he will talk about this frequency principle in deep learning and how to relate this to physics. Yes, so please to Chen. Okay, can you help me, Hajin? Yes. Okay, thanks. First I want to thank Hajin for inviting me and giving me this opportunity to present our recent work. So this is the current undergoing work, so if you have any comment, they will be very welcome. So today I would like to thank Hajin for inviting me and giving me this opportunity to present our recent work. So this is the current undergoing work, so if you have any questions, I can share it again. Okay, can you hear me? Yes. Okay, good. So first I will give some takeaway information. So first I will talk about the frequency principle that deep neural networks prefers low frequencies. Based on these understandings, we actually designed a multi-scale deep neural networks. Am I muted? Am I not muted or not? No, it's okay. Okay, you can hear me, right? Yes. Okay, okay, I will continue. So second I will talk about a first diagram to understand the two-layer neural networks and try to understand the deep neural networks from a systematical picture. So now let's talk about the macro's perspective. So as we know that John Manoeman has said, with four parameters, you can fit an element to a curve and with five, you can make him wrinkle his trunk. So in fact, we always try to use as less parameters as we can to fit a model, but this may be not true in deep learning. Now let's take an example. So traditionally, if you use a model to fit the training data like blue data points here, and if you use a force order polynomial to fit the data, although you cannot fit the data perfectly, but actually you can recover the true model quite well. And if you increase the complexity of your model, such as you use 15 degree or polynomial model, you can actually fit the training data quite well, but you can see oscillation here. That means it overfitted the data very significantly. So in traditional learning theory, actually if you increase the model complexity, you can decrease the training error, but you can increase the test error. So this is traditional theory. That's why phenomenon said you need to use as less parameters as you can. By deep learning, that is a puzzle. So even the number of parameters is much, much larger than the number of training data, that deep neural network seems to always generalize well. And this is supported by a lot of experiments. I want to go to tell into this experiment, but we try to use a macro perspective to understand why the deep neural networks does not overfit even though the number of parameters is so many. So here's an example. Suppose we are going to fit a target function that is denoted by this red curve. And the training data is denoted by this blue data points. And after training, the deep neural networks can well fit the target function as we can see here after training. But what we care is how the neural network fit the training data. So we want to see the training dynamics. So here is the dynamics movie. So before I start the movie, let's describe these curves. This red curve is the target function. And this blue one is the deep neural network output at the first training initial output. And now let's take a look at this movie. So as we can see that the neural network, after some training steps, you will capture the landscape. And after some time, some details emerge. And as the training keep on, you will converge the target function. So the deep neural network seems to capture the first landscape and then more and more details. So to quantify this effect, it's very naturally to use Fourier analysis. So we perform Fourier analysis of the target function and the deep neural network output. So here the red dashed curve is the FFT of the target function. As we can see, there are many peaks because the target function has sharp transition. It's not so continuous. For the neural network, the FFT is denoted by this blue line. And if you train a neural network, and now let's take a look, this is the frequency and this is amplitude. So after the training goes on, the neural network will first capture the first peak, and then the second peak and third and fourth and keep going until higher frequency. So we can have an observation that the neural network captures low frequency components first, while keeping other high frequencies once more. And then it gradually captures higher and higher frequencies. So we call this frequency principle or app principle. So the very simple idea is that deep neural network seems to prefer low frequencies. So we use this to try to explain why there's not so much oscillations in the deep neural network, even though the number of parameters is much, much larger than the number of training data. But in this talk, I want to go into detail of this frequency principle. We try to utilize this understanding to design deep neural network structures to fit high frequency faster. As we know that it's some problems, high frequency actually are quite important as such in some computational physics. So now let's, okay, let's go through this application. So suppose we are, let's consider a Poisson equation. So this is a Poisson equation with deletion boundary condition. So you can solve this problem by just a very simple finite, finite difference of skin, just central finite different, different skin, and you can get a linear system a u equal g, and you can solve this linear system by like a Jacobi iteration or Gaussian-Sendale iteration. And if you analyze this model more carefully, actually you can find that the low frequency, low frequency converges much slower than higher frequency. So this is very different from this deep neural network. Now let's take a look how deep neural network can solve such a partial differential equation. So to solve this partial differential equation actually is equivalent to solve the following variational problem. So this variational problem, the minimization of this problem actually is the solution of this Poisson equation, and this part is a regularization part to try to satisfy the boundary condition. So we parameterize the UX by a deep neural network, and the input is X, and output is UX. So we only need to minimize the parameters such that you can minimize this variational form. So now let's take a look about this 20 dynamics of different frequency. So here's an example. So gx here is the right hand side term of this Poisson equation, Laplace u equals minus g. And we choose this g because we want to have some high frequency components. So let's take three frequency components, higher frequency, one median, and lower frequency. So this is the Jacobi method, and this is the iteration epoch. And this color indicates the relative error of this different frequency. That means the relative error is very small. So from this picture, we can see that high frequency actually converges very, very quickly. However, the low frequency actually converges extremely slow compared to this high frequency one. But for different deep neural networks, this behavior is completely different. As we can see that the first frequency actually converges very faster, and the second one and the third one. So these actually are very different. But as we know that deep neural neural network now are applied into a lot of such differential equation problems because it has a lot of potential to solve high dimensional problems, but it will suffer from high frequency curves. So how to solve this problem? Our idea is very naive or very simple. You just scaling the function. For example, this f is an original function, and you just do a rescaling in the forward domain. So suppose you are considering a function and the function at a frequency alpha k, alpha is larger than one here. We just do this rescaling to another function. The frequency of this function actually is k. So the frequency for this function is smaller than the original function. So we only need to fit this lower frequency one. Then we kind of rescale back to high frequency one. So this is performed at a forward domain, but it's totally equivalent to perform at a spatial domain just to do a different direction. This applies in the rescale form. So since this rescale form is kind of approximated by this deep neural network, so actually we can have a lot of neural networks to perform it to fit a different frequency. So we have answers of neural network. Here, HI is the one neural network. So we construct a structure called a multi-scale structure. So this multi-scale structure actually is consistent of a lot of sub-neural networks. So in each sub-neural network, it received input x, but with a kind of rescaling factor x2x until nx. And they don't have any connection between each other. So you can save your computation cost. So in the final, you just have a summation of all the output of these sub-neural networks and you can have output. And you can have used the previous similar procedure to solve like Poisson equation, Poisson-Folkman equation and so on. We have done a lot of experiments and we found that for this multi-scale neural network, it kind of uniform conversions for each frequency. And it's mesh-free. You don't need to make any mesh. So it can deal with very complex domain and it's very easy to implement it. So you just need to have a slightly changed network structure. Here's an example. So we compare the multi-scale neural network to a fully connected neural network. So in a normal case, we use a network with hidden layer 1,000 neurons. For this multi-scale case, we use 5,000 neural networks. And each neural network also has 200 hidden layers. So from the perspective of the neural number, these two actually are the same. But for this multi-scale one, you have much less connections. So the computation cost is much smaller. So in this case, we take an example. This is a 2D example. This is an exact solution. It has a lot of different scale oscillations, different frequencies. And for the normal case, actually it can only learn the low frequency. As we have mentioned previously, in the frequency principle, it prefers low frequency. It's very quickly at a capture low frequency but not a good at a high frequency. So you can see that things in this circle or things in these corners compare with this true case. Actually, this is a normal case. It's much more smooth. You cannot first-party reconstruct this oscillation case. But for multi-scale case, you can see that all these oscillations can be well reconstructed or can be well captured. Now let's take a look at the training process, the error. This is L2L. For normal case, the L to create much slower than the multi-scale one. For 2D case or 3D case, and we actually perform extensive experiments, like for 2D, 3D, or Poisson-Bosman equation and so on. If you're interested, you can look for the paper. It just came out very recently. So now we have this micro-perspective to understand that in the neural network output actually has some order from low frequency to high frequency. And we have shared some lines to understand the generalization ability and can help us to design the neural network structures. Now let's try to understand why there is such behavior. Let's go from a micro-perspective and try to understand more. So there are a lot of related words that try to understand that this frequency principle. Now let's take one. So let's take an example of two-layer neural network. This edge is a two-layer neural network. And you can see here there is a pre-effector or scaling factor. And this A is the output vector. And W is the input weight. L is biased here. Slightly different from the common useful one. But actually you can do it perfectly almost the same for normal case. But the scaling is important. So we consider for sufficiently large M. This is very easy to understand. Just like in a statistical mechanics, you want to consider an ensemble. You always need to do some more dynamics limit. Okay, so in this case, if we study from the first principle, means we study the gradient descent of each parameter. So that's the meaning why we call this micro-perspective. So we can gather the dynamics of this neural network output. This is the Fourier transform of the neural network output. And this exceeds the Fourier frequency. And this is the coefficient. Okay, so this part actually has very interesting properties. So HP means times this sampling density. If you have discrete sampling density, it's just a summation of data function. So this equation stops when your training output at the training data, your neural network output at the training data equals to your training samples. Okay, so this makes sense. All equivalent to our training process. Now let's take a look at this coefficient. It's very interesting case one. So this black data actually is the mean taken respect to the initial parameter distributions. And this can see the frequency. As we can see that when you increase the frequency, actually this coefficient is decreased. So this reflects the frequency principle. Right. And one more interesting thing is the solution of long-term limit, long-term limit of this OD actually is equivalent to the solution of this minimization problem. And this minimization problem actually give us a lot of information. So I don't want to go to the detail of this proof, but it's actually very simple. This is the kernel regression. So there's a minus one here. So there's a C square in the denominator. So this part actually is kind of increased as the frequency increase. So the penalty will be larger for this high frequency component, meaning this neural network will find a solution that can satisfy the training data, but has as less low frequency as it can from all solutions that can fit in training data, but it prefers low frequency. Okay, now let's take a look more. So if you only have one part for the whole part, actually this is the cubic plane. So and just give us a very intuitive understanding of how the neural network interprets the training data. And if you only have this minus two term, this is the linear plane. So now let's take a look here. So if you have different parameter setup, you actually have different interpretation results. So it's very important to study the different parameter regime. So we are going to understand this different parameter regime. So we're going to draw a face diagram for neural networks. As a first step, we will try to do it for two layer neural networks. Now let's take an example of this fluid dynamics of the face diagram of water. So as we know that you can see the index, the coordinates like a pressure or temperature, and you can draw a face diagram for water. And we can benefit a lot from this face diagram because like in this part it's solid and this part is liquid, they have a lot of similarity dynamics similarities. So if you know some point in this liquid and you have another point of liquid, you know, they must have some similarities. So that's the kind of starting point or motivation of why we want to draw a face diagram for neural networks. So we can see the very naive model. This is the two layer ReLU neural networks. So we can see the very general form of neural network. You have a pre-scaling factor, the input weight and output weight are wk and ak. You can consider a high dimensional case. And initialization of this ak is initialized by Gaussian distribution with standard deviation beta one and wk beta two. And we train this neural network with mean squared error. So why we say this is a kind of very general form because if you take alpha equals to square root m, that is anti-k, very well studied just in previous examples, we use this case if alpha equals m. And this is in the mean field. So these two actually are very popular types in the last few years in theoretical study of neural networks. So to study this model, actually we need to do some normalize on non-dimensionality. To understand this, actually you can think about this Reynolds number while we want to define Reynolds number. Because although sometimes you can have different scales, different kind of parameters, but they have dynamic similarities. So if you compute the Reynolds number, they have the same Reynolds number, you know they have some dynamic similarity. They're similar idea. So we know that this a and w, they are initialized by some Gaussian distribution with beta one and beta two. To derive a kind of normalized model, we actually can do this rescaling. This ak can be rescaled by this beta minus one and wk can be rescaled by beta minus two. Also we can have time rescaling. So after doing this rescaling, actually we can derive a normalized model. So for any model we have, we can just compute their normalized a or normalized w. So what we care is the long-term solution of the neural network. So actually here are three parameters, kind of a, w, or t. They have different three scales. But t, the scale of t is not important because we only care about the final solution, the well-trained state. So actually there are only two kind of independent coordinates for this final solution. Okay, so from this dynamics, from the gradient descent, actually we can, we can see there are only two important quantities. One is beta two minus over beta one. The other is beta one, beta two over alpha. So we use these two as kinds of index. So we define the kappa and kappa prime. However, as we want to consider this m, this neural number goes to infinity. So as we mentioned before, this alpha actually goes to infinity or goes to zero. So there may not be a perfect quantity for index in the first diagram. But actually we can use their rate, how they go to infinity or go to zero with respect to this neural number. So we define this gamma and this gamma prime. Okay, this gamma actually is the decay rate or kind of rate of this kappa with respect to this m. And this gamma prime is for this kappa prime. So let's take an example. Suppose gamma prime equals to zero. We take different gamma and you can see we learn these four data points with different gamma. You can see they have different learning results. So we first, okay, so we want to classify this model into different regions. So the first step is what kind of regions is the best to classify. So this is the model, right? But if this sigma is a kind of linear or this part does not change during the training, this is the random feature. For random feature model, you can just perform this linearization. We actually ignore the initial output because usually the initial output can be offset to zero. So what's the meaning of the linear model? Meaning this model can be linearized with respect to this initial parameter or you can do it in a first order tele-expansion. If this is a linear model, all the things are very simple. Okay, so now let's understand in what case you will be a linear model. So since the only linear part is sigma, so if this w parameter does not change a lot during the training, then it means this model can be linear model because it's close enough. You can do a tele-expansion. So we only need to examine the relative difference of this w. Okay, so this phi w is the collection of all w. So this gamma equals 0.5 as we can see. As the m neural number goes to infinity, the relative difference goes to zero. So in this part, we can understand that it can be well approximated when m goes to zero by first order tele-expansion. For the second case, gamma equals to one. The difference of the change is over one. So this actually a critical point for gamma equals to 1.75 as m goes to infinity, it goes to infinity. So this is not a good linear case. This is a non-linear case. So we normalize the model and use gamma and gamma prime to enhance this dynamic behavior. So if we change different parameters, but they have gamma, same gamma and gamma prime, you can see the slope, the slope of this change is the vertical coordinates here. Almost the same. That means the effectiveness of our coordinates for first diagram. So now next, we can try to study the relative difference of this theta w. Actually, we study this slope and try to classify in the region. So we found that actually for different gamma and gamma prime, a large region actually can be classified into linear region. And this is in the red part. In the blue part, the slope is larger than zero. So you will go to infinity after m goes to infinity. So this is a non-linear region. And in this boundary, separate these two regions, actually the change is over one. So we actually have a very simple way to classify the neural network into a very simple first diagram. But this is very important because as we can see here. So a lot of other studies actually study the behavior or the properties of the neural network dynamics. And like this NDK or Meanfield or some other works like Professor Wiena Yi's work, a lot of other works. But actually in this first diagram, they only study at some point here or there. And we already know their studies has a lot of similarities. But actually, we don't have a kind of conclusion picture to understand why they have a similarity or are they in the same region. So this work actually kind of as an initial step, I try to understand this first diagram for two-layer neural networks. And in the future work, we try to understand more about this more deep neural network, not just two-layer, and try to figure out the first diagram for the neural networks. So finally, still take away information. If you're interested, you can go to my website. And the key point here is the frequency principle about this low-frequency preference and some network structure design. Finally, a first diagram for two-layer neural networks. Thank you. If you have any problem. Thank you. So there is a question in the question and answer. Can you see? Yeah, I can see it. Yeah. Okay. So, yeah, today I didn't go into kind of... Maybe you first read the question. Okay. I can describe the question first. So the audience said, many talk about curve fitting. However, we know deep neural network or machine learning was not designed for just a curve fitting. What people really care about in deep neural network is generalization power. How do you relate the generalization power to your frequency analysis? Okay. I didn't show the result, but actually we have other results for this. Okay. So let me relate it to here. For example, here. So you can also perform this, like, following analysis for, like, classification cross. Okay. Here's an example for MNIST or SIVA 10. You can use a free connected or convolution neural network. It's also okay. And you can perform this following analysis from this mapping from image to the label. And you can pick a direction, like a principle, a first principle direction to seed. You can see in such a task, actually, low frequency still dominant. So these red data points are the training data. And this green one is the owner data. You can just perform following analysis. And the neural network of fitting actually may fit in the low frequency very well. But in high frequency, it has slightly different. So since the low frequency preference of the neural network is consistent with the low frequency dominance of the data, so it can work very well and the generation is good. However, for other tasks like this priority function, it has very different behavior. You perform following a transform of this priority function. This function is defined by only minus one or one two data points. And the output is just modification of all coordinates. In this case, high frequency actually dominance. So in this case, if you don't have enough samples, actually you don't have all samples, your learning actually will have more power at a low frequency and less power at a high frequency. And the learning curve from the blue one is totally different from the real case. So it doesn't have any generalization power. So even for this real image data case, we are following analysis can also be applied. Okay. So I also have one question. So in the second part, you design the method to make sure that the neural network can claim all these different frequencies the same. Yes. So for these things, would you need to have a knowledge about the frequency distribution of the original data? Yeah. Even if you have information of the original data, you actually can design much efficient method to faster capture the high frequency of the target function. Actually, professors have developed a method called a phase BNN. But in their method, you need to specifically know where the high frequency is, and you can just do a shift the high frequency to low one. But in our case, actually, we don't have such accuracy. So we just design an answers, you can understand this is just an answers, and you can from this fitting, we found that its answers actually, well, all we can say you have this capability to transform this high frequency to low frequency. We actually don't know if we really do it. Actually, in experiments, it did. So this, if you have information of the real target function, yeah, they will benefit a lot. Yes. Also, Professor Tang is a question. Can you see, Professor Tang says... Let me check. Okay. In essence, we discussed about from mapping from the study to common organization. So far, actually, we don't work on this SGD. We actually work on this gradient descent, fully gradient descent. If you add several parts, if you add some gradient mass stochastic or some noise in these dynamics, I believe this frequency principle actually still holds because experiments show such a phenomenon. The second is, I believe if you write this SGD, more clearly, you can see more details, like you may see more relation about this stochastic gradient descent to naturalization. And I know a lot of works out in these directions. I actually don't read too much about Lenka's work. I read some of his, some of her work recently, very inspiring, especially the work that called for the physicists to study machine learning on deep learning theory. That's quite inspiring, but I don't quite read very carefully about his recent work on this SGD already. So I could not comment too much on this. Okay. So maybe the time is up. We think to change again. And then we will talk about


edition of Create Onigiri. I absolutely believe that each and every one of us has a purpose. Our purpose comes from our passion. That passion burns so deeply inside of us that we must respond or react to it and go on that path to create our life. Oftentimes if you don't, you find yourself being unhappy or feeling like you missed something or you're lost in life. Sometimes you have more than one purpose or passion in your life. Your second passion comes along later on in life. Today's guest, Carrie Marble of Bark and Scratch Outpost, is going to tell us exactly how a passion led her down a road to a purpose not only for her but for many many others. Hi Carrie, welcome to the show. Hi Tony. It's wonderful to have you here today. Well thank you for having me. That's absolutely my pleasure. So the first thing I want to talk about because I just have to say in so many ways you saved my dog and probably a number of other pets and you have no idea how many pets you've probably helped and saved along the way. That's part of the reason I'm so passionate about having you on this show today. Thank you. So how did you first get on this track of pet food? Well I was lucky enough to have a Bijan Faze come into my life 12 years ago. Her name is Snowbell and I didn't know anything about pet food or dogs for that matter and we experienced some allergy issues within six months of starting the vet recommended food in the puppy pack. Yeah.  Right. Did I read the back? No. Did I do any research? No. You know I just fed it. Trusted. That's right. Trusted. Yeah. And it didn't really turn out so well because she started having anal sac problems.  I was quite confused when he first said that. I was like what? You know and what's going on? Yeah exactly. And then we would be walking and having fun activity and she would turn and bite her side to the point where she had no fur. They call them hot spots. Found that out very quickly. Yeah.  And this was all within a short six period six months to a year because you know I am the type of mom that no it's not working. We need to try something else. So I'm constantly in the vet clinic trying to figure out what's going on. And for a while there I thought it might have been one of the worst things I've ever did because there was so much stress and that's six months. Yeah. You know and this poor puppy you know but then I lucked out in my groomer had some information for me and a path that I just wasn't introduced to yet. Exactly. So I was very very lucky that she was the type of person that said hey what's going on here and then she showed me the food that show dogs would eat. And I didn't think there was any difference. I mean the food company that sponsors the show is that not the food that the winner eats. No it's not. Most likely it's not. Not if they're the winner. Right. Now it's so interesting because my story is similar. I have a hairless Chinese crested and even on his papers it says he's pink and brown. And my sister jokingly said to me only you would find a pink dog.  But from day one he was throwing up every time he ate every time all this mucus would come out of him. Sure. So I ended up going through all these different foods and I was going to the typical pet stores where they sell the typical things. And I called his the person who I had gotten him from and she said no no that's perfect keep him on the food.  And she went there was a gasp. She went and she said no I didn't. So from day one he had had all these allergies. I took him. I got him tested by the vet and he's allergic to every protein. Every filler like oats barley corn potato like I'm like what am I supposed to feed this dog. So I started going to a health food store and I bought him ostrich. Oh boy. And he was okay with it but he was still responding and then somebody turned me on to you guys. Now he's already a year old at this point. A year old.  And I'm like yeah okay. I was willing to try anything and that's the first thing he could eat. That he did not physically react to. So thank you for that. Oh you're welcome. So your journey helped my journey and again he was the first pet I'd ever had. So like you I no idea about these things. Right. I think a lot of people don't they really don't know it's not something that you learn in school you know and you see the commercials it's so easy you just put the food in the dish and everybody's happy we ride around in convertibles and we're all good. Exactly. So tell me how did you go from learning about this food to starting this store with it. It was necessity in a way because we were driving out of town to get her food. My dog is not only allergic to fillers and certain ingredients she's actually the processing and a lot of animals it's the processing of the food. So we were trying different types of textures and things because of course I was afraid I wasn't into pet food you know the way I am now and you know it wasn't as if I was getting encouragement from the veterinarian I was working with. Oh yeah I was now going off of outside of him trying to find something because his his ending to my dog relationship was to be to euthanize my pet. He had actually said she's a year old you know so it's you know euthanizer she's no good start over and I wasn't going to do that. So that's where the processing came into play because I was feeding more natural kibbles without all the fillers because that's where I could find them out you know in the other area of the county and I started seeing results but not a hundred percent it's when I actually said okay you know what let's try the frozen and at first I was so afraid of it I fed it frozen I didn't defrost it I thought if I didn't defrost it not that stuff my vet said you know would come to be and the dog ate it anyway so it didn't matter and as time went on she started getting better and better so we ended up opening the store because I worked my husband had a window and door store and we worked the same hours that the store was open we were going to and we would be home at and relaxing a minute time to go feed the dog and oh my gosh I forgot to go pick up the food so it was really out of necessity I started going around Milwaukee County trying to find it there was nobody that sold the raw diet so my husband suggested we had a building on Blue Mountain that was kind of sitting idle a couple of things you know just weren't really working out and he said why don't you open a pet food store and I thought at first like yeah right you know but I literally went into the freeze freezer pulled out the bag of food I was feeding called 800 number on the back and said hey we're gonna open a store in Milwaukee how do we get your food that's literally how it started and they sent a rep in from Middle West which is one of my biggest distributors I'm still dealing with them they're a local Illinois you know but that's kind of local it's a close you know and they are small right you know so what really helps us pick our food is we like to deal with distributors that pick their food with our same mindset right I do have some bigger distributors I work with but I work with nine distributors to all together so that we can get the freshest food the different variety and a lot of them have the same mindset that we do you know we don't want the fillers we don't want the bad preservatives because you could have great ingredients and then the preservative just wipes it all out exactly you know yeah now I'll tell you when I told my vet I was feeding my dog raw they about fell on the floor oh yes I have to tell you it's been ages I don't know if anyone remember this like I did but my vet put a mr. Yuck sticker on my folder a lot of people do not know what mr. Yuck is mr. Yuck was a sticker that you put on all your products before they had those things that stopped the cupboards from being opened by kids yeah so you put mr. Yuck stickers on and during the cartoons they would be commercials mr. Yuck mr. Yuck I remember those yeah touch it and I was like where did you get a mr. Yuck sticker from and why is it on my folder all feeder he writes across the folder oh my gosh yeah and you know the funny thing is one of the vets that I went through in trying to find a remedy for my dog literally like my dog's allergic to chicken he's like feed him this food I'm like it's chicken he said but they hydrolyzed it differently I said does it come from a chicken because he's still allergic to chicken right and for 10 minutes and every time still to this day every time I take my dog in if something's wrong they're like we need to test him in case he got some back bad bacteria from your raw that is never it no it's no never it no they just don't get it because no why would the bacteria part of the animal be put into the raw diet to begin with they have higher standards they have much higher standards they're not gonna put that type of ingredient you know it's not even nutritious my sister's dog is outside killing birds all the time right they can handle how they eat if they were in the wild right they can handle a lot of the more natural you know like salmonella things like this a lot of the natural dog foods are getting recalled over things that don't even make the pet sick yeah you know a lot of times it's the humans not gonna wash their hands sometimes it's just they didn't have like enough vitamins you know in it and it's really sad that it can take one complaint on a natural food diet to get a recall where but other food companies have had issues for years and they just keep getting like away in court you know they drop the cases nothing happens there's no accountability yet you can find proof all over the place that certain products that are very popular are very deadly to pets yes especially but every day twice a day or just because your your vet is recommending it or it says that recommended we have to remember there was a time when doctors smoked and cigarettes were refreshing yes so now speaking of that I happen to know for a fact that you go through all the ingredients on a label and check out all the ingredients you look them up yourself the staff members yes yeah before you let a product come into your store yes many moons ago when my husband and I were the only employees we we did all of that but now we have excellent staff and it is their mission I can go to a trade show and I think everything's great and nope there's to integrate us on this back you didn't catch this you didn't see that you know we call companies what color caramel color are you using is it one two three or four because we know that it's the way it's extruded and two of the numbers are okay because they're extruded without chemicals and two of the numbers are not because they're extruded with chemicals and those are going to be the ones that are going to be the cancer causing carcinogens when all of a sudden done being cooked now we can't get the answer from that company which one they're using we don't sell that product and then we'll tell you that's why we don't sell that product but here's a product that's similar you know and it's up to you if you want to go to another store and find that product you know great we'll support you when you come in we're not gonna be upset but we will continue to educate you exactly and that's the most important thing right so how long ago did this journey start how long have you had the store now 11 years yeah snow bells 12 and the store is 11 years how that's that is such an amazing journey so now I've come in the store each and every one of your employees is trained on everything no not all of them but the ones that are on the sales floor the warehouse staff now if you happen to see JT stocking something he's not going to be able to answer that in-depth question but he's going to get someone who can yes he might be able to answer some basic questions but so everybody in the store is knowledgeable but not as in-depth as some of the questions might be so but we always make sure that somebody like myself or Lizzie or John or my husband is always there when we're open or at least reachable so if something does come in we can do our best now sometimes we might have to do some research you know but a lot of the issues that come in foundation of health you just really break it down to getting rid of all of the fillers getting rid of the processed food try to get on less processed food you know more of the real what that you were saying in the wild the organ meat you know less they don't need they don't have what it takes to break down those gabbanzo beans and the peas and the potato all that stuff your dog is allergic to yeah when do they eat it in the wild it's something we've added to replace the fibers and things from their the body of the prey exactly you know that's why raw is like so awesome it's like praying a bag you know we're missing of course some a coat and stuff but you've got the organs and you've got the nutrition without all that cooking so your animal is able to assimilate it without having to use all this extra energy because when they have to break down the kibble their body just doesn't have what it needs so the liver the brain the kidneys have to kick into the stomach whatever liquid they have or body fluids whatever you want to call it so it can break down with that kibble and the body works just so hard to do that that the organs you know they're gonna be exhausted before they need to be absolutely so yeah I mean if you can feed the closest you can to what they would eat if you weren't involved you're gonna create a foundation of health so that when like ear aches or things like that might have been around for your animal it was able to shrug it off because it was eating what it really needed to get that foundation of help have that you know strong immune system so that the body can say yeah get out of here exactly you know instead of hey come party with me I think it's you know we can compare this to humans where we can say if we're putting the proper nutrients in our body we're gonna be able to fight things off but if we're not putting the proper new if we're eating all preservatives and processed foods our body isn't gonna have what it needs to fight off the normal things that's right the things that we need to fight off hundred percent absolutely so one of the questions I have now your dog has allergies yes my dog has allergies feeding the right diet the most helpful diet isn't only for allergies though no no I know that I every time I walk in your store there's a number of people there what other remedies can be had from feeding your dog the appropriate food you can actually aggression issues and pets not really getting along there's a lot of sugar when you break down in your body is using the all those carbs carbs run into sugar same thing happens to our pets the carbs run into sugar well if you're hyped up all the time you're not exactly on your nicest game so you're gonna have conflicts within the home because maybe one dog's crabby the other wants to play you know where when you're on a diet that doesn't spike you up like that you might be a little more in you know to get along well maybe I'll play a little bit because I don't really know where so that really does help I know it seems weird but when we go to the different classes with the veterinarians they talk a lot about getting the unnecessary sugars out of the diet just like our kids you wouldn't give your kids a bunch of sugar and then be shocked when they started fighting you know the birthday party is great until all the cake and ice cream comes out you know and then the kids are crying and the time to go home and melt down right and we wonder why our pets are different you know and they're really not they're really not so let's say somebody just can't bring themselves to feed their dog raw and I get that some people just get they're too nervous about it they're too freaked out about it maybe their financial situation doesn't allow it sure what is the next best type of food that they can feed well raw raw diet comes in freeze-dried it comes dehydrated it comes air-dried I like the air-dried version because it's less processing canned food is an option we want to look for as many cans as we can without the PBA in the lining and stuff but even kibble because when it comes to cost when you're thinking about cost sometimes the like a freeze-dried the dehydrated actually gonna cost more free frozen is really the best inexpensive way to buy the raw products and the least process or the most healthiest but sometimes people will buy kibble and the raw because they have a big dog even if they have small dogs it depends what their budget is what you can do is you can take and put water in that kibble so if the only thing you can do today is afford some free water go home get some free water from your tap put it into your dog's food let it soak in let it puff up that way your dog is not breaking down all that carb that's such a great tip oh my goodness that is such an amazing tip now do you have a you know the canned food the soft versus the kibble do you have a choice there or does that not is it really not as important um canned food is always going to be the preferred between those two because they are it's less process it's easier to assimilate you don't have to break it down for them to you know because you do lose a lot in the cooking of the kibble right but canned food is gonna be expensive compared to kibble so really again if you just do what you can if you wet down your kibble turn into canned food and that's the best you can do that's what you do if you can buy some good quality can because buying a bad quality can isn't gonna help nutrition wise okay so you make sure you're looking at the ingredients we want real meats no byproducts no starches you know we don't want any bad preservatives you know because you're not helping so find the most inexpensive can you can that's healthy we can totally help you with that at the store we have clearance items all the time where you can stock up you know and most of the time dogs are gonna eat canned food most of the time cats are gonna eat it it's not gonna be an issue of they won't they're getting finicky a lot of times they get finicky cuz it's hard to eat the product it's hard for cats to eat dry food it's hard for dogs to eat dry food you imagine how you feel when you eat something that's not so great and you get kind of queasy we want to feel queasy twice a day every day no and the dog can't tell you I'm feeling queasy right now because a lot of times they push that aside cuz they want to play you know they got that survivor of the fittest going on so they're not gonna show you right away they're not feeling good unless it's an exact reaction where you know like they eat and they throw up well then you know that's pretty pretty basic that's yeah that's pretty basic there but the the the really main thing that you want to do is for your budget and for the health of your pet is you want to put your money into your pet not your vet you know right don't save your money don't say I'm gonna skimp here because then you're gonna be giving it there right so most people love their pets you know more than they love a lot of people so you might as well take your resources your love your time you know your money and put it into the animal you love instead of waiting for a problem and putting it into the veterinarian exactly and that's what we really help you do an affordable way one of our main goals at the store is to make natural foods affordable you can't feed it if you can't afford it exactly and you do I mean it is one of those things where also if you don't feed the just like humans if you don't eat the right things now if you don't feed the right things now later on down the line you're going to end up paying for it in veterinary cost in health problems with your pet or with yourself right now speaking of that let's go to treats okay everybody wants to give their dog treats and you see all these treats on commercials and one of the things that I love about your store also is because my dog can only eat duck mm-hmm you have pure duck like you have duck liver duck neck duck feet I mean every part of that duck is you and my dog loves it yes so tell tell tell me a little bit about some because I can only go in the duck area but I know you check your treats just as strictly as you do your food yes people give a lot of treats you're eating three four five a day I mean you customer will say oh I don't give many it's three four five a day every day you know sometimes that can have more effect than the food especially with the ingredients and stuff so yes again we go through I really like the meat-based organ-based body part based treats because that's again you're gonna go in for what they're gonna get in the wild you're gonna get more nutrition you're treating with a purpose you know if it's like the duck feet you're talking about help clean your dog's teeth I'm also is helping with go close to me because it's natural go close to me so it's gonna help with some hip and joint issues you know and you don't get that out of a lot of the treats that are on the market today I can have people come into the store and they're doing everything they can food-wise and it's something is just not jiving with the dogs not getting as well as you think or something's not dissipating like you think it would and it turns out they're feeding a low-value treat yeah or they're getting that treat at the bank every third day when they go you know and treats are so important you know do you have to be mindful with everything you put in your pet's mouth exactly exactly and you also offer a number of supplements and what I call is it a pedipathic area yes I love pedipathic area oh my goodness and some herbs some really good minerals and herbs and herb Smith very local types of different for everything from we have essential oils and we have the different they smell I can't think of the name right now but you smell them and they help and then you have all the tinctures we have powdered you know whatever way your pet needs to get it we have them in capsules and chewables you cook out even the slightly processed foods you're still cooking out a lot of the nutrients so to get it back in that's where the supplements come into play because you're getting it in and a good dosage right yeah the food can boast it's got good close to meat in it but the majority of it was cooked out right so really you need to add these supplements into the diets and as soon as possible you a lot of times puppy on you want to do the close to me and you want to do the enzymes and the probiotics you know because you got to get in there you got to keep the system going you can't keep your car running if you don't have oil in it exactly you know it's not gonna work you got to change that oil you got to change the air filter you know you got to do some maintenance you know so you have to stay up on the maintenance of your pet and for some pets it's a necessity they need some of if they start to get arthritis if they start to get some of that heart problem sure there are supplements for pets just like there are supplements to help people oh yeah we have kidney and liver supplements you know you've got heart supplements you have supplements that are good just overall like they've got some hip and joint they got some daily stuff they got some enzymes you know so we have individualized we have all together all different types what but the important thing is that the staff knows how to tell you which one to use for the condition you're describing exactly you know that's the big thing so let's out we just have a couple minutes left okay tell everybody where you're located sure we're at 5835 West Blue Mound Road the Tiley Road in Blue Mound in Milwaukee right and your website address is Milwaukee pet food calm excellent excellent Carrie I want to thank you so much for being such a magnificent guest and you more so I want to thank you because without you I don't know if I would have found what my dog needed when he needed it well he needed it right away I wish I would have found it sooner and that's part of why this show is so important to me too because there are so many people out there that have pets they have no idea what's like they know something's wrong with their pet right but their vet is leading them down the same road mm-hmm I totally think that need another door to open right right I'm so lucky I had that but that's a groomer in my life and I want to be my groomer to everybody else absolutely you know yeah the information has got to be there absolutely you're welcome thanks for having me my pleasure you have been watching create a life you love remember only you can take control of your life and take your passion turn it into your career and your purpose so what's burning inside of you what is it that you really are passionate about go out do it and make yourself have an amazing life this has been Tony Green you can reach me on my website www.tonig.info and I'm also on Facebook Twitter and a couple of other social media things that I can't remember thanks for watching have an amazing life


Everybody forced here ripping 20 22 origins football hobby eight box half case number three pick your team Got a shams of the Steelers Albert E. Cowboys Charles P 49ers Chris S. Titans Kurt S. Cardinals Derek you with the Panthers Thank you Derek for grabbing the Panthers at the end their last spot purchased Good luck, buddy. Eric are Seahawks GK Vikings Hamilton with the Bears James H. Chargers Jeremy L. Texans Jerry beef football team or commanders We have a football team still commanders John W. Broncos Carl T. Chiefs Kenneth P. Raiders Kyle B. Jets Long J. Colts Matt M. Lyons Matt S. Falcons, Matthias Rams Michael C Has the Dolphins Nicholas S. Eagles Rubin Saints Richard Packers Ross D. Bill's Bengals Ryan D. Giants Scott T. Bucks Sean M. A patriots Trey H. Ravens Vaughn with the Jags Who still misses MJD and Victor F with the Browns He might just all be on the same order Still misses Yeah, Derek big crowd coming your way buddy. Yeah, a golden corral maybe a golden corral We do need like a really low number on card. We do have that's a nice one The box of organs that I open for my personal had a Jamar on card. Yeah sick Got Jags James Robinson 170 of 199 a vikings Kirk Cousins 5 at a 299 captain Kirkman the Vikings looking good y'all They looking good Jets Elijah Moore and a rookie John Metzsche the third Texans rookie base Jets rookie patch here Breeze Hall 113 of 199 Texans on card rookie auto John Metzsche the third Go Texans Redemption going to the commanders rookie jumbo Jersey auto Brian Robinson jr. Yeah, I hope everyone's having a great morning Or it's just it's pretty much afternoon now. We're gonna have a great day We've got Chronicles draft basketball coming up random seems style hoping to pull a big palo or Matherin or You know Ivy obviously A lot of other good players to me and Keegan Murray Jabari Smith Chad Holmgren still gonna be a pretty sought after I think Chiefs Patrick Mahomes the second 32 of 199. Where did power go to school? Yeah, Texas Niko Collins 90 of 299 God Ram's Matt Stafford and rookie Devonte price cults Lions rookie Jersey card James and Williams 62 of 299 Cowboys on card rookie auto Jalen Tolbert I think it's Tolbert instead of Tolbert. It's Tolbert. It is.  Yeah, he pulled a handful of those.  Just like in Jack's all day and just feeling like all right Jags cards all day Getting your PC cards. Yeah. All right chiefs Clyde Edwards a lair numbered 180 of 299 Amari Cooper Brown 17 of 25 again. He's a beast Got Patriots from Andre Stevenson who's also playing very well and Kenny pick it rookie variation Steelers I think that's our first pick it today. We may have had a base in one of the other ones, but that is One of the only ones we've seen we haven't had a jersey to nice variation pick it Steelers rookie jumbo patch George Pickens 98 of 99 pickings and pick it. Oh, yeah Back to back for the Steelers Steelers box Colts rookie auto Alec Pierce on card And New Orleans a crystal Lave rookie jumbo Jersey auto Nice hit Saints Great receiver classes here, man. I'm ready to see some more rookie quarterbacks play though. I'm ready to see if they if they've got what it takes It's always fun being able to see if somebody's got it. I want to see Willis get some practice reps and get in I want to see Ritter see howl They're all on teams that don't have like very good quarterback situations either, so I think we're gonna see him down the double line here Yeah, once they're out of it Steelers yante Johnson 244 of 299 and Jets Michael Carter 72 of 199 Jags Trevor Lawrence rookie Jameson Williams Lyons Lions rookie jumbo Jersey Aidan Hutchinson 105 of 199 Buffalo got a James Cook rookie on card auto cook And redemption Kyle Hamilton rookie jumbo Jersey auto Ravens a lot of redemptions this half case Ravens Oh, thank you Mickey guys wait, I'm gonna check the next one make you sweat it out Panthers Niners Titans on half case for This is a lot though. It's like every tough one. It's it's every car though, so you're busy the whole time All right guys just checking here doing one more refresh It's two to go now. We just got purchased. I think the Niners just got purchased Yep, Panthers Titans left just Panthers and Titans All right, here's our dummy thick pack There's a book and three other hits They've done that twice now. Yeah These book ones are loaded man. All right, Bill's Josh Allen to 75 of 299 Jets Michael Carter 30 of 75 So just one base. It's a Hutchinson variation Lions Lions Almond Ross St. Brown origins proving ground auto 76 of 99 He's so good He's like the Silent guy from that draft just because they had so many other big names. He's a lion. Yeah, it's so good though He might be like third or fourth best receiver in that class Which is saying a lot because it's a class with waddle and chase Texans rookie patch John met you the third 27 of 75 Steelers book George Pickens 32 of 49 Big Pickens book Congrats Steelers That is a beauty. I love or is meant the colors on the books the colors on everything, but the books just really stand out There you go Steelers Big and Eagles rookie Jersey Auto Carson strong Nice nice You leave it out for now Show it again. All right base Connor and Wilson. We've got McAfrey 54 of 75 Panthers and Broncos 66 of 199 is Coralyn Sutton Titans rookie jumbo Jersey trail on Burke 17 of 199 chiefs rookie on Carlos sky more so huge on that one Somebody was asking for some sky Skymore and Jetsos Gardner RPA book 30 and not book but RPA 32 of 99 You go jets on the sauce Yeah, you're gonna have a nickname like as your name. Yeah, yeah, he's doing it Chiefs Mahomes 983 of 99 and Bengals chase 134 of 299 Kamara and Herbert Yeah, Garrett Wilson rookie patch card 45 out of 49 jets It's so weird I think they were trying to drive up its trade value by using him a lot and then it looked so much better It's like why don't you just run your offense through him that's on a regular basis, of course You don't understand how mad that makes me every week. I don't want to talk about that Patriots rookie Auto Pierre Strong jr. Number 12 at a 25 like tomorrow on my fancy team since his rookie rookie year That Corral rookie patch auto Panthers There you go Derek. Nice. There he is Matt Corral Sick. Oh last spot mojo right there The jerseys like coming up a bit. I was like is that yeah, it's like it's like folding underneath kind of Not even that's not the jersey behind Last spot mojo though So yeah, every time tomorrow gets the ball like more than 20 times they win and if he doesn't they lose And it's like you would think that they would see that trend falcons quarter-all Patterson 3 of 99 and Chargers Austin Eckler 158 of 299 God Deandre Swift and our rookie breeze haul variation jets There's Justin Fields nice patch 20 of 49 three color Oh Man every day happens every day every time I break day time. Hey McBride rookie Auto Cardinals 42 of 99 rookie signatures there and Commanders on the back rookie Jersey Auto Johan Datsun Solid break there. All right relics here. We had bears Justin Fields jets Garrett Wilson Titans trail on Berks Texans John Mechie the third Lions Aiden Hutchinson pick pickings for the Steelers there Lions Jameson Williams Jets Breeze Hall Autos now we had Matt Corral RPA Panthers Patriots Pierce Strong Jr. Chief Skymore Jetsauce Gardner Eagles Carson Strong Lions Amon Ross St. Brown Bills James Cook Ravens Kyle Hamilton Saints Chris Olave Colts Alec Pierce Cowboys Jalen Tolbert Jags Travon Walker Redemption Texans John Mechie the third Commanders Brian Robinson jr. Rookie Jersey Auto Redemption Cardinals Trey McBride and Commanders Johan Datsun. We also had It's been a good break in this stuff today also had a George Pickens RPA book to 49 for the Steelers And you go Congrats Steelers. Thanks again everybody. We've got more origins coming up


recording in progress. All right. So let's let me just start sharing my screen. One second here. All right. So again, thank you everyone for joining. I'm very excited to have you here. Quickly just going to go over our agenda. So we're going to go over the current state of the budget process. I think this is important. Some people already have an idea about where we are, but let's go over it quickly together. We're going to go over as well. What is our ask, right? So we're going to, we want to set up meetings with our congressional representatives. What are we actually going there to ask them to do? Having a very clear ask is important. We're going to go over understanding congressional advocacy 101. This is really where we're going to get down to some of the nuts and bolts of how you actually set up a meeting with your representative, the roles that you need during the meeting, and good follow up. And then we're going to go over our could be Congress toolkit, which everyone will have available to them. So we can go ahead and get started. So a couple of things just right off the top that's really important is we're hosting this training at an important time, right? So for the month of August, Congress members will be in district on August recess, which means that they'll be attending events in their district, largely online at this point, right? And are more likely to be available for meetings with constituents, right? So this is this is the ideal time to try to set up a meeting with your representative or and or their staff. So this is an opportune moment. Another reason why we're having this training at this moment and why we're talking to people about reaching out to their congressional representatives is that we're also at a very important moment in the budget process. So on the screen, I just have a small explanatory slide about what happens and how the National Defense Authorization Act moves through Congress. So if you don't know, Congress deliberates every year on the National Defense Authorization Act, which sets the military's budget for the following year. And, you know, while what's on screen might look a little complicated, put simply the House and the Senate vote to approve sometimes different versions of the National Defense Authorization Act, which then have to be reconciled and set up for a final vote, which is then sent to the president to approve or veto. The only thing that we need to know right for this process at this moment is that the last four steps of the process are where we can really actually speak out, talk to our Congress people, make sure that they know our opinion about the National Defense Authorization Act, and we'll talk a little bit about what that is, right? So I've just put a red arrow where we are currently in the process. You can see it here. If you see there, this typically occurs in late April or May or in August. Things are extremely delayed this year for a variety of reasons, but that's okay. I mean, that means during August recess, we actually get a chance to go and talk to our representatives about the National Defense Authorization Act. So where are we? What is our opinion on the National Defense Authorization Act? Well, it's important that we know a couple of things that have happened very recently. So in late July, the Senate Armed Services Committee voted to raise the baseline Pentagon budget to $740 billion and compared to 2021, which was $715 billion for the baseline budget, that is a large increase, right? And that is an increase even over what President Biden requested the Pentagon budget to be, right? So the Senate Armed Services Committee said, President Biden, we see your request for increased funds. We're going to add even more funds onto that. And this was big news. You might have heard of it. But I think a lot of what's seen in the news is people say, oh, okay, well, it's inevitable. We're going to increase the Pentagon budget. It's inevitable because the Senate Armed Services Committee said so. Not true, actually, right? And that's why it's important that we understand the National Defense Authorization Process. The Senate Armed Services Committee might have increased the baseline budget, but that doesn't mean that that's going to happen. That is inevitable. The House and the Senate must agree on the final defense bill. And this is where we come in, right? Going and reaching out to our Congresspeople in this moment is exactly what we need to be doing, right? Because it's really urgent that we show our representatives that there cannot be an increase to the military budget. We're still in the middle of a pandemic and, of course, economic crisis, as we all know. And it's just completely unacceptable to even begin to consider adding any money to the Pentagon budget, let alone $37 billion, right? So this is not inevitable. That's why we're here today. And in brighter news, better news, actually. Another thing that's really important about where we are in this moment is that some progressive champions in Congress who consistently worked to slash Pentagon spending like Representative Barbara Lee recently introduced House resolution 476 to cut $350 billion from the Pentagon budget and reinvest in our communities. So this is legislation that would do exactly what we want to do, right? Which is take much larger amounts of the Pentagon budget that we currently have and put that towards green jobs, healthcare, you know, green infrastructure, things that we actually need at this moment. So Congresswoman Lee introduced this legislation last year and received 26 cosponsors. This year, there are only four cosponsors on the bill and they're on the screen. You'll notice some Congress people you'd expect to see listed as cosponsors aren't there. And this comes down to the fact really that they've been busy probably and they haven't been reminded or directly asked by a constituent to cosponsor the bill again, right? So which I think is another key reason why we're setting up meetings with and developing a relationship with congressional representatives is so important, right? I think people sometimes don't understand that the Congress people sometimes are just busy and that's why they haven't done it. So it's, you know, on us as people who are dedicated to peace legislation that will actually make a real difference to make that ask of them, right? Making sure that bills that we wholeheartedly support receive the congressional backing that they should, right? So I went over a lot there obviously, but I just want to be clear and just summarize our asks very simply. When we're in these meetings with our congressional representatives, we want to do three things that are extremely important, right? No new funding for nuclear weapons, which is currently in the National Defense Authorization Act, reduce the Pentagon budget by at least 10% and cosponsor House Resolution 476, which is Congresswoman Barbara Lee's legislation to cut Pentagon funding by $350 billion. Does this mean obviously that your congressperson will agree to all of those things? No, not necessarily, but these are the important things that we need to be asking our congressional representatives. So I see someone raised their hand. If you could post your question in the chat box and we'll make sure that any questions that people have are going, we'll answer them at the end here. So those are some of our asks and this is what's important that we understand when we go into these meetings. But now I just want to talk about a couple of tips and resources and tools that will help you set up a meeting with your congressional representative. So I'll just go over these general tips and resources and then like I said, we're going to go over our Code Pink Congress toolkit. So first thing, I do want to emphasize how important constituents are in the advocacy process that we're going to be talking about, especially constituents who take time to meet with their representative in person. I do want to emphasize how important that is, because actually taking the time to go and meet with them, they don't often get people who meet with them about specific bills, especially the bills that we're talking about. So it does make a big difference. And I do want to just give one example of something that we did with Code Pink and some coalition partners. So just a really short anecdote in 2019, we actually met here in Los Angeles with Kamala Harris's, then Senator Harris's staff to co-sponsor Senate Bill 1039, which was just legislation to prevent a war on Iran. And our group was made up of constituents and members of the Iranian community in Southern California. And we set up a meeting with then Senator Harris's office with a very clear message, right, that there should be no war with Iran and that the sanctions that are devastating Iranians should be lifted immediately. Those were our two main points of the meeting and we stuck to those points very clearly and made the hard ask of Senator Harris's staff to co-sponsor Senate Bill 1039. So after meeting with her staff, we followed up with a nice email asking for any updates, right? Thank you for meeting us with us. Again, we want to reiterate our points. Please let us know when you will co-sponsor this bill, right? We then engaged our community in a social media place, right? We were calling on Kamala to co-sponsor the bill, right? So we have the meeting and then we have people tweeting on her, emailing her and even calling her to co-sponsor Senate Bill 1039. And, you know, people, countries of people were taking that action and were watching to make sure that she did it, right? And after meeting with our staff and doing that short social media action, we finally got the confirmation that Senator Harris would co-sponsor the bill calling for no war on Iran. And before we went into that meeting, she was very much against co-sponsoring the bill. She wouldn't give us a straight answer. And after our meeting, after with our solid follow-up, right, and with a coalition of constituents with a clear ask, right, we were able to successfully get her to co-sponsor that bill. And she was extremely necessary that she co-sponsored that bill in the Senate because she was holding it up. So, you know, I think it's really important just to remember that a strong coalition of constituents with a very clear ask, like the one that we're talking about, can change their congressional representative's mind on an issue by demonstrating that people they represent care about the issue and are willing to follow through on their promises to take public action in support of legislation, right? So, I think that's a really important lesson for us to keep in mind when we're talking about this. So, okay, that's, you know, important, and we understand the importance of that. But how do you actually set up a meeting with your local representative, right? What are the actual nuts and bolts? And this is, this is equally important. And we're here to demystify the process, right? So, the first thing you're going to do is contact the scheduler. So, once you get in contact with the congressional office, and we'll show you in just a minute how you actually do that using our Code Pink Congress toolkit, but you're going to contact the scheduler and be ready to provide them with the information that's on the screen, right? Which is who you are and where you're from, the issue that you would like to address during the meeting, a desire to meet with the congressperson or a relevant staffer, right? And importantly, your contact information, right? So, this is not something that you have to memorize, because we've actually already written out very clear, very easy to follow sample emails you can send to your congressperson's scheduler. So, you'll see some of the elements of the email that I just referenced are really clearly laid out, right? So, as a member of Code Pink, you're telling them who you are. A grassroots women's anti-war organization, I'm writing to request a meeting with you and your aides to discuss your representatives' name, recent vote on legislation, which could have cut the Pentagon budget by 10%, and then you'll see all of this information that you need. I'll be available to meet with you at your location office, right? So, you want to make sure you specify that you're available to meet with them in their office. They'll likely want to set up a Zoom meeting, but whatever you want, you know, just making sure that they're clear, you want an in-district meeting. And then, this is extremely important, including some dates that you would be available to meet, right? This is important for the scheduler because they can get back to you then with some specific yes or no on those dates.  So, this is a really good sample email that includes all of the information that I referenced before. So, what happens after that? Usually, what happens is you have to follow up with a phone call because they don't always respond to you, and maybe you all have had that experience that people haven't responded to your email. So, following up with a phone call is extremely important, and it's a lot harder to ignore a phone call, right? And so, similarly, we have a sample phone script that you can actually follow and use, of course, insert the important information that you need to. And we even, you know, prepared for the almost inevitable response from the office, which is that they're not available on those dates. So, that can happen, right? They'll say they're not available. Okay, great. We already have a response ready, right? Which is, could you let me know some dates that the congressperson or staff person might be available, right? So, again, we're not going to let them off the hook and just let them say we're not available. Sorry, right? Okay, let's find the time when they are while we're on the phone. This is really important as well. So, then, you know, we have scheduled a meeting. Hopefully, you've found a time and a date that works for everyone. And then, of course, you have to prepare for the meeting, right? So, these are a couple of things that are important when considering how to prepare for a meeting, and I'm going to go over them. You'll see them on the screen. So, the first is research congressperson's stances on the issues, right? So, if you're their constituent, you might know some of their stances on the issues that we're talking about. One clear thing you could do is look to see if they've already co-sponsored Representative Barbara Lee's House Resolution 476. It's likely that they haven't since only four representatives have, right? But otherwise, right, you can look at their background and use that might be relevant to the issue. What is their foreign policy view in general? What committees and caucuses do they serve on? Right? Just being aware of some of the congressperson's stances and power, right? In actual, in congress. And then the second is discuss a clear ask to make of the congressperson. We've already done that, right? We have three very clear asks that we want to make of the congressperson that they can say yes or no to, right? I can't emphasize enough how important that is. So, the meeting doesn't feel like it's sort of meandering, right? You actually have very clear asks, will they do this? Will they support cuts dependent on budget? No new funding to nuclear weapons and Barbara Lee's legislation. So, that's extremely important. Discuss roles and order of speakers. So, this is something we're going to get into in just a minute here. But you want to make sure that you always have someone to who's there on the call who has a clear understanding of who is doing what. We'll get into that in just a second. And then finally, prepare resources to leave behind. This is also important, right? So, you had a conversation with your congressperson or relevant staff members. And after that conversation, you want to make sure that you follow up either with some talking points that, you know, are relevant to your conversation, in this case about the Pentagon budget. And also, right, make sure you follow up with an email that we'll discuss as well in just a second. So, those are some good things to keep in mind when preparing for a meeting. And again, we'll have all of these slides available to everyone so you can go back and review them as well. Okay. So, like I said, once you're in the meeting and you're actually speaking to the congressperson and their staff, it's very important to assign very clear roles for everyone to ensure that it runs smoothly. They have a clear ask of the congressperson. And then it's not just all over the place, right? I'm sure everyone has been in a meeting like that. So, there are, you know, four roles to keep in mind. This doesn't mean that there has to be four people in the meeting. One person can take on several walls if you need them to. But these are sort of the distinct things that need to get done in the meeting in order for it to be successful. So, there's facilitator, constituent, closer, and note taker. And like I said, right, there doesn't have to be a distinct constituent, right? If everyone in the room is a constituent, fantastic, right? That's what we want. But to make sure that it's clear that you are their constituents and they should be listening to you, it's very important. So, let me just have a little bit deeper into each of these roles. So, the facilitator, so this is an extremely important role that someone can play in the meeting, right? This is someone who's going to keep the discussion moving, making sure that you're steering the conversation back to the main ask always, right? This is someone who is going to confirm how much time you have for the meeting, right? So, we'll say, okay, we have 30 minutes for this meeting. That means when we introduce ourselves, we won't take very long, right? That means when we're making the asks, we're not rambling or meandering. We have to get straight to the point, right? The facilitator is also someone who starts the meeting, right? And thanks to the office or the congressperson if available. Thanks to them for something positive they've done. If that's available, if not, that's okay, too. And then also, very clearly, open by clearly sitting in the main ask, right? We're here to ask the congressperson to commit to voting against an increased Pentagon budget, voting for a decreased Pentagon budget, voting against any new nuclear weapons. Very important that the facilitator is the first person to make sure that the ask is set at the beginning. And then from there, the facilitator will be the person to go around and ask everyone to briefly introduce themselves if there are multiple people in the room with you, right? Again, as a facilitator, it's your job to make sure that the meeting is running smoothly and making sure that the meeting stays on track, right? So that's the role of the facilitator. Next, like I said, the constituents are important because they're there to tell their story and why they're there as constituents and why it matters to them that the congressperson actually signs on to or commits to a certain action, right? So again, of course, as we know, right? Congresspeople are going to listen to constituents because they're there to represent you, right? But also, this is a good time to include constituents who might be representatives from local organizations. So in the example that I included, right? Code Pink really led the way on asking Senator Harris to co-sponsor that Senate legislation. But in the process, we wanted to include other constituents and other voices in the community who she might not have heard from. So in this case, members of the Iranian community in Southern California. So that can also be very important. And like I said, this is not necessarily a distinct role, but as long as you have people there who are their constituents and can speak to being a constituent, is very important. And then the final two roles, fairly simple. The closer, right? This person can also be the facilitator. But before the close of the meeting, you want to make sure that you reiterate any of the asks that you're there to talk about, right? So just saying something as simple as I hope you will vote to cut the Pentagon budget by 10%, you know, that's why we're here. So after listening to all of these people's reasons as to why they should support this legislation or co-sponsor this legislation, you need to be clear this is what we need from the Congressperson. The closer can also make sure that you, you know, if there are any questions that they will get back to them about those questions. And just making sure that the closer is available for any questions that the Congresspeople or the office has. And then the note taker, I think this is something that people can sometimes forget to include, but is actually incredibly important. A little, you know, we touched on this earlier. But the note taker, somebody who should take notes of the main points of the discussion, obviously, right? Understanding any objections that the Congressperson might have raised, any talking points that they were using, right? We'll often hear economic reasons against cutting the Pentagon budget. Well, we actually have counterpoints and things we need to respond with after those kind of arguments are made. So making sure we understand the nature of why a Congressperson might disagree or refuse to sign on to something is just as important as understanding when they will actually sign on. And then finally, right? The note taker can also sort of take note of body language and tone in the meeting. As I'm sure you've all been in a meeting where you can tell, right, based on body language or tone, if the staff or the Congressperson is reticent to really sign on to something or commit to an actual action that they're wanting to take, you should really take note of that. Or if the questions that they're asking are genuine, right? And they're just, they just want more information. So including both the substance of what was said and also some of the body language and tone is incredibly important for the note taker to take. So those are some of the key roles that people can play in the actual meeting. And then after the meeting, and I've said this, but incredibly important after the meeting to do follow up.  So, you know, debrief the meeting together, obviously not within your shot of the staff person. If you're in person, don't do it in the hallway. If you're on a Zoom meeting, definitely make sure that the staff person has left the Zoom meeting. Discuss follow up steps and be clear on who is doing what, right? So that's when you're going to designate someone to write a brief thank you email to sign off on, right? You want to make sure you send an email to the staff person reiterating your asks, answering any questions they might have had. Maybe this is the time that you include some of the talking points that will give you around the Pentagon budget. And then discuss, you know, making sure that you get a hard, you include a hard question to them, which is will the Congressperson do the things that we discussed, right? Because that follow up email, the point of that is to make sure that the staff member knows that they need to respond to you, right? It's not just a thank you, we appreciate your time. It's will the Congressperson do this? So that's incredibly important. So just a quick overview of a couple of things that we've done that we've gone over. And I think some of the main questions that people have or how sometimes people feel uncomfortable or a little bit stressed about doing this, right? So some of the dues that we should focus on is focus on the main ask and repeat it often. I know I've said that many times I sound like a broken record, but there's one thing you take away from this is that. And the facilitator, this is really important. If you feel like the conversation is getting sidetracked off task, it is your job as the facilitator to make sure that the conversation actually comes back on track that you reframe the conversation in a way that's helpful, right? So not just letting people ramble, you do have to sometimes step in, if necessary. And then some other dues, it can be helpful and nice if you can take a photo with the congressperson if they're there and share on social media. That's not always possible. And then just some of the don'ts, right? I mean, I said this, but don't feel intimidated. It's something that, you know, the congresspeople are there and their staff are there to talk to you. So don't feel intimidated. If you go in with clear asks, you'll have a much better meeting than many people who go into the congressperson's office. Don't make up an answer if you don't know it. It's okay to not know. Just say that's a good question. We'll get back to you, right? Don't get sidetracked, like I said. And don't get defensive. I mean, you know, obviously, in some of these cases, we'll disagree vehemently with some of the reasoning that congresspeople or their staff have for not supporting a cut to the Pentagon budget. It doesn't really help us to be defensive in the meeting. So just a quick overview of what we just went over. It's a lot of information. Again, everyone will receive it at the end. To review, right? At the end of the day, meeting with your congressperson and their staff is being as persuasive and consistent as possible. So that means introducing yourself, making the core ask, making sure that you have a reason behind that ask, right? Like, I'm a constituent. This matters to me for these reasons. Support that ask with facts and we'll give you all of the talking points that we have around reducing the Pentagon budget. Say thank you. And then if you can request a virtual photo. So I'm just quickly now going to do one final thing, which is go over what our toolkit consists of. So we have this online and it's very helpful. So I just wanted to quickly review that for people. And I'm just going to open it on my screen. Second. Can people see it now? I just dragged it onto my screen. Now you can't see it. Let me stop screen sharing and then go back. Give me a second. Okay. Can people see it now? Yes. Okay. Thanks, Allie. Appreciate it. Okay. So this is something everyone will have, but this is actually really key, right? I mean, all of the things that we talked about, these are really good things to keep in mind. This is how you prepare for a meeting, but how do you actually contact your Congress people and who do you contact? I think is a question that is very important that we address, right? So like Allie posted in the chat, you'll have this available to you, but I just wanted to quickly go over some of the elements. So on our website, we have a few tools that are always available. So first things first, which is really important is our contact Congress tool. So if you just toggle this button here, you'll see that you can actually contact House and Senate staffers when you click on this link. So we're going to take it. It'll take you to a hyperlink outside of our website. This is from our friends at FCNL who are having this excellent resource for us. Let me let it load. Okay. Fantastic. So hopefully people can see what I'm seeing on my screen, which is the information for different Congress people. We're now looking at senators. You can also look for Congress people, their phone number, their scheduler's name and contact information. So that's really important. So all of these conversations that we've been having, who you're reaching out to, who you're going to send the email to to actually set up a conversation with your Congress person, you're actually going to email the scheduler, right? So that's the person that they have all the information on. And sorry, that's where you can find that information here, right? And then importantly, they have their office's phone number. So this is the phone number that you call if you need to to, you know, make sure you have that follow up phone call with the office to set up a meeting time and date. I do this fairly often. We're going to have a conversation with Congressman Polkhan very soon. I went through that same process. I emailed the scheduler, and then I'm now going to do a follow up phone call. It works, right? It's actually something that works fairly simply. So that's important resource that you all have on this on this web page here. And then you can also see you can contact house staffers as well. So hold on one second. I'm going to let this load. Fantastic. So you can see also here, they have more information by states of different representatives in each state and who you can contact there, especially if you know the scheduler can't get won't get back in contact with you, right? So I would scroll down to California. Of course, we have so many representatives in California. And I would find my representative here is Barbara Lee. You can email their chief of staff, their legislative director or the communications director. So if you need to, you can email these people as well. So this is really important and helpful information. And this is all contained here on this web page at code pink dot org slash Congress schools. So one last thing, I just wanted to show people on this web page. If you toggle down here to track legislation, of course, it's not all legislation that's available in Congress, but this is legislation that we're tracking. I could pink so any basically any legislation that's related to to war and peace, we're tracking it here. You can see here House Resolution 476. This is Barbara Lee's legislation that we talked about today. If you click on it, it'll take you right to Congress dot gov where you can always find information about legislation. And then of course you can also see who's cosponsoring the bill. And that's where we have those four Congress people for so far cosponsoring her bill. So that's extremely useful. And that is always up on our website and constantly being updated. So I want to now stop screen sharing. We have about 20 minutes, 10 minutes left, 12 minutes left, sorry, in in our training today. So I wanted to see if there were any questions from people here. I'm going to go ahead and pause the recording here so we can just talk pretty freely together. So let me go ahead and stop recording.


Okay, so this is the last one, last trained mug bill. Today I'm working on 12 ounce mugs, they're a six and a half inch cylinder throw, I make a bucket full of mug pugs and I put them on one at a time and make a mug.