What I'm going to talk about today is probably familiar to many of you, if you've seen any of the work I've done, and it's mostly these questions of rhyme and prosody in early prose. Although, of course, all of the information we have from the early period, well, most of it comes from poetry. So we're going to do a bunch of poetry, too. And then how do we scale up? How do we do all of this at essentially as large a scale as possible? So we're going to talk about that. The other thing that I think some people have found interesting in my work anyways, is all the imperfect rhymes, right? So we're not just going to talk about perfect rhyming, but the Ho-yu and the Tong-yu. What are these? And I use Wang Li's definition for these with apologies to Chao Miao-gao, right? But what does it mean to have imperfect rhyming? And what can we learn from our sources when the rhyming is imperfect? So let's go ahead. As some of you may know as well, I've been working also quite a bit in intertextuality and early Chinese philology these days, doing lots of network stuff. This talk has no networks in it. Sorry about that. If I'd planned better, perhaps I could have included some networks. But Chris Foster, if you want to talk about alignments of bibliographies, we're doing that as well. We're doing what's called text reuse across very large corpora, but it works very nicely for bibliographic citations as well. More importantly, what are we going to talk about? Well, we're going to talk about the mean. We're going to talk about the rhyming, right? Because I find it a very illuminative case study for thinking about the finals in poetry. And of course, what were the sounds of these words and how did they change over time? Paloization here is the main question. And then we're a little bit about algorithmic approaches to detecting and especially visualizing these what I call phonorhetorical patterns. We're going to see one text from the early Western Joe, and then we're going to see a text which I date to the Western Han. We could argue about this if you want. I'm not sure. And that's the goal of you. So the real key to the second part is then scale. Can we scale up our essentially elucidation of these patterns to be able to use them for any text of any period? And of course, this scales beyond Chinese. If you can do this for Chinese, that's great. Can we also do it for languages that used phonetic symbols, letters and such in the way that they express sound? And I think we can. So that gets very exciting. And then the last bit, we're going to do a little bit of what's often called text to speech. It's a hot new field in tech. And you'll find that what I present here today is already well out of date, but hopefully we'll give some hope to where we're going with all this. All right, so let's jump in. A lot of what I'm going to talk about comes out of my dictionary that I built some years ago. If you want to go use the digital etymological dictionary about Chinese, you can just go to edoc.uchicago.edu and just click login and it'll let you in. You don't have to register, but I do that. So that people hopefully don't just take the whole thing. Anyway, the other thing I'll say is this talk, I'll go back to the first slide, is here. If you'd like to grab a copy of it, because some of it is very hard to read, especially over Zoom for thousands of miles, you may want to just download the PDF and view from there. All right, so let's go. Mean is one of my favorite words in old and middle Chinese, because what we know about it comes from, of course, the Tia Yun and the Guang Yun, and it's in this fun category, the Zheng Bu. So this category has two different finals in particular, and then also other finals. So it's this kind of, it's not quite a catch-all, but there are various different sounds that are all represented within the Zheng Bu. And that means that we have to really work to figure out potentially what were the sounds, what were the finals of these words. And for Ren Min Min, almost everybody, pretty much everybody, reconstructing this graph back from our rhyme dictionaries has given it a final, either an in or an un final, right? So it's either the schwa n or this i n. Sometimes with a glide, especially in middle Chinese, I think there's a really good set of evidence for there being a glide, mean, something like that, within it. That's what Pully Blank did. Zheng La San Pa and Star Austin were convinced it's mean, which is interesting. And then we get, for the first time in 2011, Baxter Cigart decided that the final consonant in this word was not the n, but it was the un final. And so how did they figure this out, right? How do we know and what's the evidence for this? And I just want to present this as a case study, because what I'm seeing, and I got to look through the other presentations, I think that what you're finding when you do the network graphs of rhymes and words that rhyme together, you're finding a lot of liminal cases as well, you have cases which are fairly solid. And then you have words which kind of fit in between various clusters in the network. And those are most interesting to me anyway, and trying to think about how do we tease out what exactly the sounds of those were that are in those liminal spaces, where it's not clear if this was maybe Yang Buzhe or Gong Buzhe, that can be really exciting. So this is just a case study to look at one example or something like that. The best evidence for mean and the final, I agree with Baxter and Cigar comes from the Shuzin. And it comes from this word, this what we think of as Dean, because in most modern orthography, the right side is Tiki Enzhi, right? But if you actually start looking into it, this is probably an orthographic mistake or variant depending on how you think of it. Donny Tsai noticed this, and he says that in the Shulin, it's always this written with the Dean on the right, and says, Jean is the phonetic, right? But if you go to the Hanstone classics and look at these stalers, they write Dean with a ling on the right. And he says that's the correct original version of the graph. And I think Donny Tsai is correct. And what it leads to is we have various potential sources for Ng, and then it changes in some cases to Ng, some cases to Ng, and sometimes it stays Ng, and this is from Baxter and Cigar. It's newer work. So if you go to the Ma Longui manuscripts, the Laozi, this graph does occur twice, and you can see fairly clearly it's a ling on the right, and this one, and this is actually a ming, so something here on the right. So pretty conclusive evidence that the phonophoric, the shengku, originally was ling and not Tiki Enzhi. Okay, so we can do that. And we have pretty solid evidence now for that graph. What about the other graphs in the sequence? And this again is where the network theory that I think most of the folks here, as you've been involved in this, you're running into cases like this, where you have characters that fall in places where they could be rhymes, and the sound is close, but is it close enough to actually make an educated guess about what the final actually was? And that's the real question here. In my opinion, these are not actually rhymes, the ones in the red boxes here. And that's because these are hokou. It seems that this palatization that we see with ming is mostly a kaiko phenomenon, kaiko as well for routine, but shing and shen, being hokou, don't seem to fall in the same category, and therefore the finals here being in the Baxter-Sigart reconstruction are probably correct. And then we get to the other example. And the other example is this wanliu from the xiao-ya in the shiting.  So the question then becomes if we have so much good evidence for pronouncing this graph as something like jing, what is the rhyme here in this stanza? This is the entire third stanza. And what does it tell us about the word tian? Is it possible that tian had a final oong that this is also one of these cases of palatization? I don't think so. And the reason I don't think so is because when you go to the qiayun in the guangyun, it ends up in the xianbu. And if we look over here, that's the shen, here is also in the xianbu. I think we have pretty good evidence that the final for tian, if we follow the system, is probably in... But zhong has a very similar profile to min. And if zhong here is indeed following the same change over time that we see with min, we can propose that the final here was actually oong. And therefore, this was pronounced something like zing, string. And this then would be the rhyme. And then you have a cross rhyme essentially with tian. Putting tian at the end of your first phrase is always pretty effective. I would think it's a nice word to drop in there. And so the question then becomes, is this ABB, rhyme, AAB? It's still uncertain. We need more evidence. But this is the kind of work, at least down on the ground level, that I think you can do with all of the graphs you find where you're running into this liminal space. You're running into this place where they don't seem to 100% fall into one rhyme group or another. And that gets very exciting. So I expect great discoveries from the network analyses. All right. Let's move on to the second part. And I'm going to run through this pretty quickly. And mostly what I want to do is talk about prose in this section because we take much of our evidence for rhymes from poetry and that's right. But there's an incredible amount of evidence in prose as well, going all the way back to the Western Joe bronze inscriptions. So if you look at the bronze inscriptions, and I've got two here on the page and I'm sorry you'll not be able to read the characters or anything, this is mostly to give kind of a bird's eye view of the text and to try to think of the prosody of the text as a whole. Where are the sections where they're using one device? Where are the sections where they're using a different device? And then can we train a system that will help us figure out what those sections are? How they might have sounded at the time at scale for any text from any time period in Chinese history? And I think we can with some work. So you can see here in the Dalu Ding, which is the text we're going to look at, you have a section of cross rhyming. This is a Huyun according to Wang Li's definition. We have some perfect rhyming, but you have really a lot of essentially Huyun cross rhyming. And that's true here even in the bell inscriptions, which tend to have the most amount of perfect rhyming in the bronzes, there's still a lot of what we consider Huyun cross rhyming. And in this case, that means that the final consonant is identical, but the medial vowel is different for the most part. And we see it as well in works like the Kango. We see it in the Shang Chu.  So if you look at the actual text, and here we are, this is the bronze probably cast in 981 BCE. It's the best guess. And you look at these, what you see, of course, is four, five, and then seven. And then I believe this is also seven and then four. So the metrics don't line up the way that poetry would. Most poetry tends to have a fairly regular metric structure, even into the Fu and the Pianhuang of the Han dynasty, you'll get couplets and the couplets normally have the same metric length in terms of number of graphs in them. But in prose, it varies widely. And we have to be very careful about that because can we adduce rhymes when the metrics are different? And I think we can. I think there's plenty of good evidence now that these are clearly rhyming texts, even though the metrics are not perfect. And you'll also notice the variation here in the medial vowel, as I said, where you have wong and then ling, bang fang and ming, right, ming, ming, read with it, final. So this is what we see coming out of the Western Zhou is wide variation as far as we can tell in the medial vowel within a sequence that seems to be at least loosely rhyming, slant rhyming, cross rhyming, covery work. So we see this right then next two sections that seem to rhyme perfectly. And here this is even four, four tetrasyllabic rhyming, just like in the shiitian. Or the next line where you have five, and then five also seems to be a perfect right. So these couplets show up all over the place in early Chinese. Other sections that rhyme here, again, we have four, four ending in un, and then un, and then the glides that Chris was mentioning, we do see sometimes rhyming with glides in all the way back to the Western Zhou Brown's inscriptions. And then all kinds of cross rhyming where the metrics are all over the place. And then you start to have to wonder, is this really still rhyming? Are they using this for its sound value? And I think the case is probably yes, it's a prosodic construction, even though it's not the type of construction, not the type of formulation you would normally expect in poetry. And then a last section here, including the dedication, which kind of rhymes kind of doesn't, it's a hard call here then to say whether or not this rhymes. The other part that we see in these texts, and I think this is actually really important, we see rhyming with final K quite a bit. So final un and final K are the most common. But again, wide variation in the medial vowel and variation in the metrics. So you have to be ready for this when you're using pros, at least pros like this. And then the last part that I think is really important, especially if you're going to do this at scale, is to look at these and recognize that there are plenty of sections that have no rhyming detectable whatsoever. Or if there is rhyming, it's very, very subtle. Here in the gift list, you could make an argument for the Ock here creating a couplet. But it falls right in the middle of the gift list. Here's another Ock that comes. So is this potentially a rhyme? Sure. And then the finals that run through here, almost everything else ends in Ock. Does the gift list actually rhyme in this case? Maybe the rest of the text, as we can see over here, does have a huge amount of cross rhyming and even perfect rhyming. So maybe even the gift list is rhyming, but it's a very hard call. And what we're going to do when we turn to algorithms is we're going to ask the machine to make these judgments for us, and then we're going to check them. So this is where it all gets actually quite complicated. All right. So that's the Western Joe. If we move to the transmitted texts, we see a slightly different story. And the story then in the Zoujuan and especially the Guoyu is lots more perfect rhyming than we see in the Western Joe bronze inscriptions. There's still some cross rhyming, but it's clearly heading more and more toward use of perfect rhyme. And again, this is in prose, not just in poetry. So the text that we'll rip through real quickly here in the Guoyu is the Yueyu Xia chapter. So the discourses of second part. And what we see is lots of use of the Aung final. And here then potentially a five, four, four, kind of an AXA construction or BXB construction here in the second half. It's hard to tell, right, which is why it's in light blue instead of in in darker colors. But for most of this text, and this is very true of most of the speeches you run into in the Yueyu Xia chapter, you see four for rhyming in extremely metrically regular constructions, mostly tetrasyllabic. And that, of course, harkens right to the poetry of the Shijing. They were, I would say, clearly using this as a rhetorical device since the poetry had such gravitas, they're echoing what they find in the Shijing in their prose as well. At least this is how it reads to me. We have other sections where you have an Aung kind of an XA, XA construction followed by three lines that seem to rhyme in et. And that's the dark green here, perfect rhymes. And then final a would be basically CCXC in this last section. So three very different rhymes, but all perfect. So three different, perhaps sections to this passage, just one way to think of it. And you can split them with rhyme. And that's one of the beautiful things I think you can do with a lot of early prose is split sections of your manuscript or your text by how they rhyme when they do rhyme or cross rhyme. This last section is probably my favorite from this text, because it's basically talking about military history. Ernest, if you haven't seen this, you'd probably like this. They're basically giving a little bit of military instruction in, as far as I can tell, basically perfectly rhyming tetrasyllabic prose right here in the Guoyu. So, you know, you want to build up the left as this Mua, as this male part right. And the female then is the right flank. But then, of course, it goes back into our cosmological didactic instruction obey the ways of heaven and surround and revolve, but don't concentrate, but don't concentrate your forces in this case, right. So relatively perfect rhyming, even in somewhat militaristic context, pretty fun. And then like we see in the bronze descriptions, long sections where there is no discernible rhyme at all. And you just, as I say, you have to be ready for that. You have to expect that, actually, in many cases. So when you scale back, when you look at this from a bird's eye view, you can start to use color coding to look at the prosody of entire texts arrayed against each other. So here we have the Daoyiding, here we have the Liancizhong, and then over here we have sections of the Guoyu. And just by the colors you can tell how different they are. I'm not sure that my color scheme is the best, I'll be honest. So one of the things I was thinking about looking at the networks is whether or not, instead of using these more random colors I chose, could we set up a gradient or a set of gradients around various rhyme groups or groups of rhyme groups, where each cluster then has its own color or color scheme, and then the gradients show where one color bleeds into the other. If you can do that all algorithmically, you could plot all of this in a very nice kind of series of gradient color schemes that would show the prosody, that would show the rhyming and the cross rhyming all mathematically. So something to think about. All right, a few issues that need to be brought up as we do this. So we have a lot of gradients. In this case, I did the work by hand, which means I get to adjudicate what the correct sound would have been. But that's a hard call in OC especially, what was the correct reconstruction, right? And as we saw where it's like mean, if you have competing reconstruction systems, which one do you choose? We think maybe neural networks will help here. That's the hashtag AI for OC. Other more complex renderings of the ways that graphs had multiple pronunciations is probably the best way to go. The other thing is that some lines will naturally fit multiple what I call phonor-rhetorical patterns. These are phonological patterns. And sometimes the patterns are not in rhyme-based. As we saw with the glides in the early part of the Dalu Ding, sometimes you have inner rhyming within a line. And you want to make sure that the system is also picking those up, probably. But it can be too much. If you highlight every graph with a different color, does that really help you understand what the sound system involved in the text was? That's a really hard question. And then the last one, we have evidence, especially in the sounds of repetition used as a rhetorical device, alliteration in some places. How do we also show those types of prosodic devices and constructions? And I do want to give a quick shout out to John Rominger and Nick Kudak, who through a project at Princeton are heading this direction, trying to work toward a large-scale system where we could use essentially natural language processing and algorithmic approaches to understanding the prosody of old Chinese. Along those same lines, for those working on Han dynasty texts, I would just urge you to consider all of the ones here on the screen. So the Guoyu and the Zhang Guoxu, we could argue about when those are actually dating, too. They probably originally were written a little earlier than the Han. But I think the versions we have, probably at least in part, date to the Western Han. We have the Pianon from the Han dynasty. We have the early historiographies, so the Shiji and the Han shu, and then of course the poetry. The Fu are wonderful if you look at their prosodic constructions, and the UF Fu are interesting. And then, as we saw with Chris, a wealth of manuscripts, right? Manuscripts are a little more difficult to work with in some cases, but I think it will pay off. And especially if we can do this algorithmically, scale is not really an issue. So we could do all of the manuscripts found from the Western and Eastern Han, Nanbei Chao, Tang dynasty, whatever you want. All of Dune, right? So that's the real benefit to doing a lot of this competition. All right. And I only have a few more minutes, so we're going to do this kind of quickly with the rise of the Alexa devices and other things like Google Home, text-to-speech has become a thing. And so when you're doing text-to-speech, most of the time, we're doing it in a modern context. But there's no reason we couldn't do text-to-speech if we can produce a reasonable IPA for any language. And here, let's think about Tang dynasty, middle Chinese. If I thought about it better, I could have produced a Han dynasty text in the system. It is algorithmically based, so you can actually use any text for this. But here, what we have is we have Tufu, right? And it's probably illegible. Again, you probably want to download the PDF to see all the different sounds here. But you can have it read in modern Chinese. Well, we can all read it in modern Chinese. That's not a problem. The Macintock system from many years ago allows you to render phonemes in a speech synthesizer. And what that means is you can produce IPA, you can convert it to this Macintock version of the phonetics, and then the machine will read it as phonetics. The main problem here, in my opinion, is that the speech synthesizer is a very generic one. It's based on English and it's already about 10 years old. And it very much sounds like war games if any of you remember that movie. But let's see what we hear from the Victoria voice reading the Middle Chinese phonology for this Tufu poem. Ready? South in Tong, New York, New Sin, Xium. Yay! See what you like to play again? It's by no means perfect. But we're getting better and better at speech synthesis. And I think there's no reason that we couldn't actually build a system for Middle Chinese at this point. I don't know that we could do one for Old Chinese since the actual phonetics are still relatively in doubt. But given the wealth of information we have for Middle Chinese, I do think an algorithmic based speech synthesizer is very much a possibility, and one that doesn't sound like war games. We'll do one last one. This is the long way famous poem here. And let's see if we can have this then read in Middle Chinese by our computer. So, despite the poor quality of the speech synthesizer, hopefully you can hear that it did at least get all of the rhymes relatively perfect. And you can see in the rendering it's basically able to handle a version of phonemes. And therefore, if you do it correctly and you do have the same phonemes, it will hopefully speak them identically. And that's what you want from the machines. So that's really it. My 30 minutes are up. We can go ahead and talk about any of this stuff for adjacent things that we're doing. And thank you once again. But I'll just pick out one thing that you mentioned, which is alliteration. And I don't know, like 15 years ago, very early on in my engagement with Chinese historical phonology, I taught a class where I just wrote several of the surging poems in backstreet cigar system. And I was seeing alliteration as a poetic device. But it's the sort of thing you don't want to tell anyone because you're like, the most secure part of this reconstruction is the initials. So like, I mean, kind of that's the whole question, even though it's not a question, but like, how do you think, yeah, well, try it. How do you think we can make progress either on the study of alliteration as a poetic or rhetorical device? Or will it ever be possible to use the existence of alliteration as a poetic device to actually inform reconstruction? Ooh, will it ever be possible? Yes. Yes, I hope that assuming human history continues. Yes, eventually it will be possible. One of the things we're missing is data, right? So we have rhyming poetry from the OC period, we have, as I showed the bronze inscriptions, which do rhyme, you know, won't go away. It works pretty well. So what exactly can we tell about the initials is your question? And that's such a hard question. Carl Grint spent much of his life actually trying to systematize graphs based on their components. And you could tell he tried to systematize the initials because the finals become relatively clear, right? In general, we kind of know what rhymes and cross rhymes and stuff. That's great. Would I ever stand up in my lifetime in front of people and say, yes, I know what the initials of these words were in old Chinese? Probably not. I think you made the right choice there because there's just too little evidence. We're working backward from mostly the Ché Yun and the Guangming here, right? What evidence do we have for alliteration as a prosodic device in the preaching period? I don't think we have a lot. There were poetic traditions that used alliteration as one of their main devices. I don't think old Chinese is one of them. So no, so I think you hit it right on the head. We don't know. We have conjectures, and I think that the conjectures are fine. More data will help our conjectures get better and better. But when we think about representing uncertainties, that's by far the biggest uncertainty in OC by far. So as a research program, do what we're doing, look at loan words, look at Sino-foreign things and whatnot, and then maybe as the initials become more clear, their use for poetic and rhetorical devices will also become more clear. But probably Chinese is a poetic tradition just never made. It's not like old English. So we'll never be able to say because there's no alliteration here, I must reconstruct tea. Yeah, something like that. I think you were talking on the 20th side. And he was talking about how the character had the phonetic gene, like T-t-n for the gene. But the original one was meaning the link. But the interesting thing about this is gene also had M as an ending, and then a lot of these M endings turned into NG as well. So I mean, because I would have to get all my computer programs and books and look up a bazillion things to actually make a real comment on this, but it seems like there's a relationship going on possibly that even the later graph was still tied in some way to changing sound. Yeah, it seems this way. And one of the real keys, I think, to this is graphs that have multiple pronunciations, or as we see, you know, sometimes they diverge crazily, right? And so it's hard to know how to make sense of a lot of that, but all of the sonorans, M and N, tend to have flexibility across vowel structures, which is put it that way, right? Whether there are glides there, the medial vowel E is probably the easiest one to do, doing it for the schwa is much harder, but probably doable as well. So did these words have slightly variable finals maybe even depending on who was speaking and how they were deciding to pronounce the word? Okay, well, thank you so much for getting up very early, actually, to watch some presentations and to join us today and for your talk. Yeah, it was really, it was really fun. And I can tell that everyone here also feels, you know, very happy and very grateful. So yeah, thank you very much. Yeah, it's very kind. Thank you.


Hey everyone, so welcome for this session about the Wikipedia in French that has deleted page for pages for deletion. So why, how, what impacts, what happened before? What led to the decision, how the decision happened and then we are we share link to one case of notability debate about an article in Wikipedia that got not really deleted. So Let's start right now. So who I am? So I'm Jean Squire. I'm I'm going to take my own slide. It will be easier for me to read. So I'm Jean Squire. I joined Wikipedia in French in 2009 and Wikipedia in France in 2018. I'm also on Wikim data and commands Morally. I mostly translate from English to French articles like Moon, Coyote, etc. I also have ADHD and autism as per girls. So I try to promote accessibility in the projects so it can be visual in learning our processes between the editors too. So it's not taxing and we don't lose time in conflicts. So I'm also one of the many editors to the main page of a role of Wikipedia in French five years ago. And of course one of the people that contributed to the page for decisions reform last year and this year. So this is a quite difficult topic. I don't know if you can see the image I shared. I know you can't. It doesn't share well. I shared a funny image. Anyway, so I you will be able to find this slide on the at the end of the session on the session page on the Wikimania website. So let's go directly to how we began and we will start with before the reform, the very origin of the procedure and it has been created the 5th of October 2002 by Anther, which later became the CEO of the Wikimedia Foundation, but later no template. It was just text with returns to the line under and just passing with the enter K. And there were got we got see six major issues raised by the community because it last it led to a lot of conflicts, a lot of grief and it remained in other spaces. So we're going to the next section there were a survey helping to shape out this back to eight years ago and that concluded that the procedure name was no longer redevent because it was more supposed to be an it evolved to not ability debate for pages and not something for just for deletions. There are speedy deletion process too now. And this procedure was also used to discuss the merits of categories, templates and other meta pages. This is more a discussion than a vote and there is an ever-lacing debate on the Wikipedia in French about either just voting or studying the merits of the of the statement of the of the debate made the comments. Of course, in other Wikis, it's often the comments, the quality, but it doesn't work like that for everyone because some people are very strict, they're very square in a way to think that it should be votes. We say it's supposed to be deleted or not. So it's also used by default. It's used by default as a maintenance of netability banners that are named in French admittability are verified and they have to be checked quite often. We have editors creating we got editors creating pages for deletions quite often, but they are well not really for deletion. They are well just to be checked for their notability Nobody really wanted them to be deleted. They were just a question like there doesn't seem to be enough sources. Next, we also have the templates what they were saying. So we had the suppression suppression templates that talks about notability and so those have other templates like page conservate, which is for page kept and it says translated. After we propose for notability debate, this page has been kept. You can view the no-close and outshift notability debate sorry bad translation and also it was not a comment for the values for this procedure to cause conflict and resettlement amongst contributors. Newbies are not where felt very hurt to see their page labeled to be deleted. It was something that was very hurtful and it was not very well understood in their guts and for newbies it was more confusing because they were often just starting to contribute. Sometimes they didn't understand very well how Wikipedia works. Sometimes it could have just be an article moved into their draft space in their own user space. So discussions opens in February the 10th 2021 and is closed in mid-January 2022 and the voting opens soon after. We said the voting period for about four weeks ending at midnight at Paris time because most of the contributors are living in France in just statistics. So there is timeline. Yes, it was a very complicated process. It started too really. They were conflicting with other initiatives like for example, I posted first in the bistro the equivalent of the village pep there asking for opinions about ideas for alternate names or the procedure and meanwhile someone else with a lot of enthusiasm and shake and just launch the process the discussions for the voting without checking this further. This was quite discouraging. There are a lot of types with height and love periods and activity. It was very very dried out. There were a lot of topic executions because the topic was just retaining and avoiding very very conflicting propositions for reform of the process itself. Yes, it was over 11 months and it was almost abandoned and at the end we just said, you know what? Just just launch the vote. Let's just set a threshold for voting and let's just launch the vote. It was a vote with the black method by the way. It was A, B, C to chose and an order in the preference number with superior or inferior or equal. So the goals were to remove the stigma or injunction like nature of the current page for deletion, Pacha Suprimi designation. When it's debated without a page, it's acceptable or not able or not. It's mis-translations for me, my bad. And the deletion debates can result in the page being retained to there were a lot of options like moving the page to another sister project like the dictionary. There were things like just a split or a merge and this procedure was used instead of the regular merger split procedures. It could be just a renaming. It will be moved. I improved the little page, the template for this quite recently by getting inspired by the Wikipedia. So we got the results. So there were two questions and for the first question, there were the Wikipedia page for deletion that will be not titled Wikipedia Notability Debate. Sorry, mis-translations. We are retracting renaming. And the division, there was also a proposal that was kept in the discussions and also put into the voting pages about whether or not keeping the division for expression's opinions to keep deletion, etc., like merging and other options. And people prefer to keep this while personally, while I understand it can be too cluttered with too many comments, I think the choice to put the keep and delete options first is rising the debate because it suggests it should be these two options and maybe it could be proven in some way with more user interface tools in the future, maybe I don't know. And so we had consequences with the case study with a notability issue with the page named Macronet or in English the verb to Macron. And I'm going to try to share this to Michael. I'm going to share the link for the chat so everyone can see this page and how it's ordered currently. And so you can see how it works. So I posted the link to Telegram or maybe I can paste directly to... So how does it work? I just try to open feed loop. I posted the link on your Telegram. All right, maybe you can open in the tabs, please, it's just a page of Wikipedia in French. So Macronet was a verb about something about a world known in the world of Ukraine. And it was a word mostly created by the recurrents in their own words, in their own language because there were Emmanuel Macron, the French president currently that appeared and said it was very deeply concerned. And it was not something about very direct consequence, very outcome. Basically the person is very concerned, says, is talking a lot, discussing a lot, but there is no result at all from this talks and just talking, talking and just nothing. And actually the page was better suited for the dictionary in French. And if you screen below to there were discussions and there were the opinions named Avis in French and there were some kept and massively, massively the delete option was used for a page that was supposed to be moved to a sister Wiki. So this is an interference issue, maybe there is an a bit issue from everyone that just used to post the error to keep on to delete and without really processing the outcome. In the delete, you have a lot of transfer to transfer to move the page. And it's so it posted in under the wrong section, it should be posted and under the other issues and other reasons possible. So what I mean is a lot of people on the page voted for a transfer or voted for a deletion, but it wasn't really for a deletion. It was mostly to move the article to the Wikipedia, sorry, the dictionary in French. So now it was, we had the results and it was deleted and I'm not sure whether or not it was, it was really kept. So yes, it's not on the dictionary in French. So I'm going to share this with Michael so you can have the link too. And so yes, so Macron, to Macron, it's a neurology and it's, it can, it can mean to show to be worried about a situation but doing nothing concretely or faking help. And it was already present in the French media and it was already kind of transition in French too and it's also a word available in Korean. So yes, in conclusion, there are, it's a process that was the change of the name quite led to a lot of changes in the template. It helped a lot to streamline what we mean with the procedure but people don't seem to quite understand how the page of the process to give opinions, to give discussion is working. There are, there is a lot of text and the user interface doesn't seem very friendly for this and I think a lot of, and I think a lot of things are still complicated and some point of tensions between user still exists. But at least one point of tension is solved. And I think I remember that some named up for the procedures in other language, Wikispedias are more about notability and real discussions than votes or to delete pages. I think it will be quite very useful for communities that still have the page for deletion name to today to consider to change their name to for example the Wikipedia in English. Is it worth it to keep such name? Isn't it confusing for newbies and maybe helpful in general for any kind of editor to say, hey, I passed, I started a page for deletion process for your page but it's just, it's not for deletion, it's just for checking. It's still helpful. So I'm finished here. So I think we only have a few minutes left. So if you have questions for me, so please write them down. Do pages still get deleted? Is it just cosmetic? Pages still get deleted but the presentation, the section where a little change, for example, I added a lot of changes with an overcontributor that should have the cost picker with me but couldn't make it unfortunately. And we changed quite a lot at the starting templates used to initialize the notability debates. So we made the language a little simpler. I think it's better word and no but it's still, I think, too chatty. It's not very well organized. There are not images to lead people to have something clear and easy to read. It's not very accessible, I think. Other questions, I'm going to check also the etherpad. We don't have anything for question for the speaker there. Question in and swear tab has nothing. So I'm leaving you when we need to write down any possible long question. There's a lot of reeling noise. Is it better now? What is the speaker on username, please? GN square. I'm going to write it down myself. Doesn't work. I've got a few compatibility issues. So if you want to talk with me, I'm going to be available in the networking space. So we could chat more freely and without the time constraint. So thank you for everyone's. Thank you for bearing with me despite the issues with the slide and the screen sharing. And see you in the networking space. Bye.


He was my godfather. He was my godfather. All the greats of the corps, the, you know, people like Lou Wilson and Bob Barrow, twine and chute, vantagriff, they all sat around my dining room table when I was a young lad. And it's through them and people like them and my father that I came to have this passion and this love for this corps of ours.


Hi, this is George Cao, and in today's video, I want to share with you a way to overcome procrastination and work on a project that, you know, if you think about a project in your business where you think, you know, gosh, if I just had focused time and energy and I felt flow working on that project, it would make a real difference in my business, okay? And I am going to give you this gift. It's been a gift to me and it's been a gift to people who participated in this. This is called virtual co-working. If you have not yet tried this, I urge you to give it a try. Again, it's free because I'm doing this for free right now. So while I'm doing this for free, and you know, probably going to do it for free at least for a few months, please give it a try. Try it out at least and you'll surprise yourself how much you can get done. And then once you come to my sessions, you may then want to schedule your own with your friends or with your colleagues or just keep coming to mine if you want. So, you know, just a quick couple of examples, right? Corby has attended a couple of these sessions. She says it was powerful and an article entirely written, posted and illustrated and on the website, she did this in one hour. Bernie says, did it today. It's extremely productive, inspiring. Kate wrote that this format seems to cut through the resistance that normally only gets overcome in my face deadlines, but it's this virtual co-working is a much more pleasant experience and better quality too. Zuzka wrote, this is beyond fantastic. I now have a site structure and primer ordered topic list that will be foundation-friendly website. So people get a lot done in these sessions. And it's one of the participants said, how does this work? Why does it work? I mean, I'm just working on my own here, but the way it works is because, well, I start off the sessions by just a little bit of inspirational talk. And then I set a timer that you'll be able to see on the screen as you work on your project. And you'll know that we all are working kind of, we're energetically supporting each other, basically. You just work on your project. We basically, in a single hour, we do two 25-minute sessions. Sometimes the second session is 20 minutes. But even in 45 minutes of one hour, you'll find that you probably get more done than even an hour and a half by yourself. So please, I urge you to come give this a try. And I've created a new tool to help you find out when those sessions are a lot easier. The tool is to go to George Cow, here, let me show you this here. Go to georgecow.com, my website, georgecow.com slash co-working, all one word. So georgecow.com slash co-working. And then when you go there, you will see this. You will see this web page. Very simple. If you don't know what virtual co-working is, you can click on this to, well, basically read the article that I was just showing you. So read how it works there. But there's an updated calendar here.  Whenever you come back and refresh the page, it will always show you the upcoming dates. Right now, I'm recording this on Sunday, October 18th. That's why it's showing this upcoming stuff. And then if you want to scroll down on the right, there's an invisible scroll bar, but if you just click and drag, whoops, let's see here. Whoa, oh, there it is. Invisible scroll bar here. Just click and drag along the side to see more, OK? And I usually schedule about one week out at a time. And if you click on any of the events, it'll give you more detail. So for example, at three, OK, make sure you look at this. Events are shown in Pacific Time, OK, Pacific Time. So I don't know if you can change a time zone here. This actually might change based on your, I think your computer might be smart enough to change the time based on that. But if it still says Pacific Time, let me give you a tip. You can go to worldtimebuddy, worldtimebuddy.com. And Pacific Time is basically San Francisco. So let's say you're in New York, then you could say, well, if Georgia's session is at 3 PM on Monday. Excuse me, I have to sneeze here. OK, if Georgia's session is on 3 PM on Monday, Pacific Time, then I look at, you know, Monday the 19th at 3 PM. If I click on that, then it'll show me the sessions for one hour. Then it'll show me, oh, New York's at 6 PM. Buenos Aires, Argentina is at 7 PM. So you can basically put in, I'm going to refresh this to get to the home page again. You can put in another time zone. Let's say you're in Sydney, Australia. So you can start typing Sydney. You click on this. And when you go Monday at 3 PM Pacific Time, what would that be in Sydney? That would be, let's see, that would be, oops, sorry. Oh, I'm sorry. Let's see. Let's go back. Let's go back. How do I go back? Oh, yeah. So click on this again. Let's go Monday at 3 PM Pacific Time. Then you'll see it's Sydney, Tuesday, October 20 at 9 AM. So this is a very handy tool if you want to translate times. But anyway, the times are all listed here. Whenever you click on the event, you'll see how to join. You can just simply copy this link, copy this link, open it, go to that link. I'm not going to go to it right now because it opened up the conference room. But you'll just be able to find that here. And then click on this title again to collapse it. And then, oh, and then you can also, when you click on it, you can click on copy to my calendar. If you use Google Calendar, you'll be able to click on that and it'll go to your Google Calendar and you can save it then. You can also click on this button, see if it will work because I'm on my wife's account right now and it is logged in. So do you want to add this to this calendar? You can click on Yes Add and that'll add a continually updated calendar of co-working with me. And you can always untoggle that calendar, uncheck it if you don't want to see that. So that's an option for you or you can, again, you can click on whichever one you want and copy it to your calendar or just write it down. And then basically at the beginning of the session, oh, right, you can either copy this and go to it or at the beginning of the session, you can come back to this co-working page and just click here. If you click there, that'll bring you into the conference room for the co-working. And I recommend, if you're brand new to these things and you want to my orientation in the beginning, I do recommend you try to show up one minute early. So show up at 2.59 p.m. and we'll start very promptly at 3 p.m. with a two-minute orientation and then we'll start our 25-minute segment. We'll take a break and then we'll do another 25-minute segment and you will be surprised how much you can get done. I'll show you one more thing. Let's say you're on Facebook. I have a Facebook event that I create each month to help you remind you that I'm doing these things. And if you want to be invited basically on Facebook to my co-working sessions, what you do is you go to Facebook and in the Facebook search box, I'm here on my wife's profile, you go to the Facebook search box, you click on the search box and you type in George, Cal, virtual, okay, virtual and you will come up with the event and just find the correct month. Obviously, right now we're in October, so I would click on October, okay. And once you come here, let's say you want to be invited to the November sessions and or the December session, etc., simply click join, okay. If you click join here, okay, I'm assuming you're logged into Facebook. If you click join here, it'll count you as one of the upcoming attendees of this month-long co-working session event. I don't expect you to show up necessarily, but you want to be invited. Basically, whenever I create the next month's co-working invitation, I basically invite the people who said they were going the previous month. So, if you want to be reminded, basically, you just come to the page and click on join and it'll now say going. So I hope this is helpful. I look forward to seeing you at one of these sessions. I promise you you will walk away feeling like it's, well, I can't promise you, but just about everyone who has come to it has been glad they've come. And once you come to it, if you can't make my events, you can always create the same kind of event with a friend or with a group of friends. So anyway, until the next video, I wish you well.


So next session, we have Lukas who is the CEO of Loft Labs and also Brandon from CoreWeave. All right. Is that good? Okay. Hi. Yeah. So yeah, I'm just an engineer. This is Lukas. He's more important than me. But yeah. So like I said, I'm Brandon and this is Lukas. We're here to talk about how we power AI labs, how we do inference, how we do training at CoreWeave. So yeah, so to introduce myself, I'm an infrastructure architect. I've been at CoreWeave for almost two years. Been from basically the start to where we are now. And we've done a lot of changes along the way. And we'll kind of talk about that today with kind of how we do things now. Yeah. And I'm Lukas. I'm the CEO of Loft Labs. I got the company started about three years ago from now and involved with different open source projects. We got V-cluster started. We got DevSpace started. Contributed that as a sandbox project to the CNCF. And we recently launched another project called DevPod. But today it's all about V-cluster. So for, I'm sure maybe some of you know who CoreWeave is. For those that don't, this is the only sales pitch that anybody probably needs. CoreWeave is a specialized cloud for, purposeful for GPU accelerated workloads on top of bare metal infrastructure. We don't do hypervisor layers at all. You access the GPUs directly. And we allow people to scale from zero to whatever they need in a matter of minutes. And that's what we're built for. Purely GPU based workloads. So kind of how do we serve AIML? Just to kind of give you a basic rundown is, we don't have a hypervisor layer. We run on bare metal. Kubernetes K8 is on bare metal. We do support Kuvert for VMs, virtual machines on top. So for people who do need that, we do support that. We have an extremely fast response of autoscaling for our inference, thanks to a Canadian stack that we run, which seems to do really well. And there's also some more talks about that this week. Some of our team contributing to that as well if you'd like to learn more. And our stack is GPU optimized. Everything that you need to run GPU workloads is managed by us, the drivers, the health checks, all that stuff. So you just come with your applications, download your model weights, and you're good to go. And we're open source friendly. Everything we do is basically represented at Kupcon. Everything we run, you don't have to learn anything new. You can just, you know, you can ask questions. We're very responsive. We're very friendly to the environment. So it's, there's no proprietary stack here. We want to note the Tensorizer, which is a really incredible open source, like we're going to open source that soon. It allows us to basically stream models directly into the GPU memory. And actually Wes Brown in the front here is one of the lead engineers on that. He'll be happy to talk more about that this week if you're interested. So come by our booth to learn about that. But yeah, so it's just Kubernetes. It's really simple. We love Kubernetes. Plug. Yeah. We have just two little demos just to kind of showcase what we're going to talk about. The keyword here being Catalyst. Catalyst is what we're calling our next generation of how we're going to support customers, large and small, giving people the same experience. So hopefully we can see this. So what this is representing is we've worked with Loft Labs with, you know, virtual clusters and kind of customizing that experience that allows people to deploy their own full cluster experience without needing to actually provision nodes, right? That was kind of what the power of VCluster gave people. So we take it a step further and we basically either we give you the same experience whether you don't want to buy nodes and pay for nodes or if you need a dedicated isolated environment, we control the control planes the exact same. So all this demo is doing is showing you how quickly we can spin up about 25 completely compliant Kubernetes control planes in our environment. We use a lot of custom, we use a lot of operators. We use a lot of custom stuff, but overall it's nothing fancy, but it kind of gives you the idea of like we can deploy clusters pretty quickly. This is about two minutes to get the first one or two ready. Yeah, it's basically that at least. Yeah, so we run so we run at CD. We have a custom operator for at CD. We deploy the API server, the scheduler, custom components that are required. And this is basically what would start your experience on on core. We basically. And then the more fun one I think you guys are more interested in is we go to the next slide. As we have a quick little K and eight about a limb demo for the Mistral seven B, which was actually an open source. It's an open source model that was actually trained on core. We've seven billion parameters about 14 gigs in size. And it's actually pretty awesome. So this this one's just a real quick demo of basically taking one of those clusters. I just provisioned. I went ahead and pre-installed cert manager, K native, the, you know, the small things you need. As you can see, we're running on RTX a 5000s with men replica set to five. And as it goes to deploy, you'll see on the bottom, that's the remote cluster that I'll talk about in a second. And the top of the screen, you'll see the revision and the pods coming up. This is going to take about 60 seconds because we're not using our accelerated object cache, but it takes about 60 seconds for the models to actually go ready for inference, which is not bad. But with our accelerated object cache and our tensorizer product, we can load about a 20 gig model, about 12 to 15 seconds to get your inference pods up and running. And that is confirmed. You can talk to us this week about it. So we'll just skip ahead. So once they're ready, you can see the revision has become ready. And then we're going to go and do an inference request. Voila. So in a matter of one to two minutes, you've got your inference up. It's going to scale to zero. You can scale up as much capacity as we have. And you didn't have to provision any nodes. You didn't have to do anything.  So that's kind of really the power of what we're trying to present today in this environment is just, you can really do whatever you want, and you don't have to care about any of the boring stuff. Unless you want to, then of course you can. But so to give some context, Catalyst is just Corweave's iteration of a Kubernetes control plane enhancement. It gives you full customizability. You can keep it virtual. You can keep it where you don't care. Or you can go bare metal. You can get a full set of like 100 nodes. You can get SSH access.  So those are kind of the two offerings we have. And then we also combine them together that I'll talk about. And on the right, you'll see, we make use of a lot of CRDs. We've got a couple that represent clusters in control planes, which just fancy way of saying like, what's your IP space? How many API servers do you want? What's your NCD backend look like? Pretty boring. But you do this, that's all you need to do. That's all you need to deploy. It's very simple. And this allows us to do things like training clusters, inference workloads, extensive CPU compute jobs, spark jobs. It doesn't matter. You can do anything. So we like Kubernetes. We run Kubernetes and Kubernetes. Everything's Kubernetes. I know it's like a meme at this point, but it makes things simple because everything's Kubernetes. So to give you some kind of context, we've kind of re-architected our infrastructure because we do run on bare metal, right? We have no hypervisor, so it's a little bit different. We run an internal cluster of eight nodes at CD on-prem. On-prem Kubernetes has always kind of been a pain because you have to manage it. Ideal, but running Kubernetes on Kubernetes is nicer because then you get to use the power of Kubernetes to manage things. So you're like, this is awesome. Let's do that. So we have a bare cluster that kind of stands up like our day-zero provisioning, and then we have a set of other clusters on top. And the real power of this new framework is kind of in the top box here, right? So as a customer on CoreWeave, you'll get your own control plane that's deployed into basically a namespace and then... Oh, that's the wrong way. And then it'll connect to what we call these real clusters, right? So these worker clusters are the ones that have 1,000 GPUs, 2,000 GPUs, 3,000 GPUs. Today, our cluster has 5,400 GPUs, sorry, 5,400 nodes. I think it's like 30,000, 40,000 GPUs, I believe. Something like that. I could be wrong. But basically, each customer gets their own isolated control plane thanks to Vcluster Pro's distribution to be able to synchronize to that. And then you get isolation and you get to deploy as many GPU workers as you want. The other thing that's cool though is that in this environment, you can also do a bare metal cluster. Like we can give you a real thing or thinking if you want and then you can switch. Like we can do that for you.  So it's pretty cool. So yeah, it's a lot of operators. We like Kubernetes so we do a lot of that stuff. We use Coup Builder. We use Argo CD extensively under the hood for day two operations and management. We love GitOps. That's kind of one of the cool things that we do here is we're very in line with what's the industry standard. So when people come to us, we're very in tune with our customers of how should we do things, how do we do it, and it makes it really easy for us to kind of communicate and get people started off the ground. And then one of the best things about this flexible deployment model is that Vcluster Pro allows us to power our burstable on-demand environment that I discussed. But everything between that and like a true Kubernetes cluster is identical, right? So in terms of what we provision and what we give to you, it's the same. The only difference is what you tell us you need. So that makes it like really powerful that we don't have to build two stacks. It's one stack. And some of the other key things, it's like, it's really flexible. Certificates via CertManager. Autoscaling via Prometheus. We have a custom at CDCRD. We have network isolation from the Bluefield DBUs as well as, you know, currently we run Calgo so we get to use, you know, network policies so it's pretty great because everything's open source. We're in the community and it just works. And then finally, probably one of the more cool things is we also have a lot of things specific for GPU style management of the nodes. We have a really extensive HPC verification workflow framework that's based on Argo workflows for ensuring that things like the H100s and A100s are healthy. There's a lot of burn-in tests you need to run. You need to make sure that they're actually performing, especially with new systems. And we take care of all that for you and make sure that that works. The two other cool things that I mentioned was the accelerated object caches. We have regional co-located object caches that can increase your model download times that I kind of hinted at. So that comes standard and we can integrate that into your inference services. And then we're going to be open sourcing a Slurm on Kubernetes, which is basically called Sunk. And that also is coming out, I think Q1. But basically it's, we can run Slurm on Kubernetes and it's really nice, so it's really cool. And then now I'll kind of hand it over to Lukas to talk about how does the syncing actually work. Let's dive a little bit under the hood. It's really great to have a cloud provider like Corvif here be so open about their internal workings. You rarely find that folks go out and actually tell you how their cloud is built up. And we're diving a little bit deeper today. So what Corvif is using internally is a project called Vcluster. We got Vcluster started in 2021. It essentially allows you to create virtual Kubernetes clusters. In fact, it's the only certified Kubernetes distro for creating virtual Kubernetes clusters. We've seen over 40 million virtual clusters created. In the first 12 months that we launched a project, there were only a million virtual clusters around. Now it's two and a half years later and we just celebrated 40 million virtual clusters created. So that's what we're doing. You'll see down here the GitHub link. If you ever want to check it out yourself, you'll also find it at vcluster.com. There's about 3,500 people who start the project, so definitely make sure you check it out if this is for you. What does Vcluster do at its core? It essentially allows you to create secure multi-tenancy for Kubernetes. And I don't envy you in having to translate it into sign language. Essentially, when you're looking at Kubernetes clusters today, you have a lot of replication. Each one of these clusters has Cert Manager, Policy Agent, Istio, Vault, all of these different components. And a lot of enterprises today are essentially spinning up Kubernetes cluster after Kubernetes cluster. Some of our customers, they come to us and tell us, we have 500 Kubernetes clusters. We have 1,500 Kubernetes clusters. Just because every time somebody needs a cluster, AWS told us to spin up a new EKS cluster and that's what we did and handed it out to our engineers. Initially, they all look nice and uniform and over time, they really don't. And then this becomes a whole mess. We've identified this problem and we essentially created Vcluster to solve it. Vcluster allows you to create multi-tenant clusters. That means you have one cluster that runs your platform stack, so you run Cert Manager, OPAR, et cetera in one cluster. And instead of handing out namespaces, which would be the default multi-tenancy way in Kubernetes, instead you're launching these Vclusters. And a Vcluster is nothing else than a pod that runs a Kubernetes control plane and then you can make that available via load balancer, ingress, et cetera. So people talk to this control plane now rather than the real clusters control plane. And that essentially virtualizes Kubernetes and allows you to use the underlying platform stack across these virtual clusters. There's a lot of sharing that's possible. When we're looking at the standard Vcluster, it runs virtual cluster workloads, the tenant workloads inside the Vcluster and the control plane alongside each other in one namespace in the same Kubernetes cluster. That's the default. The underlying cluster we typically call host cluster. What CoreWeave does, though, is a little bit different because obviously as a cloud provider they're very advanced users. You can tell from Brandon, right? And what they're doing is this here, right? I'm not sure if you saw that, so I'll go back and do it again. So essentially they run a control plane only inside one Kubernetes cluster, inside the multi-tenant cluster. And then we call that isolated control plane. That means the workloads that you're scheduling on these Kubernetes clusters, they may not be in that same cluster. There may be somewhere different, but the control plane is essentially in the same Kubernetes cluster, right? And that's a really advanced feature. That's something that we have in our commercial distro. It's called Vcluster Pro. It's essentially open-source Vcluster but packages some advanced features like this isolated control plane into a new distro. And why are they doing that? Essentially security and resilience, right? If you have a faulty workload running, right, or you have a malicious user, they could try to attack your control plane, but if the control plane runs on a separate cluster it's easier to do it. So it's easier to ensure SLA is for the control plane which obviously as a cloud provider you want to do. And it allows also advanced workload topologies. That means you can sync the workloads to different locations. It doesn't have to be the same cluster. What does that mean? We'll take a look at how core we've done this. There's essentially two deployment options they have for their customers. And Brandon was alluding at this earlier. So let's take a closer look at this. Option one is shared workload clusters. This is closest to the standard V cluster where you are sharing the resources of the underlying cluster with the exception that core we've is actually using a separate cluster for this. Again, isolated control plane, we have one cluster running all of our control planes, the V cluster control planes, and then we have another cluster that runs our workloads. And that happens via so-called sinker. I'll dive into that in a second in what actually does that mean syncing workloads to another cluster. But essentially, it means that we start workloads in a different cluster than we're currently in. Notes in a V cluster is a very interesting question. I front-loaded this because every time I give a talk about V cluster, it's the first question that comes up. How do I see it? What does it run around? And the answer is like everything in IT, it depends. There's multiple options that you can configure in V cluster. You can configure it to see all the nodes in that connected cluster. We have a shared workload cluster. We could expose all the nodes to the V cluster. We could choose to show some nodes via node selectors, for example. We could also join dedicated nodes, which is something really interesting. And we could also change the level of node visibility. So depending on which nodes we're syncing, we can either say, give me the full copy of the node and expose everything to the user, which may not be something that a cloud provider can do. We can also use the option here, modification. That means you can remove metadata, you can alter metadata, you can add additional labels. That means you may have some internal logic in terms of tagging and labeling your nodes and you don't want to expose them to the customer. So inside the V cluster, the tenants don't see that, but outside the nodes actually have these labels. So if you want to do that, then the actual node would look. That's the standard options. All of this works in standard V cluster. And then the second option that CoreWeave provides for folks, as Brandon said, if you have funding and you have the money to get your dedicated GPU nodes at CoreWeave, really excited, then you can also schedule workloads to dedicated nodes. So we're seeing here one option is syncing. That's a default in V cluster. And then we also have the regular scheduling mechanism where we obviously have to join that node into that Kubernetes cluster, into that virtual cluster, and then it's really dedicated to that virtual cluster. What does syncing mean? How does it work under the hood? So essentially if we take a real Kubernetes cluster, right, you would talk as an admin to that API server and then there's an LCD controller manager scheduled behind a regular Kubernetes control plan that creates a group context for me, right? So I have a context, there's nothing else in that name space. I could hand that name space out to one of my teams now, but instead what I'm doing is I'm using virtualization, I'm deploying a V cluster. The V cluster is nothing else than a pod running in that name space. Inside that pod we have an API server, a data store, controller manager, and a syncer, which is essentially our equivalent to a regular scheduler, right, that allows you to sync workloads to other clusters or to the underlying same cluster running it scheduled. So the V cluster doesn't necessarily need to know the nodes, right, which is a really interesting concept in terms of how to share and allocate resources in a very flexible matter. But we can essentially see this is a separate control plan running as a pod. And we can now have our tenants talk to this API server instead of the real API server. That means the tenants have another group context. That means the V cluster pod and the real name space that we created down there, they don't see. That means the Istio, the Opera, anything we're running in the underlying cluster, they don't see. They can't touch it. We can make things available to them by exposing CRDs and enabling sync for CRDs. So for example if we're saying, hey, we have a shared ingress control and we want it available for all of our tenants or for just some of the V clusters, we can essentially enable syncing for ingress. But by default we actually just sync pods under the hood. How that looks is if I'm now creating, if I'm talking as a tenant to my API server here and I'm creating a name space, that's an entry in my data store, right? And you can see we support multiple data stores at CD SQLite. We have an embedded at CD option that is going to come out really, really nice feature coming out in a couple of weeks. And essentially when we create that name space it doesn't exist in the underlying cluster. It's only virtual. It only exists in that virtual cluster that is running in that virtual cluster. Those CRDs won't exist in the underlying cluster. So a lot of autonomy for these tenants inside the V cluster, you can make them cluster admin, which is something that CoreWeave obviously wants their tenants to be for full flexibility.  And typically you need a scheduler for this and the scheduler needs to be aware of all your pods and that actually creates a lot of that problem and Kubernetes of like managing that and essentially having workloads distributed, multi-tenancy making this really hard. So what we essentially have is a sinker and the sinker copies the pod from the virtual context to the underlying clusters context or to different clusters context as in the case of the isolate is we actually certified Kubernetes distro. So we went through all the compliance check from the CNCF, right? We run them with every new version of V cluster. So you can be sure if you're using a V cluster or a real cluster, you won't be really able to tell the difference. Sometimes we see companies actually switch to handing out virtual clusters and then their tenants don't even realize that change, that they don't get an EKS cluster anymore, that they actually get a virtual cluster. So what we talked about with the isolated control plane also offers this really nice UI that you can check out. There's a free tier available for it as well. There's lifecycle management for virtual clusters baked in. So you have some CRDs and a controller for managing virtual clusters. You have templating capabilities and what we call apps. So essentially what CoreWeave and others can do is define what should run in each virtual cluster. There may be a virtual cluster, you can do that with this templating mechanism, you can manage and upgrade. It's kind of like an EKS, but you're running it yourself to essentially manage these virtual clusters. And then you can monitor virtual clusters. There's cost optimization baked in. One of the biggest features is sleep mode where you can actually say, hey, if there's no traffic coming into that virtual cluster for 20 minutes, turn it off. Schedule it down. And all the time you can reallocate these nodes or you can auto scale your clusters if you're in a public cloud or with folks like CoreWeave. And then you can also use this dashboard as admin access for internal teams, support tickets, folks debugging virtual clusters. And everything they do is hooked up to your SSO, there's audit logging in place. So you have a consistent log of what everybody's running, any Coup clusters. Yeah. Cool. So, yeah, a lot of stuff. So kind of what's next for this? So 2024 is going to be a busy year for us. Basically, we talked about option one and option two. You got virtual on-demand, kind of like what CoreWeave does today, like you pay for just the GPUs. You don't have to preserve nodes. We also have the isolated environments if you need, I don't know, you need 10,000 GPUs, you can get that. But in the future we're going to combine those. We are working on a hybrid environment that allows you to have a dedicated bare metal environment, but also be able to schedule to that on-demand burst environment through the use of the DPUs and VPC stitching and a lot of really cool networking technology that's going to be coming out next year through a custom CNI. So that's kind of really what's on the track for us is what we're aiming for is giving you a single interface into anything you need, whether it's an isolated environment, whether it's a shared environment, you should have one and one cluster, and that's kind of what we're aiming for with this setup. So you can have a training cluster, you can also spin up inference workloads, you can also spin up one off like Redis clusters or whatever you guys need for any developers who need something random and you don't have to buy the nodes for that. So that's kind of what we're aiming for and that's kind of what's coming next for us. So thank you for listening. These are our boosts if you want to swing by and talk to us. Also this is posted online if you want to get started on CoreWeave if you're curious about some of the inference examples or the ML examples we have and then obviously V cluster as well as up here to check out. So thank you.


Hello friends and welcome back to another Pokemon how to guide my name is Lee also known as Osiris and in today's guide We're gonna be showing you how to find the den where you can catch hidden ability gale wings talon flame Now talon flame has the hidden ability gale wings gale wings is an incredible ability It gives talon flame the ability to utilize any of its flying type moves with a priority boost So when it uses brave bird or max airstream or tailwind or anything like that These moves if talon flames HP bar is full will get a plus one priority Meaning that talon flame can go before anything else on the field ignoring things like trick room and tailwind and other aspects It might affect the speed conditions on the field So a very strong ability, but you've just got to be careful when you're using talon flame Obviously if its HP is chipped even slightly it will Inactivate the ability and it won't be able to use it any longer So you want to make sure that you are Protecting talon flame when you've got it on the field using these and use it early on in the battle as we see a lot of Players doing just to get big damage onto the field set conditions up and then support other Pokemon with the new Rule set coming into play on the 1st of July as I've always been saying within these guides It's a good time now to get these Pokemon catch them train them up and get them ready for when those rules do drop And these Pokemon are now eligible to be used on the ranked battle system. So without further ado my fringe Let's hop into our game. And there is a few dens you can use in the Isle of Armour wild area to obtain talon flame. We're just gonna stock up on some wishing pieces before we do anything else How many do I want? I only need around 10. So we'll just do that and Then what we want to do is come over to our map And I'm gonna go to a den that is probably my favorite place to get talent flame We've had a lot of success so far. So hopefully it carries over for you guys We're going to the challenge road, which is the tower of darkness So you want to just transport yourself up here to the top and come down these stairs and then take a Swift left and come up here and you will come to this den right here And this is where you can catch talent flame. So it appears any red beam So you don't need the rare a purple beam to get talent flame here And all we want to be doing is just dropping a wishing piece In hopefully it's a rare beam. Come on for these guides We need to we need to have a little bit better luck. We've not had much luck today So if that happens or if you get a promoted raid One of the Zera aura or the G max Pokemon that are currently running all you want to do is just come to another den Drop a wishing piece into any random den There's a little bit frustrating because you do end up wasting wishing pieces But it does reset the den that we were currently at and we can just head back to it The nice thing about the Isle of armor as well There are a lot of dens dotted next to each other when you're hunting certain Pokemon You can quickly reset the den and come back to it and drop another wishing piece and would you believe it? Would you believe it? We've got another promoted ten. I Swear trying to get these purple beams sometimes is tedious work it takes absolutely yonk sometimes I've sat there for up to an hour trying to get a purple den sometimes and then situations where you don't want one You get two in a row and I've never ever ever I don't think ever had two in a row ever until now There's something working against us, but we will prevail anyway. Are you joking? Three dens come on. This is crazy. This is crazy. I Can't believe this so we'll try one more time. They normally say a third time lucky, right? But third time unlucky for us and Okay, so we'll throw the wishing piece and we'll try this fourth time lucky And hopefully get this Blinking red beam. Come on. This is what we need all we need is a red beam and now I'm gonna say it It's gonna be a promoted den if we get the red beam here. It is come on. Just be just be a talent flame Okay, so we've got the right beam. That's perfect So if you come into the beam though and it's not talent flame or one of the Pokemon that you're looking for there Is just a quick method invite others You don't need to be online for this hit your home menu come down to system settings down To system date and time just come down to the date not good forward one Take the day forward come back into the game if you quit out of the den like this It will trick the game into thinking 24 hours have passed and the Pokemon will change to another one it has to be from a Wishing piece though. You can't do this with one of the randomly spawned daily dens If you use this method the den will just disappear So you need to be dropping a wishing piece to make sure that this method is working but Hopefully it won't take us too long to get talent flame So we'll be right back when we do have one so through a number of Data scape glitches we finally get the talent flame that we're after so we'll hop into the red den Remember that the talent flame that we're looking for in this den will be a five star and it does have the Possibility to have that hidden ability the gale wings and you can use a trace user as well So that's a nice thing to use to indicate whether or not the ability there or not straight away You can save before the den before coming into this battle if you have a trace user And if it isn't got if it hasn't got the hidden ability then you can just reset the game go back in and then start Skipping again, but let's hope it has got it's gale wings ability and it'll be a good indicator to see From this first turn if it uses a flying type attack or whether or not it goes first because it shouldn't really out speed I time ran at all, but you never know might do anyway But then the more reliable way to tell straight away is obviously with that trace user It will trace the ability from the Dynamics Pokemon and then obviously you can see whether or not it has got that ability or not Okay, so the time flame And it is gale wings excellent, so we have got the hidden ability. That's perfect We have got the talent flame now and ready to actually breed Hypertrain or mint whatever you want, but we do have this hidden ability Which is the better hidden ability that we have access to on talent flames. So my friends that wraps it up I hope you have found this guide useful. I hope you have a lot of success in catching talent flame Especially with that gale wings if it is a Pokemon that you are hunting down and looking to build a team around and We'll we'll leave it there So if you've enjoyed the content do drop a like on the video Do subscribe if you're new to the channel and I will see you all for another episode guide very soon So until then take care of yourselves and bye-bye