Hello, my name is Kevin Clues and I'm a Distinguished Engineer at NVIDIA. I'm here today to talk about a new Kubernetes feature called Dynamic Resource Allocation that will enable us to unlock the full potential of GPUs for AI workloads on Kubernetes. As a community, we've already built a solid foundation for GPU support in Kubernetes, and Dynamic Resource Allocation is the feature we've been waiting for to take us to the next level. So what does GPU support in Kubernetes look like today? Well, it requires a mix of host-level components, as well as Kubernetes-specific components to be deployed on each node of a cluster that contains GPUs, where the host components consist of the NVIDIA container toolkit and the GPU driver itself, and the Kubernetes-specific components consist of those shown here, where the K8's device plugin is the one that ultimately makes the GPUs themselves visible to Kubernetes. With these in place, requesting access to GPUs takes the form of an extended resource called NVIDIA.com slash GPU, and specifying how many GPUs you want access to. Under the hood, the scheduler, Kublet, and K8's device plugin will coordinate to find a node where GPUs are available, schedule the pod there, and inject the requested GPUs into the container that requested them. If you need access to a specific type of GPU, a combination of node labels and node selectors can help direct the scheduler to a node containing the specific type of GPU you are looking for. In this case, an A100 with 40 gigabytes of GPU memory. You also have the ability to request a fraction of a GPU through a technology called Multi-Instance GPUs, or MIG for short. In the example shown here, we're requesting a MIG device that is 1 eighth the size of a full A100 GPU using the canonical naming convention of MIG-1G.5GP. In the last year or so, we also added support for sharing access to GPUs through oversubscription. On a per node basis, cluster admins can configure the number of replicas they wish to oversubscribe each GPU, and users request access to these shared GPUs with the special dot shared extension shown here. Under the hood, simple time slicing is used to swap one workload off and put another workload on the GPU after some fixed amount of time. And this can be layered on top of the fractional GPU support provided by MIG as well. We also provide an alternative to time slicing through a technology called Multi-Process Service, or MPS, which provides a software solution for running multiple jobs on top of a GPU or MIG device in parallel. Unlike time slicing, however, there are some caveats to getting it to run properly, as well as some extra burden on the cluster admin to configure it properly. With some changes to the system software, GPUs can also be made available to virtual machines such as Kubevert and Cata. Instead of running the NVIDIA GPU driver directly on the host, it has instead run inside each virtual machine individually with the standard Linux VFIO driver making the requested GPU hardware visible to each VM. OK, so if that is what we can do today, what can't we do? Or at least not do very well. Well, first and foremost, there is no support for having more than a single GPU type on a given node. As I mentioned before, node selectors can be used to direct the scheduler at a node that has a particular type of GPU, but that node itself must have a homogeneous set of GPUs to pick from. We've talked about enabling support for this by allowing admins to customize the name of the extended resource used to advertise each type of GPU on a node. However, the names start to get overly complex and long, the more properties you encode in them, and we've never been able to agree upon the right way to do this, so it just hasn't happened. One of the most requested features we get is the ability to ask for a GPU subject to some complex set of constraints, such as its minimum CUDA compute capability and or the total amount of memory it has available. Unfortunately, node labels are not sufficient to encode all of the constraints that users find useful, and attempting to encode them in the name of the resource itself has the same problem mentioned previously with supporting more than one GPU type per node. Providing users with the ability to oversubscribe GPUs and share them among containers was a huge win for many of our customers. However, there is no way to control exactly which container will get access to which replica of which GPU, limiting the overall usefulness of this feature for users with more stringent sharing requirements. Sharing via MPS has these same problems, with the additional caveats mentioned previously of requiring a host-level controlled daemon to be running, as well as requiring all pods that access GPUs to be run with host IPC enabled. I didn't go into the details of this before, but there is currently no ability to dynamically provision MIG devices based on incoming resource requests. There are tricks you can do to add some level of dynamism to this process, but they are all shoehorned on top of the existing device plug-in API and involve complex logic to trick Kubernetes into doing the right thing, meaning that the official case device plug-in for GPUs simply doesn't support this feature. There is also no way to dynamically associate some GPUs with the native NVIDIA GPU driver and others with the VFIO driver such that a mix of containers and VMs can be run on the same underlying node with GPU support. It's technically possible to split the GPUs in this way. We just don't have a good way to do it dynamically based on incoming resource requests in Kubernetes. And with the advent of confidential computing and the hardware support we have for Inhofer GPUs, this is becoming an increasingly common ask for many of our customers. And as you can imagine, the list of limitations goes on. But this is where dynamic resource allocation comes in. In addition to supporting all of the existing use cases covered by the GPU support we have in Kubernetes today, our DRA Resource Driver for GPUs addresses all of the limitations mentioned as well. And the rest of this talk is dedicated to showing exactly how this is done. So we'll start off by giving a brief overview of DRA itself followed by the specifics of the DRA Resource Driver for GPUs we have implemented at NVIDIA. I'll then jump right into a series of demos showcasing some of the more advanced features provided by this driver. As its name implies, DRA is a new way of requesting access to resources in Kubernetes that has been available as an alpha feature since 126. It provides an alternative to the existing count-based interface of asking for NVIDIA.com slash GPU2, for example. And what makes it so powerful is that it puts full control of the API used to request resources directly in the hands of the vendors developing drivers against DRA, where the key abstractions to keep in mind are that of the resource class and the resource claim, which are in-tree APIs referenced directly within a pod, as well as their corresponding class parameters and claim parameters, which provide a means for vendors to bring their own custom APIs to these abstractions. In this talk, I won't go much further into the details of DRA itself and how it works under the hood, but I encourage you to watch my talk from KubeCon EU last April if you'd like to learn more. Okay, so assuming a cluster admin has enabled DRA and deployed the necessary DRA resource driver for GPUs onto a cluster, what does a user actually have to do to request access to a GPU? Well, starting from the example we used previously of requesting access to two GPUs, the equivalent request under DRA would look like this, where instead of requesting the two GPUs from an extended resource called invidia.com slash GPU, you instead create a resource claim template object pointing to the GPU.invidia.com resource class. You then reference that template twice inside a new resource claim section of the pod spec, give each reference a local name, in this case GPU0 and GPU1, and then reference those claims from within a new resources.claims section of the container spec. Since this is a template, each reference will trigger a unique claim to be created under the hood, resulting in each reference pointing to a unique GPU, just like we had with the traditional extended resource interface shown on the left. Now, this may feel overly verbose for the simple case of requesting exclusive access to a set of GPUs, but separating the declaration of the resource claim from its consumption means that we can naturally enable sharing of GPUs in a controlled way. In the example shown here, we reference a single resource claim for multiple containers within a pod, resulting in both containers getting access to the same underlying GPU, and by directly creating a global claim object as opposed to a template, we can reference this claim for multiple pods, providing a natural mechanism for controlled GPU sharing across pods as well. Now, this takes care of the limitation mentioned previously of not being able to control how oversubscribed GPUs get shared, but what about the rest of the limitations? Well, if you remember, I mentioned earlier that one of the most powerful features of DRA is the ability for vendors to define their own API for requesting resources, and this comes in the form of class parameters and claim parameters attached to resource classes and resource claims respectively, where resource classes are used to define the set of available resources themselves, as defined by a cluster admin, and resource claims are used by end users to ultimately request access to those resources. Since this talk is focused exclusively on the end user experience, I won't go into the details of the class parameters provided by NVIDIA's DRA Resource Driver for GPUs, but in general, they work similarly to the claim parameters I'm about to describe. So what do these claim parameters look like? Well, using the examples of the resource claim and resource claim template from before, you can basically just tack on an extra section to these objects called parameters ref, which pointed an object that the DRA Resource Driver for your specific resource type knows how to interpret, where the simplest claim parameters supported by NVIDIA's DRA Driver for GPUs looks like this. A CRD called GPU claim parameters with a count of how many GPUs you want allocated to the claim, meaning that an alternative to our original example of requesting two GPUs being injected into a single container could have looked like this, where our claim parameters object declared that we want two GPUs to be allocated to the claim, and we plumless through the resource claim template referenced by the pod. Okay, so how can we expand on this claim parameters object to knock out the rest of the limitations listed previously? Well, let's start with this one. Better support for MPS. A sharing section can be included that defines the strategy with which GPUs allocated to this claim should be shared. And one of the strategies that can be selected is MPS, where an optional set of parameters can be provided to customize how the MPS server does its partitioning. And that's basically it from an end user's perspective. As part of allocating the claim, an MPS server will be automatically started in the background with the parameters provided and torn down once the claim has been deleted. Now, it's also worth mentioning that the default sharing strategy of time slicing can also be provided here in order to customize the duration of the time slice used. Where the values of default, short, medium, and long map directly to the inputs you would provide to NVIDIA SMI to control this from the command line. Now, the next ones we'll take a look at are these two. And since the same set of fields in the GPU claim parameter spec will allow us to overcome both of these limitations, we'll consider them together. Where the basic idea is to define a selector field, which can either contain a single property, such as the GPU model you would like allocated to the claim, or a list of properties anded or ordered together recursively up to a nesting level of three. As a concrete example, consider the following selector, which reading from top to bottom says, give me either a T4 or a V100. And if you give me a V100, make sure it has less than or equal to 16 gigabytes of memory. Such a query would be useful, for example, to find an appropriate GPU to run an inference server on. Now, the set of constraints that can be provided here are basically anything you would be able to query about the GPU using NVIDIA SMI. And under the hood, the DRA driver for GPUs will not discriminate where these GPUs come from, meaning that you can now place different types of GPUs on the same node if desired. Now, these last two limitations are interesting because we've chosen to overcome them a little differently than the others. Specifically, by introducing a different claim parameters object than the standard GPU claim parameters object we've been working with so far, where the MIG claim parameters object has a single field representing the MIG profile you would like to have allocated to the claim. And the VFIO GPU claim parameters object has a single selector field, which is the same as the selector field available to standard GPU claim parameters objects. Whenever a claim is allocated, it references a MIG claim parameters object, a GPU capable of dynamically creating a MIG device of that size is found, the MIG device is created and then bound to the claim. When the claim is then later deleted, so is the MIG device. Freeing the GPU up to create MIG devices of different sizes or be used as a full GPU again, depending on future incoming requests. Whenever a claim is allocated, that references a VFIO GPU claim parameters object, a GPU matching the specified selector is found, swapped off of the standard NVIDIA GPU driver, onto the standard Linux VFIO driver, and then bound to the claim. The details of how the runtime that ensures that these GPUs eventually make their way into the VMs is out of scope of this talk. But all of the necessary annotations required to do so are added by NVIDIA's DRA driver for GPUs as part of the overall claim allocation process. And with that, we've been able to demonstrate how DRA can help us overcome the primary limitations we have with supporting GPUs and Kubernetes today.  This last part about the VFIO GPU claim parameters, we do plan to add support for this soon, but we are currently focused on getting a proper release of the rest of the features out, so it won't be available until some time next year. And with that said, here's where you can go to download NVIDIA's DRA driver for GPUs and start playing around with all of this today. The driver itself is deployable as a home chart and we have scripts to get you up and running quickly in both kind, assuming you have access to your own GPU hardware, as well as on a GKE Alpha cluster, which allows us to actually make use of DRA in a managed Kubernetes cluster, since GKE Alpha clusters enable all Kubernetes feature gates by default. In fact, we've used these scripts to set up the demos I'm about to show you now. Where the first demo runs within a kind cluster on a DGX-A100 box with eight A100 GPUs available, and the second two run on a GKE Alpha cluster with two different GPU node pools available. One containing a set of T4 GPUs and one with V100s. So let's get started. This demo shows some of the advanced GPU sharing features enabled by NVIDIA's DRA resource driver for GPUs. In particular, it shows how one can request access to a hardware partition GPU as opposed to a full GPU, and then layer a sharing mechanism on top of that that lets you further subdivide its resources among multiple clients. Each hardware partition is referred to as a MIG device, and the sharing mechanism, called MPS, relies on having a dedicated server process launched to service each client. When directed, the NVIDIA DRA resource driver for GPUs will dynamically create one of these MIG devices and launch an MPS control demon to service its shared clients. So jumping over to the code, we can see three windows. The first contains a job specification with its parallelism set to four. This means that four separate pods will be launched as part of this job. Each pod then has a reference to a resource claim called MIG MPS sharing, which in turn is referenced by the single container embedded inside it. This container simply invokes a long running and body simulation designed to keep the GPU busy throughout the demo. Now moving over to the second window, we see the actual specification of the resource claim itself, followed by the third window, which contains our custom claim parameters object, populated with the settings needed to request the smallest MIG device possible with MPS sharing enabled. Now to make this demo a little more interesting, we're not going to launch this job with just this single container inside it. Instead, we're going to run it alongside three other containers, which provide a baseline for the feature it is demonstrating. The first is a full GPU with standard time slicing enabled rather than MPS. The second is a full GPU with MPS sharing enabled. And the third is a similarly sized MIG device with standard time slicing enabled. As before, we have the claims to represent these as well as the claim parameter objects to define their settings. Okay, so now for the interesting part. Let's start off by showing the current state of the cluster, which shows that we are running in a single node setup with our DRA resource driver already deployed. Next, I'll show the current state of the machine in terms of how GPUs are partitioned. At the moment, there are no partitions created and we simply see eight full A100 GPUs available for allocation. Now let's go ahead and create a namespace to run our demo in and launch our job in its associated claims. Now that that's launched, we can run kube control get a few times to wait for all of the pods to show up. As you can see, there are four pods associated with the job and two dynamically provisioned MPS control demons just as we would expect. With this next command, we can see that two MIG devices have been dynamically created inside GPU four as well as all of the processes from our end body simulation running across all of our GPUs and MIG devices. To get a closer look at the processes associated with each device, I'm going to run a script that parses the output shown here to grab a reference to each of the four devices that have been allocated and set an environment variable for them appropriately. I'll then run a series of Docker containers that have access to each of these devices individually so we can see the processes running inside them. The first, let's me see the processes for the full GPU with standard time slicing. And the second, let's me see the processes for the full GPU with MPS sharing enabled. As expected, the one on the top shows four compute processes. That's what the C here stands for. Whereas the bottom shows five processes, one MPS server, and it's four clients denoted with the M plus C seen here. If I ended the same for the two MIG devices, I have similar results. Finally, I can clean up my environment by deleting the job and all of its associated resource claims, which will then trigger the MPS control demons to shut down as well as delete the dynamically created MIG devices on GPU four. For this next demo, I show how to use the selector field in the GPU claim parameters object to direct the allocation of a resource claim to a particular type of GPU. To do this, I have pre-provisioned a GKE Alpha cluster with three node pools, one for running the control plane services, one containing T4 GPUs, and one containing V100s. The DRA resource driver for GPUs has already been pre-deployed on this cluster, as well as an extra helper demon required for DRA to work in this environment. Specifically, to install the NVIDIA container toolkit and make sure that support for the container device interface is enabled in container D. So jumping over to the code, we see two windows. The window on the left shows the set of commands I'm gonna walk through to demonstrate this feature, and the window on the right shows where these commands will be run. So let's start off by first listing out all of the nodes in the cluster. As you can see, we have three control plane nodes at the top coming from the default pool and three nodes at the bottom. The first two of which are from pool one and the last one is from pool two. Next, I'll show the list of what are called node allocation state objects associated with our DRA driver for GPUs. There's one of these objects per GPU node, and they hold the state of which GPUs are available and which ones are currently in use on the node. As you can see, we have three of them. One for each of the three nodes from pool one and pool two. Now, dumping their contents, you can see there are two nodes from pool one with T4s on them, and one node from pool two with a V100 on it. Note the amount of memory each GPU has as that will play an important role in how our GPU selectors decide which one to grab later on. Now, jumping over to the specs I've defined to allocate claims and deploy pods in this setup, we see three windows. The first contains two sets of GPU claim parameter objects. One for requesting access to what I've called an inference GPU, and one for requesting access to what I've called a training GPU, where the inference GPU must contain less than 16 gigabytes of memory and have a CUDA compute capability greater than or equal to 7.5. And the training GPU must have more than 16 gigabytes of memory. As you can imagine, on the current cluster, this basically translates into a T4 for the inference GPU and a V100 for the training GPU. Now, the second window just defines the resource claim templates that refer to these GPU claim parameters objects. And the third window defines the pod specs which reference these claims. One called inference pod and one called training pod. For the demo, all I'm doing is running NVIDIA SMI to verify which GPU I have been granted, and then sitting in a sleep loop so that I can pull this info from the logs later on. So jumping back to the script, I first create a namespace called kubekan demo and then create all of the objects referenced in my specs inside this namespace. Once that's done, I run kubekontrol get pod to show that my pods have started running, followed by another call to print the set of GPUs that have been allocated in each node allocation state object. As we can see, one GPU has been allocated to the inference pod from pool one and one GPU has been allocated to the training job from pool two, which is verified by printing the logs of each pod as well. For the final demo, I will be showing how we have built a POC of integrating DRE support into one of NVIDIA's flagship AI products, the Triton Management Service, or TMS for short. For those of you not familiar with TMS, it provides an automated way of deploying multiple Triton inference servers onto a Kubernetes cluster, each of which may serve models with varying GPU requirements. At present, there is no good way for TMS to pick and choose which GPU a given server will be given access to when running in a mixed GPU environment. By integrating with our DRA resource driver for GPUs, TMS is now able to right size the GPU given to a particular inference server. It does this by translating a model's GPU requirements into a set of selectors, building a GPU claim parameters object from it, and then referencing that in a resource claim. The same GKE cluster used in the last demo is also being used here. So just like before, let's start off by showing the set of nodes in the cluster as well as the node allocation state objects listing which GPUs are available on which nodes. Next, I'll show the TMS server running in the KubeCon namespace on our cluster. And reference a command I've already run in the background to port forward access to the TMS server onto my local host. Next, I'll use a command called TMS-CTL to launch two different Triton inference servers. The first specifies that it wants a Turing GPU with less than 16 gigabytes of memory. And the second specifies that it wants a voltage GPU with more than 16 gigabytes of memory. Once these are deployed, I'll run kube control get pod in the KubeCon namespace to verify that they're up and running. Once that's done, I'll dump the node allocation state object to show which GPUs have been allocated on which nodes. As expected, we see one T4 GPU allocated from a node in pool one. And one voltage GPU allocated from a node in pool two. Executing into each server and running NVIDIA SMI then verifies which GPU was granted to each server. And that's it. Thanks for listening. If you have any questions, feel free to send me an email or find me on the Kubernetes Slack.


Next question is from CarlosValazquez.us. When you were a kid, what did you want to be when you grew up? A podcaster? Yeah, I knew I wanted to be on any of the podcasters. Nailed it. Yeah. Yeah, you know what? Living the dream. When I was really young... Who's the way, before we answer, because I don't know your answers, who do you think is going to be the most different from what we ended up doing? Oh. The most different? The most different? I think you... Probably you. Really? Yeah. Oh, I would think Justin would be like that. You think me? Yeah. I would guess... Justin thought he was going to be a rock star for sure. That was later on, dude. Yeah. I was a little kid. I definitely admit that. I would bet that Justin wanted to be an athlete of some sort, a football player or something like that. Yeah, somewhat. But honestly, I was more driven to be a veterinarian, which was... Oh, really? Yeah. Nobody would ever guess that. And I was actually really interested in it to the point where my parents introduced me to this veterinarian friend of theirs. And I did a little bit of shadowing and watched the day-to-day stuff, and then was immediately like, okay, this isn't for me.  Just like... When that big white plastic glove came out, you just had to know. I'm like, I'm out. Yeah, dude. When I got to stick my whole arm in that, that doesn't sound like a good idea. There was this turtle with this huge boil on its face, it was like... It was just like, oh, this is horrible.  Exactly. Yeah, it's not the glorified... But again, we need them, and I think it's a great profession, but I definitely moved on from that. That's so good by your parents to have you actually go and follow a veterinarian because that could have either... That could have also worked in the opposite where you were like, yes, this is definitely... Oh, yeah. If I was into it, I would have solidified it. They really did that for that reason? You were interested in it? And they said, hey, let's go look at it. That's really cool. Yeah, yeah. That's good parenting there. Now, here's the thing. So for me, I'm thinking about before I was probably 13, 14, because by the time I was 14, 15, I knew I wanted to work in fitness or with exercise somehow. I thought maybe physical therapist owning a gym or whatever. So I knew that at that age, like 100%. But before that, at one point, I said scientists because I love reading so much like science, another point at another time, I said salesman didn't know what I was selling, but I knew that I like to talk. And that was pretty accurate, I think. Accurate prediction. Nothing too crazy. I remember my brother was little. We asked him what he wanted to be. And he said a firetruck.  So from like eight to eight years old, I can think of that far back of thinking about this. Before that, I can't tell you. So I don't know what like two little childhood dreams. But eight's pretty young, right? That's really young. I wanted things like I wanted to be a lawyer. I wanted to be an architect. I wanted any job that made a lot of money. That was like, yeah, that was definitely like with the main driver.  Adam, you're like, well, what makes a lot of money? What's the most money? 100% that's how it went down. 100% it went down like that. There's a video that actually it's a fun. I haven't thought about this memory in a long time.   And I'm just like standing the cameraman comes running over there and they're like, what are you doing, Adam? And I'm just like in awe of the money tree. I swear to God. So at a very young age, I think you just, I put it together as a young kid that we didn't have a lot of stuff. And so I wanted things, you know, and knew that I would have, I would have to work. I wasn't going to inherit anything. So, didn't you say at one point that when you wanted to be a lawyer and then you realized what I took? Yeah. So, so I wanted to be a lawyer all the way until my senior year and junior or senior year in high school. And what is the girl I dated my junior, senior year. I came to her father's law office.  No, I don't. So I wanted to be a lawyer up until that point. And I went to her dad's office one day and we walk in and I didn't, it didn't help either that I probably didn't like, he didn't like me very much, which obviously made me not like a big fan of him as it is. And then I go look at his office and then this happens. Right. So we walk in this office and it was probably almost the size of our studio in here. And it all the way around were books. It was a bookshelf. It's like crazy. And I remember, and I remember grabbing some out and looking at the names and they were just not a single one looked appealing to me like to read. And I remember asking him like, did you read all these books? And he was like, you know, absolutely. And I was like, every word.  None of them looked interesting to me. I'm like, oh my God, the amount of law that they have to read. And as a kid, I mean, I mean, as, even as a young high school kid, I knew it would have to read. I knew I'd have to probably read a lot of law books, but not to that level and to realize how well I would have to know law and how much of that I would have to read. I remember thinking to myself, oh my God, like, no, I don't want that anymore. I mean, even when I first became a trainer, I knew I wanted to work with exercise. But what I initially thought I was going to do was be a physical therapist because that was really the only profession like professional profession that I knew that utilized exercise. Like, I didn't realize you could really be a trainer or a gym manager. And just for whatever reason, did pop into my head is that being like a career. So I became a trainer in order to go to school at the same time. And I remember having this conversation with my manager at the time. This, when I, you know, I done real well, I became a fitness manager. And at that point, school was starting up. And I said, you know, I got to, I got to go back down to be a trainer because I need to start going to school.  I said physical therapy. And they said, can you bring out your paycheck?  And I said, huh, I had no idea. And they said, do you like doing this? Do you think you would like working in a clinical setting more than working in a gym and, you know, making less money? And I remember thinking, no, I love the gym. I would hate working in a hospital or clinical setting. And that was it. That was it.  And we were both going to junior college. We both were going towards kinesiology. I too was thinking physical therapy. But my reason behind physical therapy was the money. And once I got into personal training and I did well and very similar situation. At that time, I was telling them like, oh, I got to go part-time. I got to finish my degree. And like each paycheck was getting bigger and bigger and bigger. And then it finally got to a point where I was making six figures as a personal trainer in my early 20s as a kid. And at the time, was a physical therapist's average pay was less than that? Yeah, it was right there, you know, 80 to 120. So I was already in that, I was already in that range.  Imagine if we all were physical therapists instead for how much boring this podcast would be. Bored out of our minds. You know, I didn't, and here's the thing. 50 more reps. You know, we just be talking about a million reps of like doing things really slow. Well, you know, here's the thing too. I don't mind working with old people rehab. I love that stuff. But here's the big difference. When you work in a gym, they're typically not sent to you by the doctor or insurance. Well, not only that. They want to be there. A lot of times when you work, because I've helped physical therapists, a lot of times the patients come in and say, okay, I don't really want to do this. People hire you out of their own pocket. Oftentimes they want to be there. Well, not only that, but you also get to change that. I talk about not liking advanced age as much as you do or not liking kids. And I like, I had a wheelhouse. Sounds like such a great guy, you know. You're right. Well, I mean, it's me just being honest about how I felt. But the truth is I took all of them, right? I trained lots of clients in advanced age. I trained lots of kids too. As I got, you know, longer to my career, I tried to hone in on mostly what I liked. But that, what I did also like about being a trainer was that I got to do all of that. And like, if you're in physical therapy, you're basically speaking to a type of person. Rehabbing, rehab, it's all rehab. I like to rehab work. I like teaching clients that. I mean, a big part of our job is that most physical therapists, once they get down with rehab, tell you to go see a personal trainer at a gym. So we just continued it on. And it wasn't long after me getting enough of those clients that I do and like, okay, well, what did you do with your physical therapist to get here? And then I started to learn what they did to get them to the point where I would take them from there, which I mean, that's what led me to rehab my knee surgery was I remember going to my physical therapist and I was unimpressed with what they were doing and thought, I could do this. So I enjoyed that.  I got athletes. I got obese people. Oh, so much more variety. Yeah, hard gainers. I mean, you get everything. Yeah. I had, when I had my studio for the last, you know, 12 years of my career, I had physical therapist in my studio because I saw their value was tremendous. I mean, physical therapists in terms of diagnosing, movement issues and pain issues are some of the best that you'll see anywhere. Good ones, right? Of course it's always good and bad ones, but the good ones are just the, and I had an exceptional one that, you know, worked in my facility. She rented space for me and she was so good. I used to love working with her because I'd watch her and I'd learn from what she was doing. I'd hear what she'd say. I'd watch her diagnose and I learned a tremendous amount. And I, even before that, I always worked with physical therapists, but I love the gym. I love the gym environment and it was, I made the right decision, obviously, because I don't think I would have enjoyed a clinical setting as much. You know, it's funny back when, when I said I wanted to do sales when I was younger, you know, as I worked through the fitness space, I became good at training, but also very good at sales and sales training. I did a lot of this for 24-hour fitness and I did a lot of training later on and there was a short period where I thought, well, you know, this is a skill. I can apply it in other places. And I went and worked in the banking industry and that was a great learning lesson for me because as much as you can sell in another place, for me, it's got to be something I have a passion for because I hate it otherwise. And I did, I went to the banking industry and I did investments and, you know, for me, I like investments, but it's not. I don't have a passion for it. I don't want to go out and help people, you know, with investments. And it was so boring. It was the first time in my life I looked at the clock. I never forget I was looking at the clock waiting for it to become noon so I could go take my lunch. I remember thinking, I'm not going to live like this. This sucks because when I worked in the gym, I never looked at the clock.  I should probably go home. Never, and I did that in the bank and I was like, yeah, I belong in fitness. Well, I remember taking one of those, you know, I don't know what you call them, like a personality type test in, I think seventh grade was when the first time that I realized that maybe sales was where I was supposed to be too because everything pointed in that direction. So I took one of those tests and it's like one of the hundred questions and they survey you and you answer and then it said like number one was like sales for me. And then I have family, right? So a lot of my family, that's what they did was sales. So I figured, okay. And then when I fell into training, see, I fell into training not realizing until I was actually training clients how much of it was sales. And that to me was the like, okay, this is it. This is what I'm supposed to do because I love the fitness aspect. I love working out. I love that. I love kinesiology. I was already heading that direction anyway. So that fascinated me. Then I found out you can make a little bit of money in it and then I found out a good portion of it was actually sales.  It's mostly sale. You have to sell someone every single day on why they gotta eat right. You gotta sell them almost every day on why they need to exercise and move right.  And so sales... I'm not just talking about selling training. That's obvious. I'm talking about selling ideas. That's a lot of what you do when you're a personal trainer. So it's a beautiful, beautiful marriage.


Hello everyone, this is Amit Dan and on this channel you'll find financial travel and more videos. If you like what you see, please do the thumbs up and consider subscribing. Thank you. Hello everyone, this is financial author Amit Dan of amitdan.com. Today I'll talk about a prepaid mastercard that does not charge any foreign transaction fee or foreign ATM fee. And this is not a paid or affiliated review. All my reviews are non-affiliated and they're not paid for by any credit card companies or any financial institutions. So the opinions and reviews you're getting are totally unbiased and honest. So today I'll talk about a prepaid mastercard that does not charge you when you redeem money or withdraw money at foreign ATM machines outside Canada. And also it does not charge you any foreign transaction fees or foreign currency fees if you purchase anything either outside Canada or in Canada in US dollars. Now in the past I talked about the mogu prepaid visa card which is also a debit card and that card actually does not have any foreign transaction fee. But it still charges a $3 foreign ATM withdrawal fees. But the new card I'm talking about today is called stack and this card does not have any kind of foreign ATM or foreign transaction charges. So for the rest of the video I'll take you to my laptop screen and then from there I'll show you some information about this card and the company. And also I asked them a few questions which I didn't know and I'll go through those with you. And because you'll get a lot of information from the questions I asked them and which they answered right away. So let's go to my laptop screen. Thank you. This is the stack website's main page so the URL is www.getstack.ca which is G-E-T-S-T-S-C-K.ca And when you go to the main page then you're going to see this stack prepaid master card. So they haven't still launched anything yet but there's a waiting list so if you enter your name and then you have a chance to win $5,000 and you can join the waiting list just by clicking here. And then I don't see any other information on here so let's go to the about page. And on this page you'll see some information about the stack prepaid master card. So it tells you that it replaces your wallet with real-time notifications, effortless savings, tap to pay functionality and relevant rewards. Now if you look at the fee structure, new or replacement card which is free, account activation free, monthly account fee free, contact list payment purchase free, stack to stack transfer free, payroll deposit free, chat based customer service free, ATM withdrawal free, account cancellation free. So it looks like everything is free, there's no cost to it so you have to just enter, put in money into your account and then you'll be able to use the stack prepaid master card for the amount you're putting in. So it's just like having your own bank account and you're using your bank card so the difference is this is a prepaid master card and you can use it anywhere, master card is accepted so even in foreign countries or foreign locations. Now I'm going to take you to the page where I had a few questions about these fees and I asked a stack and they replied me back and they actually did a good job reply me back because when I called them they replied me back right away. So that's what I'm going to show you on my next page. So when I was browsing on their on a stack website I couldn't get answered for lots of things and that's why I send them an email and they replied me back within I would say four or five hours which is very impressive. So let's go through those questions I asked them. So the first question I asked them is does it charge a foreign transaction fee if I use this card outside Canada or in other country? And here's the answer. I'm pleased to say that stack will not be charging a foreign transaction fee. The card holder will only be subjected to the foreign exchange rate at the time of the purchase. So which is a very good thing. Most Canadian banks do not offer a zero foreign currency transaction fee except Scotia Bank which is the Scotia passport visa infinite and I have a review on that too which you can check by going to my channel or I'll provide a link in the description box below and the other prepaid card which is mogul visa prepaid card does not have any foreign transaction fee. Then we have the new stack prepaid master card which is offering zero foreign transaction fee. So which is a very good thing. Now let's go to the second question I asked them is there a foreign ATM withdrawal fee? Is there any limit on how many foreign withdrawals can be made daily or monthly? So what it means that I asked them if I use this card in a foreign country to take out money from an ATM machine is there's going to be an ATM charges because if you do the same thing using your bank card or credit card there's an ATM withdrawal fee because you're taking out money in a foreign country and even it could be within Canada they're going to charge you ATM withdrawal fee if it's not your own bank. So here look at the answer. Stack will not be charging any ATM fees. However card holders are subjected to the fees levied by the ATM company they use. There is a daily maximum of 1000 Canadian for ATM withdrawals and a monthly ATM withdrawal amount of 2000 dollars Canadian. So what they're saying that stack itself will not charge you any ATM fees but there might be charges imposed by the ATM you're using at that moment. Which is understandable. Let's say if you're taking a different bank card then what happens here that your bank is charging you an ATM fee and the ATM machine might charge you another ATM fee. So here your own card is not charging you any ATM fee. Now the other card or the ATM is not going to charge you or may charge you an ATM fee which you do not know. But this way at least you know that you're not paying on any ATM fee by your own charge, your own card which is the stack prepaid master card. So that's a very good news for travelers or who use this card to make foreign transactions or foreign ATM withdrawals. And the amount they're giving you to draw is actually very good amount. So it's 1000 daily or 2000 monthly and usually most of the travelers will be okay with this limit because you know it's very unlikely that you're going to need to cash withdraw higher than 2000 per month. Because whenever I go to travel and whenever I'm in a different country I usually do not use my ATM cards. All my expenses are done either via my credit cards or I take a currency in that country's local currency. So this is a very good amount. So let's look at the third question. Is there a limit on how much I can load or withdraw in Canada daily or monthly? And the answer is there's a daily maximum of 1000 Canadian for ATM withdrawals and a monthly ATM withdrawal amount is 2000 Canadian. So by reading this question number three, it looks like to me that this is actually the same for foreign country in Canada. So your limit to ATM withdrawal whether you're in Canada or you're in a foreign country is 1000 per day and 2000 per month. So which is fine. And let's go to the last question. What options do I have to load this card? For example, interact transfer, e-transfer from another credit card and what other options? And their answer is stack accounts can be loaded via Visa David card, interact transaction and direct deposit. So a stack wants you to use this as a bank account because they're giving you that option to do a payroll deposit directly into the stack prepaid master card. And then the other options you have is you can use your Visa David card or you can do interact e-transfer. But you're not going to be able to do transfer from other credit cards, which is understandable. So these are the options and everything I'm looking looks very good so far. And also actually this card has reward system. You will be rewarded to use your card, which usually is not provided by prepaid rate cards or David cards. So that's another pass point. And we're going to find out more about the rewards, how they work and what is the rate of the rewards. But by looking at everything so far, it looks very good. The most attractive features are zero foreign currency transaction fee and zero foreign ATM withdrawal fees. So if I have more updates on this, I'll let you know. Thank you for watching. If you like what you see, please give it a thumbs up and consider subscribing and there will be more videos coming up. And keep in mind that this is the only channel or my website is the only website where I do not work for any credit card companies or any financial institutions. You'll not find any affiliated links and I'll not give you any affiliated reviews where I'm going to be putting a link to click. And you can apply for a credit card because, you know, most other sites do that. But on my site, you're not going to find those links or anything. All opinions are unbiased and honest. And that's what you get here. So please subscribe and like and I'll see you shortly. Thank you.


Watch, therefore, for you do not know when the master of the house is coming. He can come in the evening, he can come at midnight, he can come the crowing of the rooster or in the morning. There are four watches of the night and he can put in his appearance at any one of those. So here's where you're going to talk back to me. Of those four watches in the night, evening, midnight, the crowing of the rooster or the morning. If somebody is likely to sleep, which of those times do you think they are more likely to sleep? Come on, talk to me, talk to me, talk to me. Let's, hey, hey, hey, hey, let's do it. By the way, I've not heard a rooster since that. You guys have roosters here? Yes? Okay. We have, we have hundreds of roosters. I mean literally, hundreds of roosters. So they wake us up in the morning. Let me ask you a question. Look at the text. There are four watches in the night, evening, midnight, crowing of the roosters that's like about, I don't know, three, two, three o'clock in the morning and then in the morning. If a watcher is about to sleep, is likely to sleep, which of those times is he most likely to fall asleep? Somebody says midnight. Anybody else? Crowing of the rooster, crowing of the rooster. Well, well, here's the text, here's the text. The text says, if that, if we are likely to sleep at midnight, then what Jesus is trying to tell you, it is that that time, it is that that exact time when we are most likely to sleep, that when the sky will split open and the Son of God put in his appearance. Does that make sense to you? Yes, yes, yes. Hang on, people. Here's the message. I don't miss the message. God will not come at the time when we are expecting him to come. Is that, is that clear? Let me say that over here. God will not come at the time when we expect him to come over and over and over and over. It is repeated. He will come at the time when we least expecting. Put it in context for you. Let me put it in context for you. If all hell is breaking loose in Nairobi, if we have problems here and problems here and all kind of crime and violence and starvation and disease and all the other stuff and going on in top and people say, oh, well, this is the time that God is not coming during that time. Does that make sense to you? Let me put it again. He is coming at a time when the people in Nairobi is quite comfortable, well fed, have good jobs, low taxes, amen, is coming at a time when there is no crime and no violence. In other words, peace and safety. If you think the preacher is joking, I can give you evidence for it. I can give you evidence for it. What did Jesus say in the days of Sodom? As it was in the days of Sodom, they were eating and drinking and look at the text. They were eating. They were drinking. They were planting. They were doing all kind of stuff. The economy was good. Life was prosperous. Nobody wanted God to come right now and nobody expected God to come right now. Why? Because when life is sweet, nobody prays. When life is happy, nobody comes to church. Nobody, nobody think about God. He is coming at a time when the society is prosperous. You get it?


Welcome back to the breakfast here on PLOS TV Africa. Today in history, I'm going back to the year 2013 and it was in, you know, the build-up to the elections that eventually brought in President Mohamed Abwari. Good luck. Jonathan was still in power then and there was loads of statements and reactions to, you know, the elections and the possibilities of him getting re-elected or losing the election. It was on this day that Asari Dokubo and the Arewa Youth Forum had a little back and forth with regards to Asari Dokubo's statements. Dokubo, of course, came on criticism after declaring that the Niger Delta region cannot guarantee the country's peace if President Good luck, Jonathan, is prevented from running for a second term in 2015. He, of course, said controversy when he said the Niger Delta region would react if he wasn't given that opportunity. There was, of course, all of this, you know, of course, was in the build-up to the elections. He eventually did run and lost. He came after a recent news conference in Abuja at that time where he questioned reports that some elders from the North are opposed to Jonathan's second term bid. He said that there have been more presidents from the North and the country's South since Nigeria gained independence from Britain in 1960. He also said it was time for people from the South to lead the country. Some Nigerians condemn this remark saying that there's a recipe for disunity and could plunge the country into chaos and insecurity. There was also those conspiracy theorists who had said that, oh, you know, Jonathan, you know, had promised that he wasn't going to run. He was only just going to finish up his tenure after Omar Musa Yaradwa. And right after that, you know, he was only going to do one term and all of that. But there were all just statements here and there. But, you know, the historical moment in this is the threat by Saru Jakobo that the Niger Delta region might go back into creating chaos if, good luck, Jonathan was not given a chance to run for election. And, of course, we all know how that played out. He did run and lost. Yes, that's it. Today in history May the 11th. Moving away from Nigeria now to India on this day in history, in the year 2000, India's population became one billion. And that's because a girl by the name Asta Arora became India's billionth baby.  And that, you know, she went to the hospital that day. She just had her child. And she saw about 200 journalists in her face, cameras flashing all over. And because, you know, India was trying to push a campaign for family planning, because the population of the country was basically exploding. So they said they were going to mat this milestone by celebrating the millionth baby in India. And, you know, to preach the families to begin to have, you know, smaller, smaller families and fewer children. So her name is Asta Arora. And she was born in Delhi, India.  It was on all the major news channels, interviews with the mom, the family, you know, that's basically what happened this day in history. Asta Arora was born in India, making, you know, India the country after China to be in the billionth when it comes to population in the country. That's phenomenal. One billion people. One billion.    But, you know, since, well, it was 2006 or so, we've not had a proper census in Nigeria.  Do we know who our 200 millionth Nigerian is? Do we know who our 250 millionth Nigerian is? But we'll ask this case, of course, there were lots of babies born in that very hospital. But, you know, they decided that she was going to be the one she was born around 5 a.m., you know, judged based on, you know, the time of birth and, you know, she was a judge to the one millionth baby. So, happy birthday to her. So, today should be 21. Is that right? I'm not, I'm not, I'm not fantastic in math. Well, that's it. So, happy birthday to Asa Arora, wherever you are in any part of the world. So, that's it for today in history. We'll take a break here and to return and join a conflict reporter and a researcher to discuss something we, you know, had in our conversation. I think that was yesterday about terrorists, possibly ISWAP fighters, possibly Boko Haram fighters, we'll be getting clarity on that, disbursing food items and showing money to kids in maybe the northern part of Nigeria. Do stay with us.


Now, it's my privilege to introduce our very special guest tonight. Darren Walker is the president of the Ford Foundation, an international social justice philanthropy with a $13 billion endowment and $6 million in annual grant making. He chaired the philanthropy committee that brought a resolution to the city of Detroit's historic bankruptcy and is the co-founder and chair of the U.S. Impact Investing Alliance. Before joining Ford, Darren was the vice president of the Rockefeller Foundation overseeing global and domestic programs, including the rebuild New Orleans initiative after the devastating hurricane Katrina hit the city. Darren has deep roots in the state of Texas and on this campus. He grew up in Baytown near Houston and I know President Johnson would swell with pride in knowing that Darren was in the first class of Head Start in 1965 and would go on in 1982 to graduate from the University of Texas and in 1986 from UT Law School. In 2009, UT recognized Darren with its highest honor, the Distinguished Alumni Award. So in many ways, Darren is coming home tonight. Moderating tonight's conversation will be my friend Dr. Victoria Soto, who was recently named the assistant dean for civic engagement at the LBJ School of Public Affairs. If you watch cable news, you can't miss Vicki, who's a contributor to MSNBC and has, as you can imagine, had a pretty busy time lately. Please welcome to the stage Dr. Victoria Soto and Mr. Darren Walker. Welcome home, Darren. I've heard that you have very deep connections to the Johnson family that run very deeply, very personal. And I wanted to start, I promise we will dig into the book and to your work, but I wanted to start with the connection to the Johnson family and part of the reason that you are here tonight with us. Well, thank you. And thank you for coming. I'm so enormously grateful that you would take time out of your busy schedules to come here. And I'm always happy to come home. Good. And I'm always happy to be in Austin because Austin for me has always been this magical place. And every time I come, I'm reminded of the magic and I'm reminded because more and more New Yorkers seem to be moving here. More and more people I see from New York. The Brooklyn Hipster vibe, I can assure you of that. It's very present. So I really do have a connection and it is manifested many ways. And of course, it really began in 1965 because until I was about nine, we lived in a little town in East Liberty County and a little town called Ames, Texas, which was population 1,200.  We don't have those in New York, but it was a something FM something. And this woman approached the porch and she said she introduced herself to my mother and she said that she was there to talk about a new program that President Johnson was initiating that summer called Head Start. And would I enroll in Head Start? And of course, my mother didn't really know what Head Start was, but admit that I would actually be out of her hair for a big part of the day. And she promptly enrolled me. And so I have the great honor of being in the first class of Head Start. And when I was here in Austin, Lady Bird was very kind because I was Abbott of the Friar Society and she would have lunches for us. And when I told her that I was in the first class, she started to cry. And she said if my husband was still alive and she started to talk about why Head Start mattered so much to her and her husband and their vision for it and their vision for it was that boys and girls like me would have an opportunity to get on the great mobility escalator in this country, which it indeed provided and continues to provide. It shaped our society. Oh, indeed. Yes. Well, it's so interesting when now for the 50th anniversary, President Obama organized a Rose Garden event. And it was really interesting that the people who were featured, I mean, there was Sylvia Matthews, who was the Secretary of HHS. And I mean, just a number of remarkable people who were all invited. And it was, it didn't happen because there was a crisis at the last moment. And we all had something sidebar because I think something happened in the Middle East or something that got made the program get canceled, unfortunately. And it's just so beautiful. It's the living legacy of President Johnson of what we're surrounded by. We go and we can see the pictures, but this is this is the legacy of President Johnson's presidency. And I would extend out to that the your life's work is a direct legacy of that. And in preparing for this conversation there, and I sat down, I thought philanthropy. Okay, we're gonna talk philanthropy. I'm gonna read the book. What is philanthropy? It's giving, it's charity, usually by wealthy people. But I said, let me go check, let me go read my dictionary, make sure this comports. And it did. But then I start reading your book. And it's a much deeper and a much nuanced understanding of philanthropy. And starting with the Latin and the Greek word, roots. I didn't take Latin or Greek. So I didn't know until I was reading that, you know, the Philo, the love and that and through the love of mankind. And that what you do so beautifully in your book and in your life's work is that you highlight that this love isn't just giving. Giving is very superficial. It may be a first start, but it's actually a much deeper love that is embedded in justice, which you develop throughout the book. And that we will be getting to. But I wanted to start at the beginning, which is understanding the title. So the title is from generosity to justice colon, the gospel of new wealth, a new gospel, a new gospel of wealth. Which was the original one? Help us understand where were the original consumption of philanthropy came from? Well, we've had charity and giving throughout time. But in 1889, Andrew Carnegie wrote a seminal essay called the gospel of wealth. And in the gospel of wealth, he articulated a set of principles that really became foundational for what we think of today as American philanthropy, which is really global philanthropy, because all around the world, they're really copying what we do in this respect. And the idea that Carnegie had was that men like him who had achieved enormous wealth had an obligation to give back, that they had an obligation to be charitable, to be generous, and to think about how they could ameliorate some of the conditions of their fellow men. And Carnegie really, in many ways, provided the foundation that Rockefeller and Ford and so many others use as the basis of their philanthropy. And so that work, which has been just tremendously influential, and that essay has reverberated around the world. I mean, when you're in India with a group of Indian billionaires or a group of Nigerian billionaires, they all know the Carnegie essay. But what Dr. King did in 1968 was to talk about philanthropy in a different way, which has inspired me. And there had been very little scholarship or research on his writings about philanthropy. And so what he said about philanthropy in 1968 was the following. Philanthropy is commendable, but it should not allow the philanthropist to overlook the injustice which makes philanthropy necessary. And so what Dr. King was saying was, actually, there is something fundamentally wrong in a society when there is so much dependence on the alms of a few to help ameliorate the conditions of the masses. And what he was doing was challenging philanthropists. Carnegie didn't challenge, Carnegie actually said we should feel good about ourselves, that there's nothing really wrong with inequality. Carnegie had no problem. His, he said that inequality was simply a function of the superior skills and intellect and intelligence of men like him and Rockefeller, and that it was natural that in American society men like him and Rockefeller would have an inordinate amount of wealth. I mean, this was at a time when he and Rockefeller had literally 2% of the entire GDP of the United States was vested in these two men. And in their view, they saw nothing wrong with that. Dr. King actually saw something fundamentally wrong. And so what he said was to challenge the idea that generosity is enough. And he talked about philanthropy through a lens of justice. And through a lens of justice requires the philanthropist to actually get uncomfortable. And it requires you to not have an analysis when you see something, when you see a homeless person in front of Grand Central Station as I do too often, many. It is not to say, oh, what a shame or oh, what bad luck has been visited upon these men and women. It's to say, what injustice? How unjust it is that we can be here in New York City, one of the wealthiest cities in the world with $150 million apartments. And there are people literally on the streets in the winter above the grates so they can have heating on the street. And that there is something fundamentally unjust in the society when you have that kind of extremity of both privilege and deprivation. So one of your chapters gets at the issue of the fundamental attribution error, which as a political psychologist, that warmed my heart in hearing that. So the fundamental attribution error is basically saying that good things that happen to you is because you're good, you work hard, you're smart, and not because of larger environmental or institutional factors.  So you do a very, very nice job of linking together the fundamental attribution bias, which we're talking about, the barons of yesteryear had, and privilege. And how privilege is a lens that distorts how we see philanthropy. So if you could walk us through understanding privilege and not just racial privilege or gender privilege, but a diversity of privilege. Well, I think the question of how we see ourselves in this country, particularly those of us who are successful. And I think I am, I mean, I think I've been, I am one of those people who do you know, the economists love to study you, you're born in the bottom desile that you are in the top 1%. There's a lot of interest in how that happens in a society and in our society that's happening less. But the point is what we successful people aren't often willing to do is to engage in the ways in which our success was facilitated by institutions, by others. And particularly because we in this country have a narrative that deifies the individual, and that reinforces this notion of individual hard work ethic, pull yourself up by the bootstraps, etc. That narrative is so deeply enmeshed in our collective psyche as a country. And for individuals, and I experienced this a lot because living in a place like New York, you do live among enormously wealthy people. And often when you engage in the question of their success, they are very uncomfortable and unwilling to engage in this conversation of the bias, to engage in the conversation of their own privilege and how certain institutions, whether it's government and often it's government, but those other institutions and just look. And that actually paved the way for their success. And that is, I think, a barrier to having the kind of justice that we need to have in this country. Because until we are able, until we privileged people are able to own our privilege and our advantage, and the challenge for America today is that question of, are we going to be a society that continues to be a society where hope and opportunity are the, sort of, in our DNA. That's been what has sustained me. I always felt that my country was cheering me on. And I worry that little boys and girls who come from places like Ames, Texas, or the South Bronx today don't feel like their country is cheering them on. And I believe that the question of hope is the fundamental question. Because this is a country that rests on that idea of optimism and hopefulness. And so I believe that actually the greatest threat to the American democracy is not a pandemic, it's hopelessness.  And I think we have to really recognize how inequality, the growing inequality that we have in our society, how that really exfixiates hope. Because it makes more remote the idea that one can get on that mobility escalator. I always knew I was going to get on that escalator. Yes, there were times in my life, and there were certainly experiences or contexts that were difficult and challenging. But I knew. But I also knew how privileged I was. Even I knew that when my mother took me and my sister away from that little racist town in Louisiana where I was born, I knew that I would have a better life than my cousins who remained there. Most of whom the boys ended up in the Pinnah Tintry system in Louisiana. So I know how privileged I was because I came to Texas and they didn't. And so I ended up at the University of Texas and they ended up in Angola. And I know that my life was transformed by that experience, but I too could have ended up in Angola had my mother not taken me away from there.  You talk about a very conscious self-reflection of your privilege as being a man.   There we go. I mean let's just be very specific and understanding what real privilege is. I mean I have lived without privilege and I have lived with privilege. And privilege is pretty good. I mean there is there is something really good and you know it when it happens. When I was when I left Austin and went to New York and my first summer at the law firm it was you know and anyone who was a goes to work at a law firm, a big law firm you know you you sort of get turned over your life, gets turned over to the billable hours. But that that summer this the woman who took care of the the new associate said oh take this package and walk over to 55 Wall Street to the what was then First City National Bank. And when you go take this and open your checking account and they'll take care of you and whatever.  And so I go and I'm standing in line it was a hot day and I'm standing in line and this woman is walking through the line as we're all and and I said oh ma'am this is I'm just here to open an account and she looks at it and she says oh sir you're in the wrong line and I said oh okay and she said please you must come with me and so she takes me away from this line and then she takes me up these stairs into this thing and it said private bank and I thought I thought a bank was a bank I didn't know there was a private bank and so and so you know I mean she takes me and I sit down with this lady and she starts to tell me all of the things the benefits of the private bank your checks don't bounce you get to have I mean she just started and all of these things I mean you know growing up the way I did I mean my mother every I mean believe me every week every dollar every penny was to keep a check from bouncing and so the notion they just bid a bank and doesn't they don't bounce because you've got money coming in and off so it was really remarkable and it was it was such an eye-opening experience and it is when you live with privilege the way those of us who do live with privilege we should be asking ourselves what are we doing with this privilege and one of the real challenges for privileged people is that privilege buys us insulation from the experience that most people in this country have right and one of the people one of the reasons parents say to their kid I worked hard so that you wouldn't have to have so you'd have privilege right so I worked hard so that you wouldn't have to experience what I had to experience so you would be insulated so you would not have to worry about these things well that's what privilege buys you but the question that we have in our society today is that those of us who have privilege use too much of that privilege to compound our own privilege and that is why the there are fewer and fewer kids low-income kids getting into elite schools it's one of the reasons I so admire what's happened here on this campus and the effort to ensure that tuition and the basic costs for low-income moderate-income kids who are accepted to not have that be a barrier to come to UT but it's a huge barrier for a lot of deserving young people and it's partly why there is so much anxiety and so much anger among a lot of young people today well currently as we see the political context we can feel that anxiety bubbling up what I want to bring into the conversation selfishly is is the idea of public policy because in in your thinking about philanthropy you take a non-traditional stance on it where there is the charitable giving so you know yes we can feed the the homeless give them jackets they're cold but how do we deal with the root cause not the consequence that they're out there on the cold but how do we deal with the root cause which inevitably brings in policy it's macro institutional structures that we're dealing with which isn't easy but that in your view of going from generosity to justice that this is an institutional question and ultimately a policy one so I I'd love for you to talk to us about how you see these different pieces coming together I think one of the real concerns I have and that I write about in the book is that many philanthropists have propagated this idea that philanthropy can solve social challenges philanthropy can test can model can seed but only through public policy can you scale and one of the great frustrations of mine with many philanthropists is their hostility to government and policy and their belief that their own private ingenuity will solve the problem and there is a I believe a amongst some not all amongst some there is an arrogance that because I've been successful I know how to solve this problem right and the streets of philanthropy is littered with the bodies of men and women who were successful who thought if these school teachers would just listen to what I say we'll fix public schools or if these environmentalists will just do what I say we'll figure out climate change I mean this is not going to happen without a robust and vibrant government that does not mean that I am advocating for an enormous bureaucracy necessarily but I am advocating for the idea that government plays a critical role and I worry I mean I was on I was at Stanford a few months ago on a panel with a well-known billionaire and he and I were being interviewed and it was it was actually a very civil it was a lovely conversation and and it was going along fine and the interviewer said something about about how we would scale this and he said well we government can't do it and like well actually government can do it I mean government is probably the only way it can actually be scaled it's a really great pilot but and he said well but government's incompetent and I said well but government is us you know and he said government isn't me I just like lost it I said what who was your civics teacher what do you mean government no I mean like literally no he literally said government isn't me and and I was I was flummoxed I was I was completely enraged I mean I couldn't believe that that this person who's you know I just couldn't believe it and I had a hard time and we kind of went off the rails the conversation because I just didn't want to let him believe or get off that stage without admitting that all of the infrastructure for his technology company was like based on government all of the early experimentation that made it possible to provide the platforms for his technology were all early investments by the Department of Defense and I mean whatever but the point is none of that seemed to be acknowledged he just sort of turned up one day after Stanford and like it was just made a technology and by himself you know the mental attribution error yeah there you are at its best I mean but the point is I guess I'm saying government has a role in public policy and we know this I mean the very best our country has been in fulfilling its ideals of justice and opportunity were made possible because of public policy every every step this country has made for more inclusion for more social and economic opportunity has been facilitated because of good public policy and we will not make progress if we do not have a public sector that is filled with smart people who go to schools like the lbj school and believe that to work in the public sector is an honorable calling as president johnson did and as john f kennedy did how is it that we have allowed the public to be so degraded and anything that is public a public park a public school public housing I mean public transportation you these are things that can't possibly be good or excellent or serve the people well how is it I mean I don't believe that that's our future until I have I sometimes clash with some people because I I believe that it's not enough for a philanthropist I live just a block away from Central Park it's a wonderful park and it's wonderful that for those of us who live around Central Park and who are willing to pay for the Central Park Conservancy privately to keep Central Park beautiful that is great but if you go to parks in the Bronx and Staten Island there are parks that look like third world countries and so we have got to have a public park system that is robust and that serves those citizens because if it's just those of us who can afford to pay for the park for our kids and ourselves while others who depend on the public system are relegated to developing world conditions we do not have America I mean that is the antithesis of America that's the antithesis of our ideals so going to the polar opposite of this gentleman that you're talking about going to a happier note you write about a millionaire billionaire one of the two in Seattle who sees public policy readily working together with philanthropy to get at the root causes of of justice so if you could talk to us Darren about what happened in Seattle the raising of the minimum wage and how you see this as a model going forward well I highlight my friend Nick and our because he's he's very unusual I mean he's a really interesting guy he was an early investor in Amazon and he is absolutely one of those billionaires who has done very well but Nick fully owns his privilege and he fully owns how lucky he is to have stumbled upon Jeff Bezos you know when he was 26 or whatever and as all these guys do I mean it's I mean you spend time with them and you know when you sort of hear about sort of just how people were just were potluck roommates or they lived down the hall from each other in the dorm or whatever these things that then translate years later into billionaire status you do begin to understand how much luck plays in this but in the case of Nick I think he's really taken on the the issue of of inequality and in Seattle where it's pretty severe and where the business community organized against a living wage campaign that that workers and others were organizing there Nick was very much a financier of the campaign that ultimately was successful but it was really interesting for him to go up against a lot of it some of his friends and some people who thought he was sort of a showboater and you know when in fact he truly he understands that for people like him the the question of giving back is not enough and this is what Carnegie and Rockefeller said was our job is to give back Nick asked the question what are guys like me willing to give up and that's a different that's the difference between Carnegie and King what King was saying is that some of this privilege that we privilege people have in order for America to be America we are going to need to give up and it's very hard it is very hard I try I do all sorts of little things I was you know a couple of summers ago in Southampton out in Long Island I was at a dinner party and everyone there except for me and this happens a lot in New York had gone to you know private schools or Ivy schools because again this is one of the reasons I'm so proud I went to this school and and from this region because in the northeast you know everyone it's so interesting because no no I mean because because it's it's it's um this is this is why um places like Texas are so appealing to many people from places like New York because in a place like New York you can go socially and in certain institutions like mine and others and everyone you meet was educated at private schools it's one of the reasons I have written in to every panel that I'm on when they reprint the little brochures about all the panelists that I am a product of public education only exclusively because everybody else when you're flipping the pages I went to y'all however press I mean you could just name the schools and um I was with a group of these people who are all good progressives I mean they consider themselves good progressives and I we were talking about inequality and I said well to a couple of them well who so this person I was addressing went to Harvard and you know and this is the other thing I mean he was I think fourth or fifth generation but it's not unusual to meet people who are fifth sixth seventh generation um in New York and I said I think if we really want to get at inequality we should end the affirmative action legacy programs legacy program is a the fact that your great-grandfather went to Yale should in no way give you any benefit and literally everyone at the table everyone at the table were like almost violently responding to to that do you know and I thought well but how are we going to and it's really hard and I tried the same thought experiment with the group with the group of African-American friends who and again in a place like New York you've got a group of set of friends who are you know generation ago were like we were all you know poor low income whatever you wanted to categorize who are now you know doing well have big apartments on Central Park West I mean all sorts of right and and they were like against it and now what was interesting was was I I sort of could understand like this one person said to me so let me just understand this we finally get in like we black people right we finally get to be legacies and you want to end the program and and you know I mean it's it's like my mother my mother once said to me when she'd always had this dream of like buying a big ranch house because she used to clean big ranch houses but and so when she you know when I could about her big right and so I said oh but we were looking at houses and I look at this house and she said I like this house and I said oh but it's like not energy efficient this mother this house is not energy efficient you need to find a house that's going to be more energy efficient and she said you know in my something my mother could um you know I just think this is great when it's time for me to buy the house I want I get a lecture on field efficiency and why you know a generation ago white people were buying these houses and nobody lectured them about it nobody told them that they had to worry why did that now when I get a chance to own the house that I want you you know invite me to the party and then close the bar I mean so you know but anyway but that's that's sort of what what this person said I mean they said did not but I said to him this friend of mine you know I'm actually not worried about your kids I mean your kids who isn't going to accept a legacy African-American at chote or groton where the I mean who isn't going to accept I mean you know with good I mean very qualified and doesn't need financial aid really do you really think like let's think about who you used to be who you used to be is who I'm worried about getting into schools now not your kids and and that's the challenge for us so the discomfort well that's the discomfort and that's where for philanthropy when you talk about privilege and how we use that privilege as philanthropists to either compound our privilege to give to the things that matter to us it's one of the good pieces of research on philanthropy of large gifts large gifts primarily go to the things that matter personally to the donors it's why we have literally I think there's something like 70 some number of individual breast cancer foundations many of them funding the exact same thing but and you understand why because it's deeply personal someone lost a wife a daughter and they want to honor them but there's no foundation medical research foundation privately working on sickle cell because there aren't any philanthropists who can establish private charity private foundations to work on one of the biggest killers of African Americans well and and on this topic of racial justice broadly defined you spend quite a bit of time on it especially with the turning point of charlotte's phil and then also turning to i'm going to tie an el paso here because i think it's it's in the same vein is that how do you see american philanthropy intersecting with advancing racial justice are are we going in the right direction or are we still too far behind it in terms of of our privilege and not being able to see past that well i really do believe that we have made i mean what's what's amazing to me is how far we have come in this country and how how much of a commitment this country has made and yet how far we have to go and and so i am deeply grateful to live in this country and be an american and every day i am able to hold both of the narratives of this country the narrative of its nobility and its greatness and the aspiration the ideal to be a country that has never existed before a country that truly provides for a place where it does not matter who you are where there are not barriers to your fulfilling your dreams other than your own ability and determination that's our aspiration but we know that we have a history and that we have designed a country that produces results that are antithetical to those noble aspirations and so we if we are to make progress further progress we have to be willing to engage in deconstructing some of that construction and across all of our society we are a function of systems and structures culture and history and if we look at every facet of our life through a systems analysis which is what we do in philanthropy you understand why we are in the situation we're in whether it's our economic system which is now designed to generate more benefit to people like me right so people like me who have assets have been winners for the last 20 or 30 years we have one at a rate that is much greater and we have accumulated wealth at a much more accelerated pace than we ever did in the past right so it's great but it's actually not great for far too many so that system the system of mass incarceration it surprises people when they delve into the data but it actually shouldn't surprise anyone that we have a system of over incarceration of black and brown men primarily but increasingly women and poor whites and we have that system because that's the system we designed when you design a system with cash bail private prisons I mean when you design a system you are going to generate a systems response that reflects those inputs and so when we look across every facet of our lives in this country those systems are producing the bad outcomes that we get and so in order to actually address the racial challenge we have to look at how the systems and structures have to be deconstructed and in some cases destroyed because they are so harmful and they have to be rebuilt and that's really hard work and it's particularly hard work during a time of inequality because the times in which we have made our greatest progress in this country has been when people have felt as a society as a nation most hopeful or had leadership who provided vision and hope even during difficult times we weren't a rich nation at the height of the depression but our leader provided us with a vision of how we as a country would endure and emerge from that time during the 1960s we were a nation that was economically very secure it made it possible quite frankly for middle class white people to be to be open to talking about sharing it is very hard today because middle class and working class white people are hurting in this country and they are not interested in a conversation about racial justice and equity because for many of them they feel the pressure because they know what many economists have documented quite extensively that for the first time in American history we have a generation of downwardly mobile white people and the implications for that for this nation is profound it makes it really difficult to engage in conversations about fairness and justice and equity I had the experience and I learned this first hand because I was in I was in LA a few years ago and like is sometimes the case if you go to a city and you're going to make five stops and you've got to you'll just have a driver and you'll and that on this occasion I had a driver who was a white man late fifties and I'm the sort of talking to a person who talks to people and so we started talking and and because we were going to be together all day and he said he told me what his life story was which was that he'd had a really good job but that the the company had offshored many of the jobs and he was laid off and he ended up in debt and he was literally driving a carry car to make ends meet but it was really clear that he was in a downward spiral economically and we just talked about what that felt like for him and part of it and we really I think bonded but but I certainly he was comfortable telling me how he felt about all the immigrants in LA County he was comfortable telling me how he how angry he was about what was happening in this country to people like him and it it really hit home for me uh on a at a at a visceral level what is happening to people like him and while I of course have a sensibility about the racial injustice historic injustice in this country things feel pretty unjust to people like him and the sort of empathetic part of my brain understand why he's angry and I actually don't blame him for being angry because he's done what he was supposed to do he is played by the rules and yet this country has let him down so we can't have this country let too many people down have too many of us feel left out and left behind because people will do desperate things yes regrettably we've seen too much of that in terms of the acts of of recent years of recent weeks I would even say you talk about philanthropy being for everyone so as as we come to an end here I I want you to tell us how all of us that who aren't the billionaires and the millionaires but how we can work toward that social justice from the generosity to the social justice well I think that you know one of the things about philanthropy that is very true is that it's not about big wealth I mean I think people think about philanthropy with names you know Rockefeller the law like Rockefeller or moody or whatever it may be in in your place but actually everyone in this room is a philanthropist most giving in this country is not done by institutions like Rockefeller and Ford it's done by everyday Americans who give to their religious organization give to schools give to their local boy scouts or whatever it may be that is philanthropy and even though I just made the case for scale and working to impact the largest numbers of people the most important thing you as an individual philanthropist can do is touch another individual it is not about scale it is about asking what am I doing to help another human being in my community that's philanthropy and one of the reasons I feel lucky every day is when you're in philanthropy you are in the business of hope you are in the business of making things possible for people in the business of helping dreams to be realized and there is something enormously gratifying and satisfying about that and so I would just leave you with this idea that in spite of the challenges that we face I'm reminded of what Dr. King said in 1968 just a few weeks before he was murdered he was in a very bad place because he had been abandoned by many of the establishment he had been because he had come out against the Vietnam War he had the black radicals criticizing him and he was worried about what was happening in the cities that were starting to burn and the seeming disintegration of American society and he said to his friend Harry Belafonte America's house is on fire where are her firemen and I am reminded of that today and when I come to events like this I look out into the room and all the firemen and women are here they're all in the house and this is what in every community there are the people who are the firefighters for justice who believe through their fundamental adherents to their faith to some calling that they can make a difference and the good news is there's good news from that beautiful point I'd like to thank Darren Walker one more time thank you