was originally named McFarling's Ranch

with Bonnie MacFarlane named after the aunt of former Rockstar San Diego Designer, Rob Hanson.

Bonnie MacFarlane. Miss, Bonnie MacFarlane.

This is unconfirmed though, as the only source we have is from the Wiki pages.

The Chuparosa bank is apparently impenetrable in the game, but according to a couple of pictures,

we were supposed to be able to rob it - maybe during a cut mission given by someone.

Another difference we do have proof of, is that at some point during development,

the top of the Nekoti Rock, in Tall Trees, wasn't covered in snow.

Thanks to a trainer, we can also navigate way over the natural borders created by Rockstar

and see that the map, despite not being heavily detailed, stretches far beyond what can even be seen in the game.

Originally, the player would be able to hunt and skin bats, but then they were removed

and left only as scripted atmospheric events.

Just like the bats, the 3D model of the Sasquatch was already in files of Red Dead Redemption

- both creatures ended up being added in the DLC "Undead Nightmare".

While the first creature was even shown in an official image of the game,

it's unlikely that the Bigfoot was to be present in Red Dead Redemption.

Maybe as an Easter Egg or a very rare event just to freak out the players, who knows?

There were originally more bounties to collect - five more members of Dutch's Gang,

four unknown outlaws and a Mexican.

There were originally also wanted posters for both John Marston and Abraham Reyes.

Likewise, in Undead Nightmare there was supposed to be another missing person, Lloyd Duffy,

but it's unknown why Rockstar chose to get rid of him.

Next to nothing is known about beta or removed story missions

- probably due to the lack of analysis and decryption tools for the game.

Thanks to videos and images from Rockstar we are able to uncover some differences between the missions we played

and how these missions were supposed to be.

In "Spare the Rod, Spoil the Bandit", the player was supposed to be able to reach the balcony on the second floor

from outside and shoot at the enemies with the hostages inside the house.

The mission "Father Abraham" originally intended the player to throw dynamite at the Mexican army convoy,

not rig it on the road and later blow it with a detonator.

Do it now!

Lastly, the showdown with the Mexican army during the mission "Cowards Die Many Times" was way different.

The army was supposed to enter and take position on various vantage points inside the town of Chuparosa, as seen here.

It could also be that originally the mission wasn't tied to De Santa at all, but only to Reyes.

But there's not always a video or image left and such is the case in the mission with Norra Hawkins.

According to Wiki, Norra was a woman in Great Plains that once encountered,

would call Marston for help in retrieving her stranded dog.

Wiki further claims that in the final version of Red Dead Redemption, as soon as Norra spawns,

the game kills her to prevent the mission from starting,

but said through modding it was possible to still play this mission.

Unfortunately, none of this seems to be true: there are no images or videos of the lady or her mission.

We even delve through the files searching for her 3D model, her name or anything else in the subtitles

and mission objectives, pertaining to her but nothing surfaced.

Thus the process of killing her to avoid the player starting the mission seems far-fetched.

Modding permits us to play with items that aren't supposed to be obtainable,

like the Undead Horse that turned out to just be a prop for a specific mission.

Then to drive an automobile - a totally cool thing to do,

even possible in multiplayer now that the game has become an actual lawless wild west for modders.

Some things that can't be reinstated in the game through modding are the Stranger missions

"Mother Superior" and "The Dwarf and the Giant".

Of these missions, all we have left are some audio files.

Mother superior wants Marston to find four stolen relics - and as said before,

one of these relics could be the one shown by Rockstar in the Kit menu inside the gameplay reveal of Red Dead Redemption.

The other stranger mission starts with Marston meeting a lonely dwarf

where he agrees to find a friend for him.

He first reaches a drunken man who directs him to a giant who supposedly lives in the hills.

Once found, the giant greets Marston with hostility and John is forced to fight him to calm it down.

After the fight the giant agrees to meet the dwarf,

but they don't get along and with no better explanations, the giant ends up accidentally killing a girl.

The murder upsets the dwarf who directs Marston to kill the giant,

but the player is given the choice to whether kill him or not.

It's not unusual for developers to reuse cut content in new games or new iterations of a video game series,

but in Rockstar's case, with Red Dead Redemption 2, this is highly unlikely

- even with their new habit of recycling old content into new the way they've done in GTA Online.

Despite that, surely Red Dead Redemption 2 will have its own removed and beta content,

some of which will be revealed thanks to pre-release screenshots and videos,

and then in the future through in game files - hopefully using a PC version of the game.

And that pretty much wraps this episode of Hot Topic.

Of course more will be discovered in the future

and we hope this video will encourage you guys to search and find more info.

Soon Red Dead Redemption 2 will be in our hands and we'll be able to play and enjoy a new adventure

with new and old characters that will accompany us to a western world of outlaws and criminals.

And when it does, we'll do a full examination of the game with walkthroughs, graphic comparisons,

Easter Egg videos and much more, so be sure to watch this channel for all the coming updates about Red Dead Redemption 2,

Grand Theft Auto Online and other Rockstar titles.

Keep following us on Twitter, Facebook and Instagram

or jump in our Discord server to holla at other fans of Rockstar Games.

From GTA Series Videos, this was Gary7 MT.

Peace.

For more infomation >> The History of Red Dead Redemption & Beta Version - Duration: 34:27.

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Kumquat Essential Oil | Benefits of Kumquat Oil | Uses for Kumquat Oil - Duration: 3:25.

today we're going to talk about kumquat oil or fortunella japonica this is

grown of Asia it's been an ornamental tree in a lot of their gardens for many

many years it's also added to some of their teas or tea ceremonies it smells

really good it like like a citrus oil but a little bit of a softer one leave

me a comment below what do you think that smells like well what do you think

of the smell. Kumquat has a lot of really great benefits anti-inflammatory

antibacterial it improves your mood it helps with digestion they just you know

what I mean there's a couple of studies that I found one is a pubmed article

this article found that fortunella Japonica was effective against most

pathnogenic bacteria and yeast on skin so it turns out that this is really

great fair skin and even found that this was effective against antibiotic

resistant bacteria so it's helping fight superbugs in some laboratory tests right

now love that that's happening I love that they're testing for this only that

pubmed article below there's another article in the altmed journal that tests

this and sense of it is effective in helping peristalsis so helping your bait

justice system function normally it reduces heartburn because of its gastric

acid so helping your whole digestive system that is a definite bonus another

article said that it is also providing chemo protective activity in several

types of cancers in animals right now they haven't done any tests on humans

but that's what's going on or as far as the research

, for animals so that's all really exciting like exciting superbugs it's

helping with apoptosis it's doing a lot of really great things for your

digestive system wonderful for your skin so how do you use it add it to vinegar

and add it use it in your household cleaner right that's like a super simple

way add it to baking soda and use that to scrub down your bathtub or your sink

in your bathrooms and kitchens second lady is that third way to use it

diffuse it to reduce airborne pathogens and by doing so you're also gonna end up

with an elevated mood fourthly put a drop in your hand and just breathe it in

really deep it'll help energize you MIT Dame's to the grabbing not copying fifth

way to use it add a drop to your shampoo or your

facial moisturizer and it will use it in your facial moisturizer at night when

you're not going to go out in the Sun for 12 hours and it will help energize

your skin and your hair this is a photosensitive oil so you want to make

sure you stay out of the Sun for 12 hours if you're applying it topically or

apply it in a place that is not going to see the Sun for 12 hours

like the bottoms of your feet or you know behind ears something like that so

that's it I hope this video was helpful

if you thought this video was helpful give me a thumbs up below thank you so

much for watching don't forget to subscribe I'll see you in the next video

For more infomation >> Kumquat Essential Oil | Benefits of Kumquat Oil | Uses for Kumquat Oil - Duration: 3:25.

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Library System - Duration: 0:57.

Do you enjoy books, movies, technology and learning?

If so, then we have a place for you.

There are seven public libraries in Cumberland County and residents can join at no cost.

Who needs two-day shipping when you can get thousands of titles for free!

We also have music, movies, and books you can download from home.

Place requests online and use our self checkouts and automated phone and web renewal.

Looking for answers?

Get them from our authoritative sources using our online databases.

Attend concerts, book talks, gaming events and classes in a multi-generational setting.

Or become a library volunteer!

Whether you are looking for social interaction, free WiFi, or a quiet place to relax start

with the Cumberland County libraries and you can go anywhere.

For more infomation >> Library System - Duration: 0:57.

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Boat Buyers Guide: What CE Certification Means for Boat Owners | BoatUS - Duration: 3:05.

Hey there, folks. Lenny Rudow here for Boat US Magazine. You know, I'm here looking at a Jeanneau Leader 10.5,

and a few really interesting things popped out at me because this boat is built in Europe.

It's built for both the European and the American markets,

but there's some really interesting little tweaks that the Europeans put on their boats specifically to meet CE Certification.

Fortunately, we have Nick Harvey here from Jeanneau to show us some of these unique CE touches. So, Nick, what are we talking about?

So there's four things that I wanted to point out Lenny to you and the BoatUS readers or viewers today.

And I think the most obvious one is that we always have a manual redundant bilge pump on all the Jeanneau boats.

So if you just look to your right, you might just see it there.

Oh, there it is. Behind that little plastic cap. And you operate it with this handle right here.

So yeah, that's definitely the first thing that our owners notice on our boats. Manual bilge pump. Who would've thought of that, huh?

The next thing that comes to mind is probably

how stringent the CE certification is on water evacuation.

So in case a huge, monstrous wave was to fill in the cockpit

it has to be able to get out of the cockpit in a given time.

So they actually force us to have a certain size of scupper, and again, looking back over there

you'll see the grid there, and obviously it's open on the port side

so we are very, very controlled as far as the amount of water that can actually

evacuate out of the cockpit. And that's why the scuppers are the size that they are. That's exactly right. There's one other thing.

We have a

strict rule as far as the height between the bottom part of the cockpit – the lowest part in the cockpit – and

the entry into the cabin. So we have two steps in the case of the Leader

10.5, and the addition of the height of those two steps meets the CE

Certification, again to prevent water ingress inside the cabin. Gotcha. Gotcha. Well does anything else come to mind?

Yeah, maybe I was gonna mention one more thing.

The CE certification, again very, very tough on boat stability in general, and

they actually make sure that we pass the test –

we call it the 90-degree test – at full throttle.

We need to be able to turn a 90 degree turn within a given distance, and every single Jeanneau

powerboat has to go through that.

Interesting! OK,

so, folks, there are some of the things that a boat needs to go through to gain

CE Certification that you don't necessarily see on American-built boats. Now, that's not to say anything bad about American-built boats

They're usually built to say ABYC standards or, you know, certain levels of construction that are pretty darn reliable these days.

But it's pretty interesting to know that the Europeans look for these specific items.

We hope you found this video helpful, and don't forget to subscribe to the BoatUS YouTube channel.

For more infomation >> Boat Buyers Guide: What CE Certification Means for Boat Owners | BoatUS - Duration: 3:05.

-------------------------------------------

Huluween Film Fest: Haunted Sounds Behind the Screams • Now Streaming on Hulu - Duration: 1:29.

[CHOKING]

- I'm Rodney Ascher, director of "Haunted,

Horrifying Sounds From Beyond The Grave."

And action.

Part of this was inspired by the composer sound

designer I'm working with.

He's part of a team that incorporates

live sounds and field recordings into music

and sound effects projects.

So we were talking about how would be funny for some sort

of serious artist to find himself making a Halloween

sound effects record.

Like a lot of people I came to horror first as a fan.

Even as a kid and as a teenager I always saw it as kind

of a roller coaster challenge.

Am I up to the challenge of seeing this movie that I've

heard is so frightening, and when you survive that challenge

you look for the next.

Maybe it's a little sad to say, but horror

can really help you understand the world around you.

[CREAK]

For more infomation >> Huluween Film Fest: Haunted Sounds Behind the Screams • Now Streaming on Hulu - Duration: 1:29.

-------------------------------------------

3 Things to Look for 49ers vs Packers (Week 6, MNF) - Duration: 5:13.

Ayo! It's Bryan here. Today, going to be talking about the San Francisco 49ers as

always. Doing another Top 3 video. This time, trying to cover the game

against the Green Bay Packers on Monday Night Football. Going to be talking about

the three things you should be looking forward to for this game. So, this could

be for matchups to players to all the lily Dahle, all that good stuff.

Should be a fun time. I don't know if they can upset the Packers. It's going to be

hard, although Aaron Rodgers is looking really

banged up from all the news articles that I've been seeing from all sources is

that he's really banged up. I mean, it's against the 49ers. The 49ers

defense, they're not going to tackle as much from the looks of it. Offensively, they

might turn the ball over. For the Packers, I wouldn't worry too much,

although hope with the Niners can pulling upset, but it's going to be hard.

Going to be talking about that, but before I get the video started, have a really

big announcement for you guys. I started selling some merchandise now via

teespring.com. So, if you guys want to check it out, there will be one in the

info card section or in the link in the description below. I have a t-shirt and a

coffee mug if you guys want to take a look at it. I haven't bought for me

personally, which I should to show you guys. This is the best way to support my

channel right now and if you guys want to spend a little bit of money just to

buy a little merchandise for me, that'd be freaking awesome if you can,

but if you can't, that's okay. You know, I just kind of want to have my own

merchandise and I've been talking about it for the past couple of months now.

Yeah, merchandise? I think it looks pretty cool personally from all the pictures

and what have you and if you guys buy it, that'll be much appreciative. If you

can't, that's fine. Just wanted to cover that. Again, it'll be in the info card

section and in the description below if you want to take a look at it and

hopefully purchase it for yourself. That's it for the big news today. Before

I get the video started again, please "Like" and Subscribe to support my channel.

That would definitely help me out a lot. Let's do this. Let's kick some a** as

always. The Top 3 things you should be looking forward to against the Packers

for Monday Night Football. Coming in at number three,

I have turnovers. Now, the game against the Cardinals last Sunday, it was a

pretty disastrous day in terms of turnovers and giveaways because the

49ers turned the ball over about three times I would say. 2 INTS from

Beathard and one fumble by Mostert, which almost all of them led to points

for the Cardinals. That's why we end up losing pretty badly 28-18 to the

freaking Cardinals. A team that lost to the Rams 34-0. Although it was the Rams,

getting blown out 34-0 is saying something about your team and we

lost the Cardinals unfortunately. We still haven't beaten them since 2014.

It sucks. Turnovers had a big reason for that. Missed opportunities

right there. If they can just lower the turnover count. If they can try to take

care of the ball as much as possible, Beathard can do whatever he can. Also, he had

a fumble as well. I think a sack fumble or something like that too. So, that was almost

four turnovers in this game. Wow, pretty bad I would say and if they do that

against the Packers, man. We are going to get blown out big time because I think

the Packers are a better team, although Rodgers and them, they're kind of banged up

a little bit, but there's still a pretty good team in my opinion. 49ers, please

turn the ball over as less as possible. That will give you a

chance to win this game some way, shape or form. Coming in at number two, I have

injuries. I always mention this, mostly on all my list, but it is so prevalent to the

49ers right now. It is ridiculous how many people are on the injury report.

Being out for the rest of the season or out for this game. Notable players out,

Matt Breida and Dante Pettis unfortunately. I think this is Pettis's

second game out. This is Breida's first game out after he got injured against the

Cardinals last week. This is going to be a different offense and Beathard's going to

really have to rely on his passing skills to get through this, but luckily,

the Packers defense. They're kind of okay, but they're a little shaky as well.

Hope Beathard can take advantage of that some way, shape or form.

he has Alfred Morris and Raheem Mostert again from the back field. I

don't know if I can trust them. It's going to be hard to, but it's hard to lose

someone like Breida, who's been producing so well. Top five in rushing yards and

he's out for this game against the Packers. Injuries, I think it's going to take

a toll on this team. I hope nobody gets injured for this game, but if it does,

then it would suck big time. San Francisco, I don't know if they can deal

with this, but it's whatever. Injuries, unavoidable. Coming in at number one as

the biggest thing look for, for this game against the Packers is a hopeful upset.

I'm pretty pessimistic about this game. In my prediction video, I didn't really

have the best chance for the 49ers to win this game and I'm pretty sure a lot

of you guys didn't have a lot of faith in this team for this Monday Night after

the Sunday afternoon debacle, which was the Cardinals game. I kind of agree with

you guys. If they can pull an upset against the Packers at Lambeau Field, at

Monday Night Football, man! That would say something, but I don't

think that's going to happen, but you know, you got to keep in the back of your

heads if the Packers don't show up or if god forbids, something happens to Aaron

Rodgers or something like that. I don't know. 49ers, I give them a minute chance

to win this game, but if they do, that would be freaking awesome, but it's going to

be hard. That's going to be pretty much it you guys. Just wanted to

do a quick video on this game against the Packers. Should be exciting to watch

a Monday Night Football game for the 49ers.

Hopefully, we do not embarrass ourselves on Monday Night Football. As long as we can

keep it as competitive as possible, then I think it's a victory for us people in

Niner Faithful. I know you guys are expecting wins and what have you, but

with the roster. What it looks right now and the injuries that we occurred, going to be

hard. Please let me know what you're looking forward to for this game against

the Packers. Please, I'd like to hear what you guys have to say and if you guys

like this, please "Like" and Subscribe to support my channel. That would definitely

help me out a lot. If you want to buy a t-shirt or a coffee mug, they'll be in

the description below and the info card section on the top right of your screen.

That would be much appreciated if you can. If you can't, then that's okay. I'll

still keep it up there. See y'all later. Bye guys. Love y'all. Have a great rest of your

weekend and go Niners!

For more infomation >> 3 Things to Look for 49ers vs Packers (Week 6, MNF) - Duration: 5:13.

-------------------------------------------

Humano - Duration: 1:27:30.

There's only one way to uncover the mystery of life:

by knowing who we are.

I don't know who I am, where I'm from, where I'm going...

or who we once were,

who we are, or who we'll be,

if we become anything at all.

In photos from my past,

I discover a struggle and a yearning to comprehend my own existence.

I named this group of pictures "Regression of the Embrace",

or "How I stopped smiling".

Smile...

Hug...

Hug...

Hug...

Smile...

Less hugging...

Working on that smile...

Nothing much...

Wanting to disappear...

WARNING!

If you haven't faced life's conflicts,

don't watch any further,

because you probably aren't aware of your own existence.

BUENOS AIRES, ARGENTINA JUNE 2011

I'm off to meet Plácido,

a guide I met in Buenos Aires at a talk on Andean cosmology.

Back then I was writing a film script on the mysteries of the Andes.

Who are you?

What are you searching for?

I have a notebook full of questions,

and I hope to find as many answers as I can.

Sometimes, you can't even follow your own heart,

your own essence.

I want to switch off for a while.

I'll be your friend, not just your teacher.

Don't wait for happiness. Be happy with what you have...

from the moment in which you make that decision.

Some things in life are simple.

Those things shouldn't be questioned. Life should just be lived.

It's better just to live.

Sometimes we aren't ready for certain questions,

and when we are, the answers often bother us.

Some questions are so obvious,

they even provide their own answers,

so we don't take any responsibility.

Focus on living, not on asking so many questions,

because the truth can often be very disturbing.

We're still not quite ready...

to know the truth.

Oh shit!

In this place, traces of the past are still intact.

These prevailing traditions, are like something out of a dream.

These people hold within them

thousands of years of ancestral and Shamanic knowledge,

their legacy a gift to humanity.

After all, the Incas couldn't conquer them.

I'm looking for Placido.

You're here. That's a good start, isn't it?

Less than a century ago, they decided to emerge,

their first contact with the world.

I don't like being exposed to things,

and I usually try, if possible...

not to let them see my face.

What are you searching for?

The reason for our existence. Why are we alive?

Well that's a good question.

But at the end of the day,

words alone can't explain it.

Instead, we would have to…

If you want to find your answers, we'd have to go on a journey.

This journey...

was impelled by your ancestors.

Ancestors are the ones who have asked questions,

who have had visions,

and unable to find their own answers,

they've left it up to you.

What interests me most is the orgin of man, of human beings.

If you want to learn about humanity,

first you have to be human.

The human condition

must be consciously manifested within us.

We are all born as humans, but we are not all human.

It's a condition that must be achieved by those who want it.

It's really simple,

but words aren't enough to explain it.

That's why we're starting...

with some rituals.

Don't stray too far.

I gave my body to the lake,

I came out like this.

These waters...

are like ancient waters that have melted straight off the ice,

as if frozen in time.

That's why snowy mountains are believed to be sacred,

because they hold information, either water or something else.

They store things, as if frozen.

So that's why we have to come to the mountains

to carry out these rituals.

Let's see, how can we explain this, for example...

-Alan... -Yes...

Last night the temperature dropped

to about minus ten degrees,

and Alan spent the whole time

trying to endure the cold. Why?

I felt that my body couldn't endure the cold.

So you're experiencing different dimensions.

Here, we experience many dimensions, thousands in fact.

Nobody in their right mind,

at least from the city, would dare to come here

and try to endure sub-zero temperatures.

But you're in another dimension.

That's what happens.

Dimensions are ways of understanding,

they are challenges.

So I can tell you that right now, you're in another dimension,

just by being here.

After only a few hours together,

he tells me a story.

As a child, his grandma was playing in a valley with some "misarumis",

magical ceremonial stones that open the gates of knowledge.

After playing for a while, she mysteriously disappeared.

Her family searched the whole valley and asked door to door.

She had gone without a trace.

They went to the altomisayoc for help,

the only one able to communicate with the apus,

protective spirits of the mountains,

guardians of the Earth.

At the ceremony, the apus told them she was in another world,

and would return after six months.

After six months, she still hadn't returned.

The apus, aware of the situation,

explained that she would return the next day,

at the third strident chime of a bell.

The sun began to rise from behind the mountains,

and a bell chimed, making the earth shake.

Another chimed from the mountain's belly,

and yet another from its peak.

The altomisayoc made a desperate plea to the apus.

The girl spent that night alone.

The next day, the apus made the wallatas bring her back.

The apus had foreseen her return, but not the consequences.

She was sleepwalking.

They said that she would wake up on the third roar of a bull.

They couldn't speak to her, she had forgotten her own language.

She had forgotten Quechua

having spent 10 years on another planet,

or six months on this Earth, as per our concept of space and time.

Suddenly it all came back to her.

She spoke about a magical world,

where people lived in harmony, and anything you wanted became real.

It helps knowing that other ways of life also exist,

and how these relate to our own.

What is Pachamama?

Pachamama... is a very broad concept.

Pachamama even includes the universe.

What we should really be talking about...

is Aipa, or Aipamama,

which is much more specific, and which refers to the Earth.

So Earth, or Mother Earth,

isn't just our home.

It's our body,

and if we, or if everyone believed that Earth was our body,

then it would be impossible to harm Earth.

How would you define nature?

It's a little bit hard to define,

because defining life is never easy.

How can I explain this...

It's a slow vibration.

So nature is...

something that compliments our lives,

helping us to evolve or retrogress.

What's the purpose or function of man in relation to nature?

The evolution...

of all different beings on Earth.

What is the reason for our existence?

Existence is a way of combining...

light with matter.

-Why are we here? -Why are we here?

-Just by chance? -No, there are reasons.

-Why do people worship the sun? -Nobody does that in the Andes.

-What powers does man have? -One of man's powers...

I don't think I can absorb much more.

It's hard to take this all in as a mere study,

detached from the subject and its context.

How can we help things evolve,

if we're deliberately killing them?

How am I supposed to communicate with trees, mountains, earth or rocks,

when I can hardly communicate with myself?

Shamanism is a way of restructuring the mind.

Shamanism provides us with secrets...

to work firstly on our emotions, then on the material aspects.

If you can't understand your emotions,

you won't know how much or how little

you need to work on them.

Walk like a puma.

Feel you're a puma,

sniff like a puma, feel the Earth like a puma.

Shamanism deals with...

making things real and developing trust,

and tricking the mind.

It actually plays with the mind.

Could we do a Shamanic ritual or recipe later on?

Yes, we could.

Wachuma...

is... a sacred plant.

It's also known...

as Saint Peter.

When the Spanish arrived,

the Jesuits also consumed it.

So, they say...

that since Saint Peter is the one who holds the key to heaven,

what this plant did,

was take the Spanish up to heaven.

That's why it was named Wachuma.

Sometimes, with the help of certain plants,

you think you're seeing things that you can't actually see.

The reason...

why many people consume these plants

is to see what can't be seen.

We don't believe what we can't see,

and so it helps us.

It helps us to see, it helps us...

to believe in this invisible world.

Do you think this is nature's gift so that we can understand it better,

and be cured?

Well, these plants are sacred.

Tobacco…

Sacred plants...

are bound to man,

to help man.

But if man

starts depending on these plants,

man is no longer man. He instead lives for that plant.

We don't use Wachuma in the Andes,

only in extreme cases,

when a person can't understand or see anything.

The use of coca leaves is more common,

which are used for the same purpose,

to gain awareness.

-Is it hallucinogenic? -Yes, sort of.

But how can we be sure of what we see?

Is it not part of the imagination? Is it really there?

Well...

To tell the truth...

If your imagination, or whatever you like to call it,

changes your life for the better,

then...

then I think we can say that it's a good thing.

But often what you see can change your life for worse.

This whole journey up until now

is just preparation.

That's all it is.

And the best way to prepare yourself is by contemplating nature.

So really...

you're not just imagining it. There are other beings around you,

who can perhaps guide you,

and teach you something.

All of it?

The plant is already inside you even before you drink it.

This offering involves...

treating Earth as if it were our mother,

not just our home.

So...

it would be nice, once in a while,

or once year, to say "thanks mum"

for everything that I've taken from Earth.

How can you offer something to Earth right now,

if you don't even know how Earth is,

how it will react, or even what Earth likes?

Would you offer it something?

-No, because I don't know how. -Exactly.

But if you were to live for Earth,

and if Earth were to live for you,

then you'd know what it likes.

You'd know how to converse with Earth.

If we understand what exists on Earth and what surrounds us on Earth,

then we can begin to understand that other worlds might also exist.

Who taught others about the "despacho"?

Knowledge?

Well...

The Saqras passed down this knowledge

to the human priests so that they could fight against...

-The Wiracochas? -The Wiracochas and the Chullpas.

So we've inherited this knowledge from the Saqras.

If Earth undergoes any changes,

or if Earth...

is damaged in a way that is not its natural process,

then humanity will also be damaged.

Humanity will also be destroyed in some way,

or it will destroy itself.

Well, here we are.

We've just finished the "despacho" ceremony, and...

we're in the mountains,

in Qeros.

It's really cold.

"Despachos" are usually carried out

in the mountains, near a lake.

We made an offering to Pachamama.

I'm slowly starting to understand...

what I'm being taught.

It's not that easy for Westerners or "gringos"

to understand...

the Andean worldview.

But I feel I can really identify with all of these concepts.

You'll just have to learn how to trust, that's all.

Off you go.

The only thing that can overcome fear is action,

but that action needs to be as slow as possible.

Yes, I'm scared, I'm trying to ignore it.

Fear only exists...

-if you need it to exist. -Yes.

Trust yourself.

The cold is part of adjusting.

-Am I doing well? -Exceptionally well.

Am I doing alright?

I'm already in the cave.

Wow!

No!

-See how there's no fear? -It's so beautiful.

When we aren't afraid, we see that beauty.

Fear doesn't let us see...

-...reality. -Reality.

It would be great if people could trust,

just once in their lives, in something that they can't explain.

Wow!

Well I can't really explain

what I was feeling just then.

It was a mixture of fear, adrenaline...

of understanding fear...

You can understand fear in the dark.

Everything is intensified...

I could see the fear, it had a form.

This place is completely magical.

It can be hard to describe fear.

Sometimes it's just an image, or a feeling,

that words can't explain.

I think today was the first time...

that I completely understood fear,

and felt joy in overcoming it.

It's all so simple,

sacred places for overcoming fear,

other "huacas" for understanding love, or laughter.

It's all so simple...

and yet sometimes our fears are so complex.

when they come from...

who knows where, right?

Our fears...

The burdens we often carry...

are what our fathers wanted, our grandfathers,

and what their grandfathers wanted.

So in the end, there are seven generations behind us,

supporting us and directing us in their path,

not ours.

So these bags or burdens that we carry

are nothing but genetic influences.

They're often genetic, and sometimes emotional.

This is...

a kind of...

...door. -Really?

-Look, there's a ghost here. -Yes.

It's a ghost.

I want you…

to repeat seven times, while looking at this,

"Forgive me, I forgive you".

The human body

isn't that straightforward. It's really complicated.

Once, maybe,

it meant everything.

And back then, it was present here too.

Working with your ancestors

means that you will recognise...

what you were.

Forgive me, I forgive you...

Some beings once lived here

and built this whole place

with a purpose in mind.

Nobody knows what that is,

but if you do this...

you'll have a greater chance of finding out.

This Earth...

registers all evolution, right here.

Our ancestors...

were once here,

talking, eating, working.

Everything is registered here.

Here...

Eat this...

Pachamama has its own language.

Fire has its own language.

For example,

if you say "hello fire",

do you think it will understand?

I hope so, I don't know how to talk to it.

Well do you know why it won't understand?

Because the fire never learnt how to speak Spanish.

-That's why. -It didn't go to school.

Not to school, or university.

-Have you ever heard of "ícaro"? -No.

Wow, which world do you live in?

"Ícaro" is a chant

without a form.

The form, or what we're speaking, is Spanish.

That's a form.

Only those who speak Spanish can understand it,

nobody else.

Fire doesn't speak Spanish, so it can't understand you.

But "icaro" is a language for communicating

with everything material on Earth.

The chant goes like this...

Sing however you want.

-Whatever I want? -Whatever you want.

So...

-Did you understand anything? -Yes.

One night I dreamt that I was walking in one of Cuzco's valleys

when a pack of bloody-thirsty dogs attacked me.

I told Plácido about my dream,

and he explained that I had eradicated all of my old ideas.

What concerns me is the awareness of humanity.

The only way for someone to ultimately evolve

is by bringing awareness to humanity, to people on Earth.

So, I think that's my goal, what I wish for.

I know I may not achieve it,

but at least I will achieve it within myself, I know it.

Let's go. Come on, hurry up.

Come on.

-Why don't you stay? -Stay where?

Here.

Don't you think it would be easier to stay here?

Easier?

-Yes, it would. -So why don't you stay?

I guess it's because I'm trying to push myself.

Here, carry this.

-What about the camera? -I'll take it.

I'll help you.

Come on, run.

Faster!

This pile of rocks...

has been formed by others who have also brought rocks here

to adapt to this place.

Put it on there

and stay here.

They are the few who have really lived.

The rest are asleep.

Long ago, man's purpose for temples was practical.

Here, people began to learn about different things,

like true love, medicine,

and understanding the different bodies that live within us.

Plácido told me that temples

are linked to specific things that need working on,

like understanding the 3 Andean worlds,

where they all relate to one another.

In Tiahuanaco, we find the Sun Temple, linked to Hanaq Pacha,

the world of the condor, of the future.

It's the celestial kingdom where our ideas about God exist.

Nearby, there's Puma Punku,

which is linked to Kay Pacha, the world of the puma, of the present,

and where we live in harmony with the apus and with nature.

Strangely enough, Plácido mentions a missing, lost or hidden temple.

It's the Uju Pacha Temple,

the world of the snake, the past, of material things.

We can't be introduced to the other temples

without conquering the snake first, or material things.

Nobody arrives at God's feet from above.

No wonder there is nothing left of this temple.

After seeing all this, I wonder...

what the conquerors would have felt seeing these majestic constructions.

Would they have felt intimidated when they discovered their purpose?

Could this be why they built churches where the sacred Andean temples lay?

What do the inscriptions mean on the Sun Gate?

Could they be instructions to awaken mankind?

Nowadays, temples are more about control,

and more about...

hypnotising people.

-Weren't they always? -No, they weren't.

Temples used to be for freeing man from mankind.

The Andean way of life is not a religion.

Different religions have made us...

seek external Gods.

They haven't allowed us to take any responsibility,

or accept a God within us.

They've always taught us to search for something else.

What are your questions about religion?

It's more about trying to understand why religions exist.

What their purpose is...

since they seem to segregate people rather than unite them.

That used to annoyed me, but not anymore.

I've also learnt not to reject my own religion.

The only thing you need to understand,

is that everything

is there to be understood,

and not to be rejected or judged.

As soon as you start judging, you enter into dualism.

So if we want total peace,

there will be total war somewhere...

-on Earth. -Of course.

So there will be absolute peace.

Those who preach love reach the light straight away.

Those who preach death, like the Catholic religion,

stay on Earth instead of reaching the light.

They say things like "you need to die to find happiness",

or "you have to die before you can go to paradise".

As long as these two conditions,

Earth and light, allow us to exist.

If we understand this, then we can be human, but only then.

Otherwise we'll either be Sajra,

what Catholics call the "devil",

or else a type of God,

or a priest to these Gods.

We'll simply never be human.

It's easier to identify with divinity in the mountains,

than in the city, locked up inside temples,

praying to an unknown God, whose intentions I'm not sure about.

But amongst nature, it's all there.

Some of the knowledge is protected in a way,

because knowledge in the Andes

was somehow first protected through jealousy,

and only for those who could see it,

because in the Andes, knowledge is like a key,

and you don't give your key to somebody you don't know.

And that key opens dimensions directly,

which may seem crazy to some people,

like an illusion, or part of one's imagination.

But if somebody was once there, then it's real for some people.

Throughout my time in the Andes, people always talked about the apus.

These beings are invisible to us, and they take care of Earth.

Their bodies are the mountains.

After hearing of people's experiences with the apus,

I didn't want to miss out and put my anxiety aside.

I too wanted to meet the apus.

We spent two months trying to locate the altomisa,

until we finally found her.

We couldn't film this session.

María is very old and not as strong as she used to be.

She seemed ageless.

She observed me without saying a single word.

I was really scared.

I had more coca leaves in my mouth than ever.

Nothing could calm me down.

At first, I didn't really understand what I was hearing,

whether it was the Shaman's distorted voice,

or if there was really something else there.

Everyone said "Good evening daddy".

It was the apu.

I was late to greet him.

He wanted me to ask a question.

Trembling, I asked about the apu's role on Earth.

We stayed like that for 30 minutes.

After the first five minutes I was able to switch my mind off.

I didn't want any rhetoric between my conscious and unconscious.

I let myself enjoy what I was experiencing:

one of the most beautiful symphonies I had ever heard.

Believe or die.

Many people think and say

that Andean ancestral practices are the work of the devil.

If that's the case, then Lucifer's acolytes are amazing.

My experience with the apus ended up killing all my dogs.

The apu who came to the ceremony

suggested that I talk less and practice "allynkausay",

the human path towards balance.

He also told me that my own apu was Champaquí.

I couldn't believe it.

They'd said Champaquí, a protective mountain in Argentina.

I thank the apus for all they've given me.

For the death of our dogs.

-Could you say that this is alive? -I can say it's alive.

But only to you.

Could you explain that everything is alive?

Everything?

In just one word?

Could I explain that everything is alive?

How could I explain it? No, I couldn't explain it.

Could you tell others that this rock is alive?

I would have to explain it using examples,

by practising.

The apus are the same.

Unless you've shared an experience with them,

unless you've lived with them,

it's all just a story.

Actually I don't feel...

like I've left anything unfinished, fortunately.

And what will you do with all this?

A movie...

For your apu, Champaquí.

Do I blow three times?

Blow on it...

and ask to connect with your apu.

Here's part of the Earth

from where you're connecting from.

So the underworld, or what we call Uju Pacha...

-The world of the snake? -The world of the snake, let's say.

It's a place...

It's exactly the world we're going to work with.

There was once a world named Earth.

Androgynes inhabited various parts of this planet.

Chullpas were beings who built things,

not with their hands, but with their voices.

One day...

a being called Wiracocha arrived.

He saw everything that was there on the planet.

He had come from a planet called Apu.

And so they named him Apu Illa Teqsi Wiracocha.

And so he taught these beings about dualism.

Then a Saqra, another being,

arrived from a faraway planet or star.

He started to extract gold from this planet

for vital energy,

energy that is consumed by these beings.

The Saqra...

decided to create a new being.

He created man and woman.

The Chullpas disappeared,

and humans began living

in dualism as men and women,

in various parts of the Earth.

So we were created by the Saqras,

and in the end, we are like their slaves.

More beings arrived,

and they wanted to know

why these new beings were created.

As punishment,

they sent the Saqra deep below the Earth

so that he could see his own creation,

and whether or not they would be his slaves.

That's why he's known to be bad,

but actually he's neither good nor bad.

He's the same as us...

Even in Latin, Lucifer means "carrier of light",

so it sounds strange if something negative carries light.

He is still seen as being negative,

because the only thing he seeks, from one point of view at least,

is to gather all the energy on Earth, which is gold.

So the only thing that major religions try to do

is face up to him and find their own gold,

although always saying "they're bad, we're good".

But do both of these energies search for gold?

Both of them search for gold.

But I'm not referring to the conscious mind.

I'm referring to the unconscious mind, where it's known to be true.

And it's known to be true, because it is.

How do we know about the story of creation?

We know about creation

because there are certain frequencies that humans can reach.

Stones speak.

They become permeated with that information.

How interesting.

When I first wrote down that question

about whether it was important for us to know our origins,

I thought it was the most important question of all.

Now that I know it, it doesn't seem important.

It seems more important to know...

who we were, who we are, and who we'll be.

Understanding this is easier than knowing who I am.

Knowing who we are is up to each individual,

and nobody else can tell our story.

Because this is a story, stories are easy to understand.

Please come in.

Right now we're inside the elephant's belly,

-inside its form. -Which represents...

-Which symbolises... -...the Mother's belly.

Your mother's belly.

Since you couldn't return to your mother's belly,

we need to search for an alternative.

so that we can re-enter it

and be consciously reborn from the mind.

Lie in a fetal position.

Use the cold to create a connection.

Listen to your heartbeat.

And Earth's heartbeat.

WARNING!

HUMAN,

CLOSE YOUR EYES

Feel like you're part of everything.

Breathe from the trees,

from the rock, from the ocean.

All you have to imagine, is that you're inside,

and convince yourself that you're inside.

You just have to be aware that you are Earth,

all the time.

That's all.

All you need to realise,

is that you are just one more cell on Earth.

Once you realise

that you're part of Earth,

you'll start facing up to Earth.

But if you aren't aware of this,

you'll just be a virus.

You need to realise...

that your body...

is the most evolved material form that exists.

Life of mankind is closely linked to life on Earth.

If humans, as a group,

do something negative to Earth,

then all that evolution will go to waste.

Understanding a second beginning from the mind

means being aware of where we are.

It's about realising...

who we are.

Having made it this far means that you've made the effort.

You're already here.

All you needed to do was make it this far.

Wake up as a human being.

Make a conscious decision to be born again.

We're a mixture

of four DNA.

That's why we don't even know who we are,

or where we're going.

We don't even know what to look for.

So when you do something good, it seems bad,

and when you do something bad, it seems good.

All you have to do...

is take...

everything inside you from your ancestry,

which are those four DNA,

and declare yourself a human being.

And remember

that your main body is Earth,

and it's your home.

As long as you respect this,

everything will be fine.

Otherwise...

all creation...

the whole species...

will go to waste.

One day I decided to put this mask on

to explain to you that life is really simple.

As an action, that's all it is.

All of it, just for me.

The apus and Pachamama

ask nothing more of you than awareness about sharing.

When you put this into effect,

you start to live and face up to Earth and the apus,

and vice versa.

Life brought me to you,

to help you remember who you are.

You've done it, haven't you?

I hope you'll never forget

that you're a human being.

So in the end, what are you?

In the end, what are you looking for?

Who are you?

In the end, what are you?

TO OUR ANCESTORS, WHO CONTINUE TO LIVE WITHIN US.

For more infomation >> Humano - Duration: 1:27:30.

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Regularization for Sparsity - Duration: 1:42.

So let's dig a little deeper into feature crosses.

They can be great but they can also cause some problems.

In particular if we're crossing sparse features.

For example maybe one of our features is the words in a search query and the other feature might be unique videos that we have to look up.

So now we have maybe millions of possible words, maybe millions of possible videos and we're crossing those, we're going to get a lot of coefficients.

All of that means that our model size is going to explode, taking memory, possibly slowing down runtime.

And a lot of those combinations are going to be super rare even if we have a lot of training data and so we may just end up with some noisy coefficients and possibly overfitting.

So you know the answer, if we're overfitting we want to regularize.

And now we're going to say can we regularize in a way that also will reduce our model size and our memory usage?

So what we'd like to do is just try to zero out some of the weights, in which case we won't have to deal with some of those particular crosses.

This could save us RAM and this can also potentially help us with overfitting.

But we have to be a little careful we don't want to lose the right coefficients, we just want to lose the ones that are sort of extra noisy.

So what we'd like to do is explicitly zero out weights, and that's what we call L zero regularization.

It would just penalize you for having a weight that was not zero.

But that's not convex, it's hard to optimize, sort of a comma trail problem.

Instead what we do is we relax that to an L1 regularization, which just penalizes the sum of the absolute values of the weights.

And by doing that we still encourage the model to be very sparse, it will drive a lot of those coefficients to zero.

And that's a little different than L2 regularization, which also tries to make the weight small but won't actually drive them to zero for you.