 So about clusters and our work, let's see. So Seymour, what can you tell me about Triton? Yeah, so like yesterday, Enrico was giving us this explanation of what is a cluster and where can you do computing? So Triton is a high-performance computing cluster. So what it basically means is that it's a bunch of servers that are in a machine room, that are connected into like a fast storage system, and then they are connected to each other using this fast interconnect. So there's lots of computers basically at one place that are connect, like create this cluster. And our cluster is a heterogeneous one. Many of the large-scale clusters like Lumi from CSC, they might be homogeneous. So you have only one kind of a computer and you have a bunch of them. But in our case, we have this kind of a sheep of the easiest mentality where we like constantly update what kind of machines we have. And at some point, we don't anymore have any of the original machines left. So then are we the same cluster? Well, in our mind, we are the same cluster, but basically it's a bunch of computers that are connected to each other via network. And this cluster is then managed, all like stuff in the cluster is managed using a Q system. We'll be talking a lot about the Q system in the coming days because that's how you actually use the cluster. But basically you can think of it as like different kinds of like, different kinds of kitchens. Like there was this metaphor about parallel computing yesterday and we were talking about like Stoves. Like how many burners you have? Yeah, how many burners you have per stove? And you can think of like each compute node. So we're talking about compute nodes. We're talking about the single computer. So you can think of every one of them has different amounts of processors, different amount of memories. Some of them have these GPU cards that are used for computing as well, like accelerated computing and various other beaches. So, but you can think of the cluster as this kind of a family of like a big building full of kitchens with different kind of stoves basically. Like a full restaurant worth. Yeah, let's see what else is here. So building your skills. So I think we've sort of explained pretty well that there's this thing where you're always needing to learn things. We're always learning. And we have different resources here. You can check out, but being in this course is the best way to start. Should we talk about how to get help really quickly? Yeah, so, yeah. So Richard, how would you, like if you have a problem, how would you ask for help with that kind of a problem? Well, so first I would try to search the documentation and just a general web search to see if I see any ideas. Then usually I would come to the garage and ask for help. If I know exactly what the question is, then I would make an issue tracker or make an issue tracker request, which can be found here. It's basically Alto GitLab. So, yeah. We nowadays also have like this kind of a chat service, a Zulit chat where you can join us to have like a bit more like informal kind of a discussion, like if you have questions and stuff like that. But yeah, like we also have this daily garage where you can come and ask us directly, like what's the thing on your mind, what kind of problems do you have? Do note that like your university might have a different kind of like way of dealing with customer issues and like it might have a different portals where you can ask for help. But the main thing you should remember that like help is available all around. So it's not only the official route. There's also like, like of course in the internet, there's a huge amount of resources available and your colleagues are valuable as well. So if you know somebody who's been using similar kinds of things, you can ask them for help. And people are usually very, very good with helping each other. Yeah. So let's see, are there any notes in HackMD about this? No, it's there. So what's next on the schedule?