Hi everybody, Joe for jaspyscasebrakes.com. We are now another step closer to knocking out that 48 box high end mixer on jaspyscasebrakes.com. I think like three more fillers, one spot straight up, or maybe four fillers. I don't know, we'll pivot either way, but we're that close. So check out the details, if you're watching live, check out the details on jaspyscasebrakes.com. Here, we're gonna do that division break. Jaspy's four box quick hit division mixer, number four, featuring a few nice boxes here, four nice boxes here. Big thanks everybody here for getting in. Congrats to the people who won spots in this, and thanks again to the people who bought their spots straight up. There are the divisions there. Let's roll it, randomize it, two and a six, eight times for names and divisions. One, two, three, four, five, six, seven, and eight. And of course we'll use a different dice roll for the giveaway part at the end of this video. Two and a six, eight times for the divisions. One, two, three, four, five, six, seven, and eight in final time. Great, after eight, NFC South versus the NFC North. We're actually gonna see the NFC South tonight. Tampa Bay football is back, boys and girls. I'm excited. All right, Mark with the NFC South. Sean with the NFC East. Brian with the NFC North. Chris with the NFC South. Alan with the NFC East. Robert with the NFC West. Mark with the NFC West. And Mark with the NFC North. Let's order these alphabetically by division. We're gonna pause the video when we come back. We're gonna see if there's any division trades. I'm gonna run and grab the boxes too, and then we'll come back and have the break. Stick around, B-R-B. All right, welcome back folks. No deals were done here in this divisional break. At the end of the break, we'll re-randomize these names. We're gonna see who's gonna win that mixer spot. We are super close to getting that mixer knocked out. All right, so for the break itself, we got 18, 19, 20, and 21. We're just gonna go in chronological order. Let's start with the valiant. Let's start with finding a knife for myself. Post it notes, we'll tag the names of the player if I don't know them right away. Maurice Hurst, I know Mo Hurst. He's a raider. 47 out of 60. Is he still a raider? I know there's been some turnover on the defensive line there. No, he went to the Niners along with one other dude. Anyway, this goes to the AFC West. That'll be for Robert. Didn't really work out at least for the raiders. All right, next is Josh Adams, taking it to the house, 11 out of 15. Josh Adams went to the Eagles. It's 2018 by the way, there's also a graded card here. A redemption is Carolina's DJ Moore. Looks like it only just recently expired. Oh, by the way, NFC East gets the Josh Adams, Sean Maddock, NFC South, Mark with the DJ Moore. I don't know, I'm not sure how Leaf handles this sort of stuff, but so recent that maybe you can get something there. The graded card is Josh Rosen, 2018 Leaf Valiant Purple, graded a nine, five, 10 and 11 out of 15. He's with the Falcons now, but that year he wouldn't to the Cardinals, right? Yeah, Cardinals. That goes to Arizona. It's 11 out of 15, NFC West, Mark Rao. And now let's move into 2019, plate some patches. There is a plate down here, one-of-one plate, out of fives and under, get the train whistle. It's John Riggins. That'll go to the NFC East. That'll be for Sean. Sean, all aboard the Big Head Express. Woo-hoo! Behind Luke Keekley is Josh Allen, Jaguar is Josh Allen, 21 out of 60. That'll be for the AFC South, Chris. Behind Luke Keekley is NFC East, Michael Gallant, 65 out of 75, we'll see him in action shortly. Happy football day, ladies and gentlemen, the NFL is back. NFC East, Sean Maddock. Beyond Luke Keekley is a Dwayne Haskins, three-color patch and autographed two out of 50. Rookie patch auto, NFC East, Sean Maddock. This is one to maybe hold on to, see what happens. Stuck, stick it in a drawer, in a shoe box in the back of the closet for a couple years. See if maybe he merges as a player for the Steelers. Maybe replace his big back. It's kind of what, oh, what James Winston did. All right, there's Luke Keekley right there for the Panthers. All right, now we're in 2020. Now these have the Red Star parallels in there. There's Josh Uchi for the AFC East, Allen. Behind Kittle is Darius Leonard. Behind Darius Leonard is a, ooh, I saw Chargers colors. I thought it was going to be, there's Austin Eckler. That was going to be his quarterback. Behind George Kittle, the Red Stars. Ham Newton, AFC East. Maybe a rookie here, behind George Kittle. Yeah, Darrington Evans, AFC South. That's going to be for Chris. Rated rookie, Red Stars. All right, nothing too crazy out of there. All right, final box, Leaf Flash Football. This thing out here, all right. So five autographs, let's see what we got. Good luck, everybody. And then we'll do that randomizer. We got Matt Bushman, and that'll be for, that's right, he's a raider. And that will be for the AFC West, Robert. How about some Trey Ragus? 31 out of 75, is that another raider? Yeah, he is. Trey Ragus is a raider. I don't know if either of those guys are on the team, though. Although Ragus did look good at moments. Bushman was an undrafted free agent. He might still, not sure what his status is. Oh, practice squad, all right. So there you go. Trey Ragus, I think, not sure where he's at right now. I think he ended up being, he was another undrafted guy that ended up being waved. All right, well, there you go, AFC West. Maybe they'll show up somewhere else, Robert. There's Daz Newsom, 31 out of 35 speckled autograph. Daz Newsom is a bear, NFC North, mark with Chicago. Couple more here, we've got Tutu Atwell, flash of brilliance autograph, three out of 35. I think he is a ram. He is a Los Angeles ram. NFC West, mark. And the final autograph is Rashad Bateman. Rashad Bateman, is he a patriot? No, Raven, we might see him tonight? No, on Monday night, that is, we might see him Monday night? Look into my raiders, there's Rashad Bateman. All right, thank you, everybody, for getting into this quick hit mixer, divisional mixer. Now, here's the moment of truth. This is the big moment we've been waiting for. Oh, Bateman's out with an injury, says Oliver, all right. Here's the big moment, though. A one out of those eight spots are gonna get a $3,000 mixer spot. There's some new dice, there's a new list. That's the biggest hit of this break, is the $3,000 mixer spot, so good luck. Let's roll it and randomize it. Four and a five, nine times, name on top after nine. One, two, three, four, five, six, seven, eight, and ninth and final time. After nine, congrats to Brian Frank. Four and a five, nine times, with a spot that he got straight up, you are in that 48 box high end football mixer. That's a $3,000 spot break. Thanks for getting in. Thanks, everybody, for giving this a shot. I'm Joe, I'll see you next time for the next break. Bye-bye.


Hey everyone. Welcome to KubeCon. My name is Kevin Cluz and this is my colleague Sanjay Chatterjee and today we're going to be talking about accelerating AI workloads with GPUs in Kubernetes. So let's dive right in. We are in the midst of the next industrial revolution from self-driving cars to real-time health monitoring and smart cities. AI is powering it all. And at the heart of this revolution are GPUs and the platform that provides applications access to them. For many, Kubernetes has already become this platform, but we still have a lot of work to do before we can unlock the full potential of GPUs to accelerate AI workloads on Kubernetes. This includes changes to both the low-level mechanisms used to request access to GPUs, as well as the higher-level processes needed to map a set of GPUs to a workload based on its requests, where the biggest change in terms of resource management will be direct support for non-fungible and non-exclusive resources at the node level, and the change at the higher layers will take the form of things like topology-aware placement strategies and advanced multi-dimensional scheduling. So to kick things off, I'm going to start with a brief overview of what it takes to enable GPU support in Kubernetes today. I'll then jump into the details of one very specific use case that could benefit from non-fungible and non-exclusive resources, namely GPU sharing. I'll then introduce a new feature called dynamic resource allocation, or DRA for short, which we see as the enabler for taking GPU support in Kubernetes to the next level. Finally, I'll hand things over to Sanjay, who will walk us through some of the challenges with scaling out GPUs on Kubernetes. So what does it take to actually enable GPU support in Kubernetes today? Well, it takes a mix of host-level components, such as the NVIDIA container toolkit and the underlying NVIDIA GPU driver, as well as a set of Kubernetes-specific components, such as the Cades device plug-in, GPU feature discovery, and the NVIDIA Mac manager. With these in place, one can make requests like the one seen on the right to inject GPU support into their workloads, as well as direct those workloads to a particular type of GPU using a node selector if desired. To ease the deployment of all these components, NVIDIA provides a GPU operator, which I'm not going to go into the details of today, but I encourage you to watch the following talks later this week to learn more. One tomorrow at 3.25 p.m. and one on Friday at 11 a.m. For a history lesson on the evolution of GPU support in Kubernetes, I encourage you to also check out the following talks from various organizations at past KubeCons. Okay, so now that we know how to bring Kubernetes cluster up with GPU support, how do we actually make the most of the GPUs we have available to us? Well, there's five primary techniques that can be used to share GPUs amongst multiple workloads. Time slicing, MPS, MIG, VGPUs, and CUDA streams. Most of these techniques have been available to Kubernetes users in one form or another for quite some time. The one exception being MPS, which we plan to release official support for in the next couple of weeks. So what's the difference between all of these different sharing techniques? Well, as you can imagine, time slicing provides the ability to run several workloads concurrently on the same GPU rather than spreading them across multiple GPUs. Each workload has access to the full capabilities of the GPU, but they alternate in time. MPS, in contrast, provides a method of space partitioning, where instead of alternating workloads on a shared GPU in time, each workload remains resident on the GPU without being swapped off but with only a fraction of its total memory and compute capabilities. MIG is similar to MPS in that the resources of the GPU are space partitions, but they are done so at the hardware level rather than in software, meaning that MIG devices are suitable for multi-tenant environments where MPS is not. Now, VGPUs are interesting in that they can be configured for either time slicing or space partitioning using MIG, with the added property that each VGPU is wrapped on a virtual machine, making them suitable for multi-tenant environments under both configurations. The previous sharing techniques, which provide shared access to a GPU at the system level, the final one, CUDA Streams, is a programming abstraction that allows you to run multiple kernels in parallel from within a single application. And with all of these sharing strategies in place, you can actually layer them on top of one another in order to maximize GPU utilization across all of your workloads. Different setups call for different strategies in terms of how or if GPU sharing should be used at all. And I'm not going to go through this table right now, but I encourage you to read the blog post linked at the bottom of this slide to learn more about the advantages and disadvantages of each strategy in different scenarios. I also recommend checking out these talks to learn more. Okay, so the last thing I'm going to talk about before handing things over to Sanjay is DRA. So DRA is a new way of requesting resources in Kubernetes, available as an alpha feature since 126. It provides an alternative to the count-based API for requesting invidia.com slash GPU2, for example. And what makes it so powerful is that it puts full control of the API to select and configure resources directly in the hands of third-party developers. It also gives one the ability to precisely control how resources are shared between containers and pods, which is one of the main limitations of the existing device plug-in API as it stands today. In the interest of time, I'm not going to dive too deep into the details of DRA right now, but I encourage you to stick around for these two talks later today to learn more. I also encourage you to check out these talks from previous group cuts. In particular, my one from last November, which focuses specifically on DRA with GPUs. And with that, I'll hand things over to Sanjay, who will take it from here. Hello, KubeCon. It is such an honor to be here today as we're living in the most incredible moment of our lives. The world is discovering and falling in love with generative AI. Today, I want to highlight NVIDIA Picasso, a GNI Foundry to build and deploy foundational models for computer vision. I feel so proud to share that Kubernetes is driving Picasso's life cycle from training to inference. And today, I will focus on training and the challenges we have faced when scaling out with GPUs. For the inference part, I hope you got to attend my colleague Jan Chen's talk yesterday on talking about the costs of inference. Now, because this journey on Kubernetes started back in 2020, you can check out our coupon talks from that year for more details. Now, the training workloads are essentially bad jobs that require anywhere from 8 to 512 GPUs. And they all depend on all reduced collective communication between all the GPUs. That's for the synchronous stochastic gradient descent. However, to reliably run multi-node jobs of various scales and priorities from multiple users on a shared GPU cluster, we realize the need to augment Kubernetes with advanced scheduling capabilities. For example, gang scheduling, starvation handling, topology of our placement, fairness algorithms, and much more. Currently, many of these features exist in open-source projects today, but we still need comprehensive solutions in Kubernetes when scaling out with GPUs. Today, I will touch upon the top three challenges, namely topology of our placement, fault tolerance, and multi-dimensional optimization. First, let's look into the challenges with topology of our placement. To satisfy the massive compute demands of generative AI, scale-out clusters need to interconnect thousands of GPUs. Now, inside the DGX node, for example, the DGX A100 node, there are eight GPUs, and they can all directly communicate with each other using NVLink. However, beyond the NVLink domain, multi-level rack and spine switching units with GPU-direct or DMA support can scale out these clusters with hundreds and thousands of DGX nodes. So to schedule multi-node jobs, we have to be aware of two topology-aware constraints. First, an optimal placement that minimizes the hop distance between the nodes, and second, bin packing these multi-node jobs within switching hierarchies to improve cluster occupancy. And within a node, the application launcher also needs to be NUMA-aware so that it can bind the training processes to the appropriate CPU core complex. For example, in a DGX A100 node, there are eight NUMA nodes, but the eight GPUs are connected to only four of them. Hence, topology of our placement of a training application is key, both within and across nodes. Next, let's look at fault tolerance and resiliency. Since GPU clusters constantly operate at peak performance, it is not uncommon that electrical and mechanical components can degrade or fail over time. And these component failures can lead to issues like GPU throttling and even job failures. So we need to detect these signals and isolate the faulty nodes so that we can diagnose and repair these faulty components. However, to operate this at scale, it is imperative that we have to automate this fault-handling lifecycle. The first step is to build observability to the GPU infrastructure with in-band and out-of-band GPU monitoring. NVIDIA's infra monitoring components like DCGM and infinite band diagnostics combined with Kubernetes node problem detector and other Linux utilities can help to surface these system faults to the control plane, typically as node conditions. Now, based on these detected node conditions, a scheduling control flow with fault-handling capability and combined with application-level check-pointing can ensure that the training jobs run to completion. For example, if pods are augmented with an init container that runs pre-flight in host and network-level test, then faulty nodes can be detected even before the application starts running. And if faults are detected after the init phase, then the application may need to be check-pointed and the pods rescheduled to a healthy set of nodes. Hence, automated fault-tolerance scheduling, which is both proactive and reactive, is an essential requirement when scaling out in GPU clusters. And finally, putting it all together, I want to highlight the multi-dimensional optimization problem. Imagine we have a 40-node cluster with two switching units. Now, there are 16 nodes that are currently occupied running a job from user one, and 24 nodes just became available. And there are four multi-node jobs of various sizes and requirements that are waiting to be scheduled, three of them from user one, one from user two. Now, interestingly, depending on the KPI to optimize, the scheduler can end up choosing a different job. To optimize for starvation and topology, it'll choose J1. For occupancy, it'll choose J3. For priority, it'll choose J2. And for fairness, it'll choose J4. So which one should the scheduler choose? For most users, the most important KPI is priority and starvation of their jobs. And for the business objectives, it is occupancy of the cluster. And cluster admins always try to allocate resources fairly amongst users. This is a classic multi-dimensional optimization problem. So we need to think about a configurable, multi-objective optimization framework that will make deterministic decisions by considering all the global constraints in a GPU cluster. And not just when scheduling, but also when finding the optimal victim set for preemption or the optimal node group when doing node reservations. Today, I want to conclude with a call to action. This is a great time to solve challenging problems with JNAI and GPUs in Kubernetes. Nvidia just announced Nvidia Blackwell. Amongst many other features, there's inbuilt hardware support for resiliency. We want Kubernetes to take advantage of that. Kevin has been engaging with the community on the low-level mechanisms to enable GPU resource management. And we will keep engaging to solve the GPU scale challenges as well. For many, this is the Linux moment for Kubernetes. Let's make it happen. Thank you all.


Like it's got great to see you? You too. For the first time this season. Fourteen days, eight hours, around 30 minutes until the window closes. You've been fairly active so far. How close are you potentially to getting a sixth signing in this summer? We're hoping to, for sure. We're hoping to try and do some business before the window shuts release. ond a ni am maen nhw y gallais a wnaeth i chi fydd wedi eu gwahanol o哥wyddiadau am rhan o hanes yr oed, ond yn swyddad, yn ôlu i'r Albanau yn dda i ni gael ei ddweud i'ch cerddiannol a'r smedd gweithio. felly mae'n gael ei..., Ac ydyta ti'n eithaf y holliant yma'n ffordd? Mae ymddian nhw, mae yna'n ffordd yn oed i ni, yn y hangen nhw'n llwyso'n holliant? Rwy'n oed, yn gwybod yma wrth gwaith a wnaeth oedd ymddian nhw ac yn unrhyw o'r rhaglenio. Wel mae'n rhai o'r ffordd, mae wedi amlwg er mwyn nos o'r clwb, oen ti'n radd? I can say as we're hoping that we can try and bring some players in to give us that help with what we need. What's it for you, when the wind has shut? The announcement of the virus has ended in at least two weeks before we have a data programme for the new virus. Wel yw'i amdod i'r tyfnod o'n gweld roddo i gwneud oheruns ofio'r ullteidydd ym mhenddoch, ym mhenddoch, sy'n hollwch chiELLau gwahoddiad yn y gallu gwahodd iawn i'n mediad i'n ffleti'r mhenddoch i'n gweithio'n dryrdd. Rhyg o'n farddau llyfr o'r tyfnod i'r fflet. Yn farddau llyfr o'n meddais, rydych chi'n mynd i'r eitaf i'r profiad Dominic Sellanc. Mae pob yn cael ei ffordd o'r holl ffordd ac yn cyfrifio Rhan Fredricks fydda i ddod o'r ffordd o'r hwnnw i ddim yn eich cyfrifio oherwydd. Ond yn cael ei ffordd oherwydd a'r holl ffordd o'r holl ffordd o'r holl ffordd. Mae'r cyfnod i'r cynnwys eich sarnig, Marko Sinesi, yn gweithio'r cyfrant, ydy'r cyfrant yw'r cyfrant yw'r cyfrant? Mae'r cyfrant yw'r cyfrant yw'r cyfrant yw'r cyfrant, ac yn gwybodol o'r pethau a rwy'n gwybodol yn ysgôl, yw'r cyfrant o'r cyfrant yw'r cyfrant? Erw na, mae'n golygu, mae'n gyd recruit. Mae'r tabletm redddoedd. Roedd angen adnoddiadonol i fus produce, byddai'r bobl hyn. A wedi cael arbrining widerad, oedd yn meddwl i llan� sewnodio ar ôl salute theoretical honAC a, eich cais ei ddafyn YongLeysir cyfly Gmail O algorithm migrants. Roedd yn gwych D norigen i'r tas i ydych chi gafodd, Roedd eiоты i ffordd a llunion gyda un oedd wedi allan y papyearhysud theiaeth i deönio mewn bwrddon sy'n mer � addslenu, ac ellen i bethau yw gweld, Diolch yn gael i'ch gael. Mae'n gweithio'n gweithio, a hynny'n i gael fel'r adeithasol yn y gweithio, nad oedd ddau i'r cyflwyno'r ddechrau a ddefnyddio'r gwaith gan y teimlo i'r gweithio'n gweithio. Rwy'n dweud ar gyfer y hynny'n gweithio, mae'n gweithio'r cyflwyno'r gweithio anhyfnodol a'r projektyd yr edrych i'r ddechrau du yn ymgyrchonol. Rwy'n gweithio'r beth sy'n dweud i'r ddoesio. ystod mor oeddi am gyrdisodol i'r cyffredin cyffredin ymlaenau? Rydych chi'n edrych i gael i amdaint cyffredin gyffredin chi wedi'i gael i gael cyffredin cyffredin cyffredin yr angen siaradau yma i chi eu cyffredin lleiau? Mae'n twf greenlil Aberthaid. It's kind of unfair on Miquel, he's done an incredible job in that sense, a similar team for sure The challenge is there, what Miquel has done in a short space of time I asked on how that improvements happened last year, narrowly missing out on-fawr Come here to our home ground, while you understand the challenges that we're going to face and the problems that they're going to cause really. With your analysis and your research in the way that you've looked at Arsenal and from your comments there, would you suggest that they could be a team that could break Man City in Liverpool, that they could get into the top two, they could challenge for the Premier League? I'm not sure about that. What I do know is if the Premier League seems to be a team that could break Man City in Liverpool, I'm not sure about that. What I do know is that they're heading certainly in the right direction in terms of everything that they're doing on the pitch. They're a team on the upward curve of the pitch in terms of the signings they've made. There's a real progression and a real idea and a philosophy around exactly what they've done. They've done some very good business. They're a good side and they're a good team in terms of they're on the upward curve. I see them improving drastically really. And finally, from me, last week obviously Manchester City and Erling Harland, a lot has been made this week about the fact that Bournemouth only allowed him eight touches. Is that because of your team or was that because he had an off day? I'm not sure. What I do know is that he faced a real stubborn team in the way we set up, made it very, very difficult for him in terms of trying to make it very difficult. No spaces really inside the pitch for certainly where he was playing. He didn't have many touches, but other players in the Man City side, which obviously I referenced after, a top player in Harland as a number nine. But when you play against Man City, the ability that they have is to have another nine, which are also world class players. We went there with a plan. We went there to give the best we can to try and nonify that. It didn't pay off on the day. They were far superior and much better than us. You mentioned the progression that Arsenal have made. It seems remarkable that this time last year they were bottom of the table. There was all sorts of talk about Miquel's future. How difficult is it to change a team, put in your own project, as Miquel has done there? I looked at one of your last games in charge of Fulham was only a year, 15 months ago. There's only going to be about four players that started that day that are likely to start this weekend. What do you mean? How difficult is it to... Well, I suppose what I'm asking is how impressed you are with what he's managed to put in place and how he has transformed it so they are playing the way they're playing now. Million per cent. The one thing what you need is that you need trust, you need time. Miquel will probably be the first to say I don't know, but he definitely had that when the noise was around him. There was big noise for sure. There was big noise. He had trust in the people, what had put him in place and he had the confidence to get given some time to structure things how he wanted to structure them. Over the course of that time and that period where he got that, it's been proven that he's come out the other side and you normally find in football really good people who are good at their job and have clear plans with a bit of time and clear heads really and people what can take some breath and understand where the situation currently is and see why that situation currently is, is you can be progressive really. So while Miquel has done an unbelievable job in that sense, it's probably he'll be the first to say as well that when the noise was there no one pulled the trigger and certainly he probably was able to go and do the job and execute the job how he wanted to do it and make big decisions, big calls and he's been proven that he's done very well for that. I swear in the Premier League we're sort of leaping to conclusions very early on players after only two games so on the either side of it in danger of doing the same, but how... But we will. Yeah, exactly. But rather than pointing the finger at someone not doing well, Gabriel J. Zeus is, I mean that looks like an absolute spy in signing. Brilliant signing, yeah, amazing signing really and probably Miquel had the player when he was at Man City so top forward, an incredible centre forward, he's got probably every facet to his game really as a number nine can drop in, can drop down, link play, there's all sort of threat on your back line as well. Work rate, endless work rate as a modern day number nine in terms of pressing and leading the line from that sense. So then, yeah, he's a real challenge for us at the weekend to try and keep him quiet, a big play for them. And without going into too much depth about everything on the Arsenal side of things, you know, I don't recognise some of football that's played in the Premier League these days, the way Jacker and Zinchenko are switching and all these things. I mean, are you seeing a lot of innovation and I suppose Pep Guardiola type stuff in this Arsenal team? Yeah, I am. I'm also seeing things that obviously a good coach, which Miquel is, is producing at his football club and his team really. So a lot of challenges positionally, tactically in terms of how he's set up the team. And then obviously added to that is the quality of the player that can execute that delivery of message really. So, yeah, they're a good side, a well coach side and a teamful of players that possess good quality in all moments really. And when you say you want to make it as uncomfortable as possible for them, what's the key to that? Is that just not allowing anyone a split second of time? Are there other elements to it? There's loads of elements to that. There's loads of elements put, try and put our stamp on it, try and work out where we can exploit their weaknesses, which they will have. And also home stadium, fans in terms of what we need to bring to the game. There's loads of facets, why we need to, you know, we need to step here and while of course we respect everyone what steps on the field when we play, there needs to be an element of, you know, these are just names and we need to, we need to put our stamp on this game and we need to bring our personality to this game. And that's the most important thing what we need, as well as the tactical element, as well as all facets out of possession in possession. Yeah, we need to bring personality to this game on Saturday. You made it very easy for your crowd to build up an enormous atmosphere in the last home game by scoring after just a few seconds. How much of a part have they got? Massive part, yeah, massive part to play, tight stadium and they've got big parts to play. We need to make this place uncomfortable this year for teams to come to. We need to generate that, stand to us, stand to my players to do that. They need to generate, they need to get the energy and give the energy to the stadium and give the energy to the crowd. How we do that is with the way we play and how forceful we are, how we can dominate in certain moments and be progressive in certain moments, can bring that energy and then we can react from that as well, really. Early goal last time, give everyone a lift, first game Premier League after two years of not being in it was a massive lift and give everyone a big lift in a stadium, really. So, yeah, we need to continue that, really. Good luck, Scott. Thank you. That's the name, Scott. Scott, I'm going to ask you to take a trip down memory lane. 25 years ago, this coming weekend, you made your debut as a 16-year-old at Barry. 25 years ago, you were still great. I'm sure you won't be able to find any pictures on the internet. Probably internet don't exist back then, do you fare? What can you remember about that day first of all? Sean Newton got sent off. Yeah, I remember it well. I remember not being, I didn't think I'd be in the squad. I remember I was a 16-year-old boy, so I didn't think I'd be travelling with a first team. I was travelling, and I expected I was going to be making the tease. To be honest, you were on the coach on the way up, and then obviously he was on the bench. I remember that excitement, real nervous feeling which you have when you're first setting out, really. And then I remember when Alan Kerbyshire gave me a nod to come on, really. Felt very quick. Felt very actual game in the environment while I was in, but big experience for me, really. At the start of that dream, I've wanted to be a player, really, and cracking on from there. You've given a lot of players their debuts since you've been the manager here. Does stepping into the Premier League make it more difficult to give young players debuts without seeing many 16-17-year-olds in the league? No. I think it does, for sure, that the quality of the level of what you're going into every week is much higher. I always say that when you're 16, 18, 19, you give debuts first and foremost on players you feel have the ability and are good enough at that moment to have an impact, really. Harvey Elliott, I remember when I was at Fulham, was an example of that. A young player we give a debut to and kicked on the ability first and foremost and I witnessed that daily. So, yeah, look, I think it's more difficult, for sure, in this division. But, like always, if the talent's there and they can make a step up, then, for me, I'm a real advocate of pushing them in. Just talking to young players, the development squad kicked off their Premier League Cup campaign with a superb 3-0 win against Brighton, one of the top academies in the country last night. Yeah, incredible, Neil, category one academy, unbelievable win, really. You know, I've always said it, an amazing job the guys do in the academy. Coops, Tommy, all them guys in and around it. What are developing the young boys in probably at times difficult circumstances in terms of where we are as a category of club and that. But, for sure, an incredible result did amazing. Just interesting that, obviously, the excitement of being on a bench when you're making a debut in Ferry. What was the emotion when you 3-0 down after half an hour at the Etihad? Hello, Ike. Yeah, hello, it's difficult.  Obviously, we've seen it many times throughout the years of watching Man City and teams go to Man City. You can be on the end of one really, so I was immensely proud of the team and showed big courage, big desire, and they let their head drop in that sense, dug in, stuck with everything. So, of course, that's probably strange to say when you just come off the bat of a 4-0 loss, but that was probably my emotions really during it. Man City, Arsenal, Liverpool, you enjoying it? Yeah, I'm enjoying it, yes. These are the challenges that we look forward to there, the challenges that obviously we worked so hard for, last year and while there's some absolute mammoth ones and ones which are right up there in terms of big, big challenges, none bigger than last week when the heavyweight of Man City, they're ones which we're excited about and looking forward to really. Just finally on the team news front, what's the latest with David Brooks and his involvement in the first team squad moving forward? David's pushing on really, is with the team in a modified, in terms of his training, but he's with us, he's not no longer on his own. So now he's split between the two groups of being on his own and then also being with us in a controlled environment. So I'd like to think that maybe over the next week or 10 days we can start pushing him into full training and then from there trying to get him up to a level and speed of participating at Premier League level really.