So welcome to Jurassic World Alive where my shirt is shrank, which is really annoying I think it has I'm gonna have to go back and look at old footage and be like no Maybe I always look like that I've just become huge No, we are looking at a new dinosaurs Kind of just being released by itself if I if I think I'm getting that right. Yeah, so hold on. Yeah, that's right Oh my god. Oh, I forgot about this. I was saving this for a video I was saving this for a video because I saw some of these hybrids and I thought this can't be real This cannot be real turns out. It's very real very real Well, let me there we go sort of the hair. So first off the new dinosaur Albertosaurus which looks exactly like the one from Jurassic World evolution at least with the eyebrow has eyebrows If I remember right, that's what them The one in just world evolution had look at that. Look at it Glorious and also for whatever reason It's wearing lipstick. I don't know whether that's supposed to be blood Um, but I don't think it is because no other dinosaur just has blood on its snout But Alberta source does so 106 speed a 30% crit chance. So pretty decent at a crit Fierce killer instinct.   You know what my dinosaur team. I'm gonna crit reduce everybody Oh like that. I'm gonna base my my dinosaur on crit reduction. So I never get Crip. That seems to be just you know You know, whatever So I got I don't it once and then we have the new high score for the drone that But I mean that that's a cool dinosaur, right? however We have oh we have we have horrendous atrocities that Lydia has Committed to mother nature this kind of not really being one of the dodo Sevier Oh, look at them. He was running around. So that's a lot of health Level 16 I think 126 bloody speed. Whoa. Okay. Well, that's what's going for it. It doesn't have any armor or Crip And I think yeah protectable it so it can actually heal itself alert decoy Interesting friend HP ability disabled. Okay, so HP over high as damage 100% critical hit. Oh, so you always get a crit here if you do alert decoy as long as you're secure Interesting. There's a delay of one. So that's very rare to get off.  I'd hope you're still secure. Otherwise, it's useless But I've heard that this one's a good one to use so Leave in the comments down below. We've also got this guy the major stirrus met megas met mega stock or us meta stock or us I assume Which looks like a cat with our armor on it level sixteen two thousand three hundred 15% armor and 30% crit chance very good group shield Defense rendering attack. Oh, that's a new one So talk as a high-stage beef as multiples deal 40% of the targets HP very good and And you get a shield, but it's delayed one Now does have any abilities Can kind of resist damage and speed so that's not too bad torn meh stun very good You need that 50% though It's all good with 50% It's like if something does instant charge There's a chance you might be stunned because if you got 75% chance to not be stunned and that is 75% chance to stun I think it's all you'll never get stunned. I think that's how it works. I don't know I think that's the way that Lydia's tried to make it. Anyway, so these scoot over for thing oh Oh, you're an abomination these scooters or as I assume your scooter source hybrid and I'm for I'm for fun It is as well. I get loads of ambicons. Okay, I could probably get this guy pretty high level if I needed Cleansing, okay, that's good revenge Fierce impact. Oh in a revenge. Okay revenge protection as well and deceleration rampage No escape escapee swap prevent lasting one turn. So you got passive you can't they can't escape Good reasons to stun and reasons to speed increase and decrease. So that's very good I think really anybody cares about vulnerable. I don't really see that too often. So that's not too bad, but now Now we get to the bloody worst one the worst offender, which is this guy. I think this is unique.  So Now this is a mixture between lambion mammoth a mammoth already has let's have a look a month I think you already have a few hybrids for oh God Okay, I was it was like no you have a few hybrids for the bloody mammoth Enter the moth is good mammoth theorem is good And I think some of those might even have a unique to them. Yeah, Mammalania bloody Nora, okay Okay, so mammoth DNA isn't very high demand So why would you want to have this guy? Well, let's have a look show you get 10% armor, which I think is right Normal 3000 health, which is very good 767 attacks are not the greatest of attack, but you do Persistent process strikes you can increase it you can cleanse yourself you can do a group heal and you can decelerate an entire team Very good 75% chance of stun at stun resistant Which means that if it's a dinosaur that is going to do the instant charge You're not gonna be stunned by it. Very good. So prevention You hit a mace I'd rather 100% for that and vulnerable nobody cares about so it's not the best and it's also not the best look It's not an original design or shall we say it is an original design because I don't think anybody would Think of doing that. I think they would be maybe you know take the alambias or base Shunking it up putting tusks on it and maybe you know a long nose. There you go They got an abomination, but this guy it's cat. It's to me I Thinks if this was real, I Don't think there'd be much complaints. I think I could see this being a real like sanizawa can beast But because we know it's not it's just it's just like oh god Personally whether I'm the only one I might be the only one But I don't really I'm not really too fussed about that But we do have another one. We have this guy The Andrew Thurden, which oh god, it's it's it's I mean it's handsome. It's beautiful And I think we only need this guy level 10 now. I have been I don't think I've My daughter there. Let's have a look I have 290. Wow. Okay So we'll see when we can possibly get this guy. It's 50 each so Chances all that we can't God no with the 10s or God jesus So hopefully I'm a bloatness after doing a live stream of hoping in my head anyway I was thinking I could do a video like I'm back But I'm thinking maybe it's probably better if I just do a live stream because People will have questions and if I just do a video and you guys will be like, okay and Well, you know if you've got a question at least in a lot I Mean that's fine. This is okay. Oh, oh, I was gonna say I'll take the 10 Because that means maybe in my other high fusing fusions that I'll get better and to be fair When I've been doing Scorpius Rex gen 3 I have been getting some really good cops without like 50 40 and I think I got a 90 a one-pointer Unique creature you are pulling my leg on you but I Come on how many tens was that like? Oh 10 10s. It felt like 10 10. It obviously wasn't 10 10 Okay, well, I guess we'll we will unlock it because I can just go into our Shared sanctuaries. I think what we've just shared one now, so it's up to level 13 at the moment Where are you there you guys are is it 20? Yeah, that's around, but I think 17 is wrong. All right, so Wait, why is it a goat? Why is there a goat making weird noises? It's like I'm killing something that's a goat. No Again It's like they're playing multiples at once, but alright fair enough. Well, we got two more pops So if we get like a 20, I think we've done it if we got a 30 We've definitely done it Now I need to scroll all the way down. They should be like a scroll to bottom There should be a scroll the bottom because like If I'm scrolling all the way down here. I'm not doing anything with these guys. Am I I'm hardly going down here and go ooh the new Delta whatever I want to max that guy up. Am I? No, that's the officer. Although we are getting close. I say close. We're almost halfway there We'll get there actually So a hundred so yeah, if I get a 30 or 40, sorry No, yeah, if I get a 20, we're done. Come on. Come on. Come on. Come on. Come on. Hey There we go. We did it. Awesome. Just what I need.   Sorry. Andrew Thorium Andrew Therium Again a creature that looks like it could probably exist Who's gotten interested? Whoa, it's got a Gaussian blur around it To try and give it. Okay. So what can you do 25% chance to quit very good 5% armor not bad 119 speed is very good. I don't know about its attack and help level 11. You can't really tell Group warning squeal That's brilliant. I love that Shield before attacks lasting this turn increase quick chance 20% and increase damage 25% Lasting two turns and it reduces the speed of the target for 50% Okay So I don't know why it's got a down for attack Because you get increase a crit and increase damage, but the opponent gets a speed reduction However, it looks like the the symbol is making them have a attack decrease, but it's like the speed But okay and rendering attack which has a cruel than a one which does point four percent of the entire HP And you can't escape from it Stun 50% It's not guaranteed Okay, reduce damage good a vulnerability 50% speed reduction good and crit reduction Okay, we don't really need that but if this is a hybrid, you know 50% reduced damage 50% reduced speed Very good Good is some good moves that might when it fuses to something be pretty decent And it's got good every distances and it's got a good crit chance and there's a little bit of armor, which you know Every little counts, but we are now go look at look at Alberta soldier. Yeah, I'm here We are going to actually what I should do is just see if I'm I've had enough model of a source DNA So as you may knows I Have now I am able to upgrade Hadros all looks up to level 28 and actually before we go anywhere before we do anything because I haven't actually done this Let's look into I know how long we're like 60 minutes in my god Let's look at this week's event. Yay So it is Tuesday today, so we're still on the first part where you got galamimus dina chyrus and chyrus and phosphoracus to dark which Galamimus do you really need no anything anybody needs galamimus? Dino chyrus or din chyrus near phosphoracus Maybe if you're going for the hybrid and then on Wednesday to Thursday, you got clenic in which is okay Elucosaurus gen 2 which is pretty decent if you want to just go for a good and good hybrid for that for just the rent General like skill tournaments and stuff has eagle gen 2 or skill tournaments where they're all level 26 Well, the one where it's not a cap or like, you know, they're all the same And then on well on Thursday, you've got some good incubators to get You've got a rare. I don't know what that is. I know the rare I don't know But Friday to Saturday is pretty decent you got a look a source if you want to go for early dominance I don't know if you really want to go for early early dominance because I don't really see it use too much And I definitely don't use it anymore and has eagle which I guess has some Hybrid to go into and dodo which for the dodo hybrid I've heard is pretty decent and on the Friday you've got an epic incubator to get and The important one on these Sunday You've got one attempt to either go for earlick a spix which I see a lot in a competitive play or the pook Daclas, which I think might be the one with the has to eagle hybrid I'm not too sure, but either way some good lineup there. It's really up to which which ones you go for I wouldn't say there's an outright it for me. I think for the commons. I'd go for Fosuracus for the res I'd go for Has to eagle gen 2 or a liquor source. I think myself for the epics I go for dodo hundred percent and for the Sunday I think because I've already got a liquor source level 29 I'd probably go for the pook and gacta less or whatever it is because I don't think I've ever maxed that guy up So back to the actual game. Hello. Um, I do have had a sore looks To level up. However, I think it's 200,000 coin and I don't have that much because I spent all my coin leveling up Scorpius gen 3 I could trade four thousand five hundred four two hundred fifty thousand Coin which would allow me to do that, but I'm kind of waiting for a sale. I will see we'll see so we got a level 26 One of this guy. I'm gonna make that's have a look Oh, there's no nobody's donated. I guess I just did this two seconds ago Well, we may as well just donate this there you go and you know what go go I think a lot of people are asking for go go go go go go go go because they may have been getting for gorgas stitches But now the new scope is exchange three needs it. So Let's do a fusion of a thing is 20. Yep 24,000. Let's see what we get. Oh 60 and a 50 not bad some very low ones though So that is two pops. Unfortunately, not a great deal there Oh, that wasn't very good Brings us to three pops and possibly we need to get to 800 we need to get a turn Oh, there was a 50 there was a 50 and I think all were just ten away for a ten away. Oh, that's a no But hold on. Yeah, there we go. We got it Nice and we get a 40 So we got three pops to four. No two four six. Hey, we got four. We got friggin four pops guys for Scorpius Rex gen 3 and which I would very highly doubt we're gonna actually gonna manage to level up here But I have been in very lucky with it. So look at that 40 For you 40 is really friggin good The only thing stopping me like maxing this guy straight to level 30s. I don't have monoliths But going from level 21 is it for a unique I think it's level 21 or 23 either way We're up to level 26 now. So it's definitely usable. Oh 40 for halfway almost we're just about to get over half way probably will be this one What do we get our survey says a 20? So what was that 80? We got 120 four pops 120 It could have been 40. It could very likely been 40 But for whatever reason E 750 gen 3 or Scorpius Rex gen 3 Is just really kind to me and I like that. So I think I've added at the moment I've got it to tier 12 on health. I think it's tier four on speed I'm trying to like really everything else next needs to go into attack And of course when it's level 30, I'll have what six to seven thousand health and you know, it's it'll be pretty damn good So as you can see have dropped down the ranks quite a bit Hey, so we're gonna smell a lot like I think the meta right now. I've been told is very Swapping swap out kind of thing. So it's a bit tricky now at this rank I always fight against our dentist Maximus first So I'm kind of tempted to put you Taranix in but he's my speed.  Oh, no wait, did he just disconnect? Oh? That's annoying. Ah, that's annoying For him. It's really good for me.  He can't do anything. Oh, no. Oh No, oh Come on. He's gonna have something. Oh He's giving up. He's he's he's thrown in the towel. That's it He's thrown in the towel does now he could do and Oh my god More wrecks gets an absolute. I'm so sorry. I Don't know he would have made a difference If he'd done his Gemini Titan a big hit then he could have switched his Sarah Magnus and possibly killed me And at least then he would have got something okay Well, we're gonna watch an advert and then we'll be right back guys beyond me. That wasn't a proper fight I really that was definitely not a bow. Oh my god. Okay, let's do another one. Shall we I like How I said I'm doing really bad and that's why I'm a low rank right now and then proceed to show you Basically killing a dude without losing a single dino. That doesn't happen. That is very wrong. I'm glad I caught that in camera So here we go three apexes and a the raw boosted. I like how Hadrosaur looks just has like the same amount of help. There's more wrecks Maybe I should have put more health on that thing. I don't know. Anyway, here we go another boys program faster than me Yeah, they they usually are he's got 600 extra health and two extra speed However, he doesn't have the attack now if I get a crit here, which I don't but I could have very easily now Here's the conundrum, right? Do I switch to Sarah Magnus reveal my trap card or do I just let him kill me or do I let him reveal his trap card Oh Oh Fair enough, I'll happily take that Now I'll put in Scorpio Fox gen 3 because why not look at it. He's I never you just bring it in I'll I do I want to go for toxic quills now. I could predict him switching out But I think he's kind of happy losing his modern wrecks.  You know, that's gonna be the case The list speaks interesting interesting Right, so I mean you have precise impact, right which goes through that and He is probably gonna do like 5,000 damage But and he's also was he's kind of like my worst nightmare, and I didn't even do anything brilliant I ran out of time. That's very good No, I was too busy thinking I think he's gonna he's gonna finish me with a speed boost. I think here. I think he's gonna finish with a speed boost No, right Now I wouldn't be surprised if he's gonna go for a switch now He's gonna switch in something to quickly finish on my head. It's all looks and that's a good price to finish off I will admit that's a good price to finish off However, I'm not gonna let him do that so I'm gonna switch to my Sarah minus to hopefully hit his Sarah Magnus Yeah, there's a ceremony. It's after a good Sarah mind. Yeah, that that oh wait, what? Well, we're both the same for the same health. I assume the same speed. I don't know about attack 2300 2000. Oh my god. Are we exactly the same? I think we are exactly the same. Oh, of course. Oh, of course Of course, I should have went this done Hey I beat him and I could actually switch out my Sarah Magnus and I probably definitely a hundred percent lost this one I would say You yeah, I don't know I mean He was actually thinking about what to do that. I don't know why Grip a live I don't I can maybe have a chance to stun grip a live and I think he yeah, he could have mobilized I suppose But then I'm just gonna go for it. Sod it Well, I can't switch out I don't think I can I could I've switched out? No, I don't think so Or did I sorry to not do it there? Well either way He's definitely gonna go for you know his classic You know regenerate or whatever he's gonna do that So I'm just gonna go for mine here and then we'll be on the same page and then I think with two hits It depends what he's gonna do here really does it's a good go for it And he does he does go for it fair play to him fair play to him And then he'll probably go for his regeneration here. Am I able to swap out? No, so with that in mind, he'll go for his emergency heal while he can Now it's a case of what he's got a shield. I think he's won this Yeah, he's definitely one okay, he decided to go for another hit fair enough. Yeah, he's one oh But and another thing we dress a world alive. I want to show you guys Is that the kind of the picture you know when you open up just will live and you get and What's it called you get the splash screen which shows the new or this this titanaboa looking creature So now they or at least it's been put online This is like the hydro boa. Whatever. Maybe I'll throw up an image of it if I remember. Oh, there you go. Whoa So yeah, there you are hydro hydro hydro boa is a hydro boa something like that. It sounds like hybrid boa But it's high hydro boa. Oh my Lord Ryan first in That's an interesting choice Okay, I mean does it have a good attack? It doesn't 2000 not not bad not bad, but we're just gonna he's gonna put him in first aid torting shield Fair enough fair enough. Does it have a resistance to stun? Of course it does course it has a resistance I may as well just keep its attack down So run does a thousand if it does go for its big hit It's only gonna do like well a thousand damage with this. So it's not a great deal. I'll hopefully take that Now I could go for the stun. I don't think I am I'm tempted to go for the impact But I want his shield gone. I want his shield gone. That's what I want to do I think I can tank a few hits.  He's probably whittling me down He's probably got Sarah Magnus or something and he's maybe just get me to the point where he can swap in but I Don't think he wants to lose his model of Ryan. I really don't think he does So at this point he's got really low. I think I Might be happy just to go for the distracting resistant here Sorry distracting impact. I think I'm because I think he's gonna swap out. Yeah, I had a feeling I had a feeling who's gonna swap out And I'm pretty sure Sarah Magnus 2100. Okay, that's a decent amount He's actually probably making his model of Ryan and Sarah Magnus around about the same attack So they're equally useful But I'd rather do that like he's gonna go for the the speed he has to do some damage But I'll kill him and he's only now gonna do a thousand damage Now if I went for the nullifying and saving the resistant That would have been a lot more damage and I'm still at the point where his model of Ryan can't kill me one Hit without getting a lucky crit And whatever comes in is gonna take at least a hit and that's if I want to stay in Um, I think I might I don't think I have any good ones Any good switches Yeah, yeah, I'm happy with that. I'm happy with this. So he's still got his model of Ryan Um, we have 2000 he's probably gonna kill us in one hit now I've heard also the magnetator this guy. Uh, isn't really that useful anymore He's he's been useful for so freaking long and now it's not that's crazy to me um Now Now now now is the question um I could have went for tryco here um But I'm not I'm not gonna go for tryco because I know he's got that model of Ryan I know he has it and it's wait now.   Oh, it's scorpious rex Okay so Can he kill me in one hit? No, so it could end in a tie. It could go for toxic quills and in a tie However, I think he might switch out. I think he might switch out the model Ryan just to finish me Um, and even if you do oh He wanted a tie Interesting in oh on this stone as well Oh Was this a good idea? No Uh, no, that was terrible. I've lost I could have got a tie That was bad I just thought he was gonna quickly go for model Ryan kill Well, then Scorpious rex look at that tryco with all its armor all its health level four. Sorry 30 killed Destroy. Okay. We'll do one more and hopefully we get a regular win You see this is what you don't see with other youtubers. They'll post their wins. They won't post their losses Um right Now I think it's a case of like I'm just used to using my old dinosaurs and a lot of the time.  Um, whoa a tryco that's faster Wow, interesting. So yeah, the main reason the argument I've heard that why Oh, there we go. Oh now I can't kill him in one hit brilliant The main reason why mortem rex Um Is well, sorry tryco rex isn't used that much anymore Is because a mortem with 130 speed can usually best it um I'm just going to go for a regular hit here I don't know what I put a lot of you see. I knew he was going to do that I knew he was going to do that just to get some sort of damage on me. So he's probably going to do like 559 So it's not a great deal. Um, and it seems to me. He's pretty happy for during that guy off Yeah, he's like come on. It's 183 damage. It's not the fastest thing. It's going to get killed So there was no need for me to waste a big hit going for it I Sarah Magnus just for a swapping.  I don't think um, they were 4600 and now it's 3000 Sorry, 2003.  Uh, oh I forget about the resilient strike actually Come on see at like a crit could have killed me there. So I'll go for that. Of course don't get the crit Right, so try go what you're gonna do buddy. What you're just a regular hit.  He gets a crit Right. We're not bad. We're not bad. You can still kill me With some like a Morton that's faster, but I highly doubt he's got a Morton Oh Smiling enemies very rarely see this guy Um, does he have a damage reduction? Uh new New you can do 3400. So I'll just go for a big hit Oh monolo Ryan With a 2000 And it being quicker Doesn't get oh no unfortunate. Oh, we didn't get the stun.  I don't mind you will lose that guy and Um, I think he's stuck in for one more. So He can't do anything well played. Well, I mean not well played that that was unlucky That was unlucky. I don't even want to emote to him. That was completely unlucky. He should have got his stun But again, that that's just the way of well played I'll just say good luck Because it wasn't well played. It that was completely rng Completely rng it depended what if he got the stun there, it could have changed the battle But because I got off my huge hit Um Hey, I worked 4,000 5,500. Yay Hey, guys, we're gonna wrap it up there. We've enjoyed this video. Leave a like until next time. I'll see you cuties later. Oh, bye


We're here for KubeCon, CloudNativeCon, part of the CNCS, and we've never missed a KubeCon, been there from the beginning. theCUBE has been there documenting front row seat, all the action being on the, in the arena, as well as front row. I'm John Furrier, your host, Rob Stretches here with me. Savannah Peterson's been on theCUBE. Joe Peterson tomorrow will be here. Rob, great to see you. We wind down day two. We've got a great special guest, Joel Inman. He's the CEO of compute.ai, CUBE alumni also presented in our SuperCloud 4 event recently in Palo Alto. Joel, great to see you again. Great to see you. We've got SuperCloud 5 coming up. Not only we don't have them this close together, but because of the Amazon's web services and annual user conference, we're doing a special edition and coming off the heels of KubeCon, Microsoft Ignite, open AI developer day. Yesterday was a huge success. The Amazon show is going to be the battle for AI supremacy. It's all the conversation everyone's talking about is AI. And you're smiling because I know why, because you guys have a product coming out and it's out being developed. Compute.ai is your company name. It's also your URL. It speaks for itself. We love more compute. It should be oxygen as Vikram said on theCUBE, SuperCloud 4. But here at KubeCon, this is the audience actually gets into the, it's into like hardware and infrastructure to build platform engineering environments.  That's a long-winded intro, but welcome to theCUBE. Yeah, thank you for having me. And I love talking to you guys because it's a continuing conversation. You guys are evolving your thoughts. You're doing research. You're putting out different thought pieces and feel like we're able to join in and just kind of come right along with you. In terms of kind of what we do and where we're focused, we're building the compute engine for AI. It's all in the name, right? And the way we see the world is that AI ML is going to drive the future of compute, compute needs. It's going to be machine generated SQL and it's going to require a scale that we've never seen before. So we're implementing efficiencies within that compute layer to be able to handle that demand. This is a great topic. We're going to unpack here. Before we do that, I just want to mention the folks you guys are a startup. Self-funded. Some angel. Not entirely self-funded. But pretty much not the traditional VC backed company. It's a tough market right now. What's it like being an early stage startup right now because you've got, it's a buyer's market on the venture side but it's a huge enablement on the AI side. It's a huge wave coming. What's it like? You know, I think there's good conditions, there's bad conditions, but sometimes when you have a strong product, a strong team and a strong vision, those are the factors that really transcend market conditions and finding the right capital, visionary capital that kind of pairs with your vision is essential. So it is a lot like matchmaking. But funding is just the lowest common denominator. Everybody needs money, but who are you going to partner with? Who's going to take you to the next level? Who really understands your vision is going to introduce you to the right people within their network, who's going to help inform your team and grow your team and really be right alongside with you as you grow. You know, that's what we're looking for in investors. What are the opportunities for entrepreneurs out there that want to go get VC, venture capital, because you don't really need that much to get in the game now, but to scale, you probably will have to do an institutional round of financing through a venture capital, although again, lots of changing in that market, but still, you need capital to grow. What's the opportunities out there for entrepreneurs? Well, I think the opportunities are to have confidence in your vision and just to continue to press, who do you know, who do you know, introduce me to find the right people that are going to back you? All right, let's unpack the compute, because you mentioned something earlier, I heard you before we came on camera, talking with another entrepreneur and influencers here around how you see the next chapter after our current one we're in, because we're in this euphoric moment of chat, GPT, open AI, just had their development day, you're starting to see that grosser, and by the way, they're lowering costs, opening up the context windows, so you're starting to see that progress. What's next, after we get through this first wave of AI, what's next, and where do you see the compute being the key there? Yeah, great question, so love all the attention that AI is getting through chat, GPT, and LLNs, right? I mean, the cool things you can do with it, you can cheat on your high school essays, you can manufacture marketing terms out of thin air, there's a whole world beyond generative AI, and when you're looking at the AI implementation of the future, Enterprise A is going to come with all sorts of different models, and it's sort of like hearing a lot of people say I was there when, I was there before chat, GPT, because the reality is we have a community of data scientists that have been working on this for over a decade, they've been training their models, and training their models, and training their models. If you look at the Databricks survey from the summer, one in three models are now being operationalized, okay? So the way we view it is that it's time to move from training your models into production of your models, into implementing those use cases, and generative AI can't be applied to certain workloads, so I'm thinking of credit card fraud detection right now. When you have that generative aspect of AI, that's kind of licensed for the AI to come up with some hallucinations, which you cannot absolutely have, so it's more like an inferential AI, so bottom line is as AI starts to infiltrate our various infrastructure, that's the second way, if that's where Enterprise A is going to really come up with. And where do you see the unlimited compute opportunity because that's kind of your narrative right now, is talking about this idea of unlimited compute, like oxygen, it's going to be plentiful for the problem set, which is data. What do you see that fitting in? What problem are you going to solve? So the way that everybody is thinking about compute right now is AI is incredibly compute hungry, we know that, right? We're buying as many GPUs as we possibly can, they're flying off the shelves, we're even having to rent them, there are startups that are taking GPUs and they're renting them by the minute and by the second, right? But as you move into the fabric of our infrastructure, you're really going to see GPUs and CPUs working together and they're going to work together in a common SQL environment. So you have our data platforms, you have Spark, Presto, Trino, they all can invoke models using UDFs, they can all kind of connect right to that AI, you have a big query, you can go right from your trained model into a production model, when you're having production, you need SQL and you need to be able to operationalize that model at cloud scale. Is that how you see really compute and data coming together or how is it that, because there's a lot of people taking different approaches to the platform, be it from a storage up perspective, be it from like you said, the data warehouse data lake down perspective and then the apps, the data apps are being built on top of those different data platforms and AI being a data app as far as I can, it can be a, not a data product but more a data app where it's using multiple data products to go maybe I have one for the CFO's office and maybe I have one for HR, we call them SLMs or segmented or specific language models for those. Is that how you're seeing this kind of more than one data platform for the right type of AI? Is that where you're seeing it? When you think about the platform required for AI, so I kind of touched on it but I didn't complete the sentence so let me complete the sentence. You need GPUs and CPUs working together. You need to feed that AIML model, you need to feed it structured data, you need to feed it unstructured and semi-structured data. So you're going to have vector databases, you're going to have relational databases, you're going to have GPUs, you're going to have CPUs and providing the compute infrastructure for that is going to require a SQL based framework that is able to scale. The output in the backend of many of these AIM models is machine generated SQL. So we're seeing these use cases in business intelligence where it's spitting out complex SQL automatically. And then it's going to layer deeper, you're infusing AI into those BI tools that's going to generate 1000 times more SQL in the future. That complexity of that SQL requires compute efficiency and that's where we come in. So we're providing that compute efficiency to scale in a platform that hosts AIML models, vector databases, relational databases together. Where do you see the integration happening because one of the things that we're also seeing is the large language models have all this training built in, why not use it there, integrate that into my data infrastructure which might have proprietary data or no zero tolerance for hallucinations or any potential miscue. So this idea that you got to blend them together is a big topic and people are looking, what's your vision on how you see that playing out? Because this world is going to be dealing with a lot of data, machine generated data, whether it's SQL or other stuff, you're going to see dynamic things happen. You know, I think it's a broad question. I think you break it down into pieces and you say, okay, well, what is my use case for the AI? What do I need it to do? And you have these LLMs that have a chorus of public data, publicly available data. Well, essentially what that is is scrubbing the internet, taking the entire internet and saying, we're going to feed it back to you in ways that make sense to you. But other sort of use cases, other sort of use cases require private infrastructure. So I think you're going to see that mirroring sort of the cloud infrastructure versus on-premise infrastructure discussion. Do I need it to be private? Do I need it to be in a Colo facility? Yeah, I think that's what we're seeing and we have this idea of a power law and that John, myself and Dave Vellante and George have worked on. And I think part of what you see is, again, that the size of the models for those public ones that are scraping the internet and things like that are massive and they're up kind of at the front and the top and then the power law comes and there's this long tail that's kind of being pulled upwards from a size perspective, but the number of them and the specificity of them is very long. Like you have, once they're specific to telco, finance, like for instance, I use the example of if I'm building 10Ks as the CFO, that would actually be a really good job for a LLM to go and do is or an SLM to go to very specifically, but I want to keep that data private because it's my financial data. Are you starting to see people engaging with you that says, hey, I'm looking for this compute for this and I need the security and the kind of walled garden as it would be? Yeah, oh yeah, absolutely. I was on the phone with someone earlier today who was doing credit card fraud detection. That's why it kind of pops to mind, right? And his issue is, well, we need to keep this data absolutely private, absolutely secure. Can you imagine the implications of people's credit card information leaking out? I mean, yes, you can because it's happened before. But if AI gets a whole of it, it's a whole different ball of wax. So there's absolutely the use case and I appreciate that article you did on the power law because it's a beautiful graph. It shows that the long tail of vertical specific AI, that's going to translate into on-prem data centers. Not everything is hosted, not everything is open. So we're going to have a mix and match of solutions that are necessary. The way that we're looking at it is compute is compute. And when you have GPUs paired with CPUs, you're really going to need to get the most out of that platform. I got to ask you about data management. We've got a couple minutes left. I want to understand the implications of how the data management market changes with this future. Data formats have been a big discussion for proprietary formats, open formats, data bricks, they introduced concepts over kind of mind-blowing, Rob. Remember, you got Iceberg and Parquet out there now. Data management clearly is changing. What's the impact and or order of magnitude, importance of these formats? Can you scope that for us and how you see that? Sure, so the proliferation of Iceberg and Parquet and the standardization on Iceberg and Parquet, you know, it's fantastic for data lakes and cloud data warehouses and everybody to kind of in the Spark ecosystem in particular, Spark, Presto and Trino. But it's much more profound than formatting. And the way that we view this at Compute AI is for the first time in history, you're able to separate transactional workloads. So your typical DDL and DML from queries. And queries are the ones that are taking up 80% of our compute requirements. So what we've done is we've built a query engine and- 80% is coming from the query side, you said? 80% of compute or more is coming from the query side. And this DQL, okay, by separating that, you can build a dramatically simplified engine that is focused on queries only. The time to market is fantastic. It's fast, anybody can do this. What we bring to the table is to say, aha, now this is possible, we can build something that is far more efficient and utilizing the hardware resources that are already there that has never been done before. Joel, really appreciate you coming on theCUBE and just getting shared in the vision. We love the, you know, I love the URL compute.ai. I think it's a great name speaks for itself. I love the idea of compute as oxygen.  The world wants more power and more compute. So great job, great mission. For the last minute we have put a quick commercial in for what you're doing. Your status as the company, are you looking for funding? Are you knocking on doors? Are you waiting? What's for the people who are curious on how to engage with you? Whether it's an investor, potential investor or customer. Are you open for business? Give the quick pitch. Yeah, okay, so yes, we're open for business. So I joined the company about five months ago. Before then it was just the founding team of engineers, so the four engineers. So only five of us in the company now but we're getting a lot of traction. We're empowering channel partners right now. We're also speaking with customers and we're engaging with customers. The quick commercial on us is the compute efficiency that we're seeing, we no longer require memory over provisioning. So we are dramatically shrinking the memory footprint that is required for compute. And when we do that we balance the core to memory ratio. We run CPUs much higher efficiency and we're getting a 10x performance improvement while reducing infrastructure at the same time as 5x. In terms of the stage of the company we have early capital and I mean, my job we're always raising capital. We're always in those conversations and as I mentioned at the beginning we're looking for those partners to really share in the big business. What's kind of profile investor you're looking for? If someone's watching, is there a certain category or mindset or background affinity that you're looking for to have that match? Obviously you guys are, I won't say age out in terms of you guys are systems guys never age out with systems. You're not the young 20-something year olds. I mean, Rob, we're starting a company you're competing against 20-something year olds. This is the big challenge. What's going on? We're looking for big figures. We're looking for big visionaries who see the world the same way we do. This machine generated SQL is going to rule the world and we're providing the compute for them. Joe, great to see you and again congratulations on the venture. Love the idea, we'll be tracking it. Thanks for chairing. Again, AI is just beginning. The picks and shovels, then it goes into mining, the data and again, compute will be a big part of it. Of course theCUBE, bringing you all the compute action and content from KubeCon, we'll be back as we start to wrap up day one. Stay with us, we'll be right back after this short break.


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Okay, let's start welcome to our session Volkswagen's group IT Operations team adventurous journey to the land of open stack. My name is get pussman. I'm with Mirantes My name is Timon Schultz Yeah, I'm with folks folks wagon The Volkswagen group Consists of 12 brands and financial services. It's not a brand but part of the group well-known names like Volkswagen Audi Skoda and others and the Volkswagen group manufacturers cars in 31 countries 121 production sites and employs 610 K people in Manufacturing cars or services for car owners financial services stuff like this and they built 42 K cars per day and Ship them to 153 countries And they made revenue out of it 230 billion euros per year obviously Organization of this size needs IT and we are from infrastructure operations one part of the IT department of the group IT from Volkswagen and We manage or the group manages the department manages four data centers 7000 service and employs 80 plus people and we are talking about the Traditional part of the IT not about the cloud. So This department manages more than 250 business business critical critical applications And that's what we in the cloud would call the legacy stuff But that's the these are the applications that create the revenue currently So a very important part and there are multiple IT departments and other brands as well So this is not the only IT department. There are more or less independent IT departments and other brands as well The project we talk about today is the VW group IT cloud abbreviated the VWG ITC and we have two Major goals in this area The first goal is to support the business objectives from Volkswagen with respect to a digitization and new markets like Connected car IOT car sharing organization things like that and the second one is We follow a slightly different paradigm than in the past we don't try to Press people to use the technology from central IT We try to convince our customers our internal customers that the offering that we have is a very good offering and Competitive to other offerings at the market. So we have a product and we want to sell it to our internal customers And convince them with our offering But besides of that there are more specific goals for this project so on the one hand it should be in the future the global integration platform for all brands which means they could participate in building the cloud in operating the cloud and Running services on top of this cloud or their applications on top of this cloud Even if it's connected currently to open stack It's not the project covers also hybrid cloud approaches. So public cloud as well. It's not only private cloud Alongside the the project and the technologies one aim is to foster methodologies connected to cloud to the cloud model like DevOps or HL development HL processes and the innovation in IT in general The major value that we would like to Deliver to our customers is to help them shorten their time to market for their products for their applications For example for connected car or digitization products to bring as fast as possible their functionality to their markets But because it's a Volkswagen product for their internal departments we have to cover or embrace policies from governance from compliance as well To deliver a secure product to the to the customers and save the data or safeguard the security of the data of our customers and By using open source by the way using open source and big corporate organizations is very challenging By using open source. We also want to use the model behind open source the collaborative model to create software to Run software and to enhance software in the future So we W also aims to introduce kind of a corporate open source model into the company To help the various departments developing a software so that one department creating software would be able to Benefit from stuff that was already created in other departments and use the same stuff For example for a config management couple manifests, whatever it is heat templates to have joint forces on creating the stuff And one Target in the back for sure is cost saving as well The cloud has a lot of advantages over our traditional systems with respect to cost reduction And that's one of the targets as well Currently the cloud is deployed only on one location in Wolfsburg in the headquarters of Volkswagen But there is already planning to deploy it in various locations around the world This is a global approach. So the cloud will be operated and deployed in multiple locations in the world the next one Probably will be deployed in the Czech Republic and after that the next locations will be somewhere in the area around the world So a pack either North America Latin America or China or Asia in general As already mentioned, it's a public cloud There's a part for public cloud as well and there we work Together with the usual suspects in this area the big public cloud providers around the world That's one example of the workloads running on the cloud. It's on the car configurator For the Spanish market that was the first application installed and running on the cloud Actually, if I would click this link, we could see this application Ricardo I have seen you a few minutes ago. There's Ricardo He invested a lot of work into this application and suffered a lot from our problems at the beginning But if you want to know how it feels to deploy on this cloud and consume this cloud Then you should talk to him. It's it's one of our dear dearest customers now This is the timeline we followed in creating the cloud so the initial planning took place in the middle of the last year VW was already consuming virtualizationization technologies for example and the next logical step was to to deploy a cloud and to use and benefit from from the cloud after that we started a proof-of-concept phase and selected the vendor and Started the pre-production so until the end of the last year there was we built up the first system Put it on to pre-production and presented it to potential customers so that they would be able to Help us pivoting on the services that would be required in the first setup And then the system started in production so for for example the ngw website Started implementing on this production website and we added platform as a service as well So there is pivotal cloud phone. We're running on this platform as well And then we are now in the phase four and that's the face. We are currently working in We call it the rise of the Titan because we added a lot of Stuff or plan to add a lot of stuff and we are currently developing all of these services and in this timeline we picked out two Yeah, we could call it incidents, but major decisions to Change our way. The first one is the samurai versus ninja incident and the second one is project versus product management summarize versus ninjas I already mentioned that The project was born in the traditional department and this traditional department the approach is to plan things in a waterfall model plan releases and release these releases after six months for example Deploying it on golden machines very reliable very expensive and Do approvals for specific parts or provisioning for example of parts of the resources manually And it took it takes months or years to deploy in the system But it's very reliable high quality and it works But it takes a long time and if you have problems with your planning or issues with your technology Then you have to start over. It takes a long time on the other hand in the cloud area You have an agile approach. You have continuous integration continuous deployments things like this You try to leverage benefits from commodity hardware for example And you have automatic way workflows and your aim is to deploy in days or weeks, but not in months and years But we want to benefit from both areas so if we introduce cloud we want to have kind of the same quality from the old world and It took one decision We staffed the team from resources from the traditional team and said okay We want to achieve all the benefits from benefits from the right-hand side But you want to do it with a specialist with the subject meta experts from the traditional world and Try to infect the old world with these method methodologies as well the second one a second important change was to Move from project management to product management. So the traditional world is organized with very Precise project planning. It's all about scope cost and Quality and schedule, but it was done on department level. So the storage department plans something the operational department plans something something the server operations plan something and at the end That doesn't necessarily fit together Especially if you are under time pressure and you want to deliver a benefit to the to the to the business For example for digitization workloads. You have to be very fast We suffered a lot from this because from from the silo point of view it was Very understandable why the departments did this but at the end there was there was a problem to bring all the things together So we switched to a product management approach which means Think about your service as a service for a customer. What are you internal customers? What is the product? What is the value for the business? What is your market? Do you have a market for database as a service? For example, and that was very important especially because We required from these products are on us who create the the products that they Incorporate operations as well. So they have to deliver an operational and support model for their services Otherwise like in the in the old world There was a gap for operations, especially And one of the benefits is we have roadmaps for our products. We have minimal viable products. So if there is Something wrong in our planning or we have Misunderstanding of the requirements of our customers because we we are able to do pivoting on the Features of these products very fast. It's a model for fail fast and fail save This is the face. We are currently working in so we call it the rise of the titan because it's huge These are the products the 60 products that we are currently developing There is nearly everything that you can imagine a private cloud model. Some of this is hybrid cloud model as well But we have also products like cross services, for example, that's automation all the methodologies that we need guidelines for for the developers all the workloads to be integrated on the cloud as well as Workload onboarding. This is very very important You have to consult your customers your future customers these customers may come from a more legacy model as well You have to consult them. You have to help them to leverage all the new technologies and all the things that they want to use and consume on the cloud and Make them understand the model that you're working in So now it's my turn thanks, Gert Thanks for this talk and for this part of the talk and for all the support you and me want to start giving so This is a second part and I'm responsible among other things for the operations of the group by T cloud of the on-site group by T cloud and What all people tell you is you have to change your organization to be successful with cloud For so far to me nobody pointed out of exactly how I should do this I haven't got a recipe either, but I would like to invite you to share some experiences some consequences we or Some recommendations we draw from this and how we want to proceed on on this matter If you have any questions don't hesitate to ask straight away We will have a Q&A afterwards as well so Yeah, we'll see how So Gert pointed out that Not all of you will we be aware of how traditional IT is is done and I would like to start with with the Rackymatics for server operations So if I have a server Service might be a Linux service it will involve a lot of teams like server ops over planning storage Facilities so acclimatization and power supply We can go on forever and it will involve like 150 people in in total to to give a service of Of that quality With all its drawbacks So imagine in this direction Below and in this direction we can could virtually go on forever. We could describe more tasks. We could describe more More teams it doesn't involve applications and so on this models changes quite a lot We had a rough sketch Where what parts the green ones the cloud operation Team will be responsible for so it's infrastructure life cycle management for instance, which was another department before It will be is the hardware for the set storage as well It will be the controllers it will contain Contention Serious parts of the network Obviously quite a small thing at least here the open-stack control plane But there is lots of other things infrastructure monitoring infrastructure background and recovery and so on which was a shared responsibility before So quite quite a change from this one to quite a green field in both meanings of the word in this diagram and To make clear what changes and what challenges we had we took a couple of interviews We have some co-authors to so to speak and had And recorded a couple of different view point of point of view like customer security team and so on And we will share some some quotes or some expectations from from these Stakeholders that is so to speak and we will start with With the customer the customer always challenge you with with the public cloud supplier in this case we choose a AWS because it's by far the largest and by far the one with the most services and they say AWS does it that does have it? Why don't you? Yeah Because we just started so The recommendation is you have to be very very clear about your world map. You have to tell them. Okay. It's not there It might be there at that point of time You can a color a collaborate giving us requirements also on Most people are quite happy if they know, okay, it's not there But it will be there in half a year or a year or whatever We are working Together with a product thing on this Then the cloud ops is always the last resort for for a problem In an organization like ours people just called the cloud ops team and Get informed that while installing the tenants they forgot a router and that's why there is no Network connectivity for instance So recommendation we We do draw from this is that you have to provide for the whole organization Proper customer training and onboarding. So it's not it's not like providing a website where they can fill in and It's it's just not the way it is What happens a lot is that people have problems with with IT in general and Use the cloud as an as an enabler to solve this problem the most prominent is that people call me Yeah, but I just can't Can't develop software with a Windows client Which is the only client we provide as a group RT in Wolfsburg Yeah, I don't have a good answer for this My recommendation is stay very polite when you come across these kind of requests Then there's a special thing in a large organization which has had IT for a very very long time and has mainframes and Oracle databases and Microsoft SQL databases made name any technology We will have it and Obviously People want to connect to back to back end systems and like a legacy systems And this is kind of Pandora's box if you start on this one you you'll end up in in trouble in a way and You have to be very strict about that you require statelessness because it will Enable you to do operations afterwards But in a way that you help the customer To create a migration plan might be that you first put the front end into the cloud and afterwards other parts like Ricardo did Not that you just don't say okay, it's not possible So obviously my team is has some As a point of view as well What drove me a lot as being part of IT for 15 years or so is that about 60% of the accepted incidents led to serious improvements of the of the Of the platform so If something did not work it wasn't fixed in one Location and the other locations were Forgotten Which brings us to the recommendation deploy immutable infrastructure, so do everything as code and to see ICD Be quite modest start with a very very small test set and extended Because in a product and Project point of view if you start huge it will be stripped from the product play and If you have testing in place you can quite Quite easily in enlarge it, but you can't afterwards injected In which test cases in word What struck me a lot or most in this whole journey was that Harness Did call me? Yeah, we had an incident was a was a load balancer as a service it Restarted itself automatically and Reinstalled all the VMs Coming from a point of view where such a decision would usually in take a meeting of Approximately five manager to decide whether to To restart it because some of the services are running and others aren't Yeah Be confident a lot of things really work they People just don't tell you if they work they really work they do And what what we have an experience is that there are two kind of of users We call them cloud citizens. Those are familiar familiar with AWS or Azure or whatever Which are critical and very demanding and cloud immigrants They need a lot of help, but after that are quite happy What help us there is that we have a Concept which is called tenant for free. They get a small and one year free tenant where they can just play around and After that people knew what to expect and whatnot this was said a lot so of Course my management takes a point of view as well actually part of my management is on-site. So I'm have to be a bit polite on this Cloud is One expectation accord is cloud is just a new platform and this heavily heavily underestimates the level of disruptiveness it has and I think we are quite successful in Telling people how disruptive this model is and how huge the shift is in responsibilities and all these things Another expectation is Is that any new workload can Without any modification run on the cloud A quote for this is open-stake is a cheap replacement for VMware, which is not quite true What helps there is that you Should have a good checklist what means cloud ready or cloud native and by any means stick to these conditions You will end up in a lot of trouble Another thing what what the management always says not only in cloud is that you can do it on top Because you have too much spare time. I won't comment on this general problem Being very European very German organization we have specific employee employer expectations and One is that we stick to our stuff very very long. It's quite common that somebody starts at VW His or her career and ends his or her career Like 35 years or 45 years later Which means People are technologies are always place place where people are not our recommendation is That you have to train and crawler shy the stuff a lot For cloud operations, which brings me to the next point Experienced stuff is hard to find At least in Germany, but I get the impression that every other boss is having we are hiring So it doesn't seem to be a German problem alone Yeah, see above you have to train If it takes longer and it takes longer Another thing which I embrace a lot is that my management the general management sees this as sees a lot of synergies They want us to deploy the fitting Technologies from cloud like lot of testing like CSED like conflict management name it to be pushed back to traditional IT to have synergies to have More advancement in traditional IT and I Find find this is a very good idea and We try to serve as to take people so to speak part-time from from the traditional IT job Being a network are being a storage guy being a server guy or doing conflict management and traditional IT and deploy them in in the cloud and Especially we Make them responsible for a new product and people are not the way that they just forget when they have Forget about it when they do the other job. They see okay. This is this is the same I can deploy the same to the same software the same whatever the same principle there and there The security team is They are not on site, but I have to have to give them My high regards. They did start off this journey with us and they were very collaborative and Both of us learned a lot on this Their initial point of view was okay, we have a set of rules we apply it to this technology as well Which does not work too good So commendation from our side is involve them as soon as possible Basically at the first First meeting invites them we want to do this and this and this Help them to to do policy involve involvement train them in the technology as you train your own stuff They will There will be much more Understanding and they did a very good job on this Then one thing which is always so to speak unfair to the infrastructure the platform has to compensate for any deficiency The application has that's why we have said many fireballs Which the platform is not really responsible for Our solution is which we will implement in the next phase is we will have user specific tenant types We will have managed Types where they can't fiddle around with a minute with a network Too much and we will have unmanaged where they need a tight security approval approval and where they will have to to address risks and Countermeasures and all these things and one quote from them is no Programmer or developers cares about security And I can understand the point of view on this Our recommendation is embrace security concerns tell them yet. Okay. We know there is a loophole. There is some risk and we did this and this and from a technical point of view you should Introduce security screening as part of your As part of your application CICD So what we do is we screen The images we generate for some known mistakes and all these things Which is a very good idea and Last but not least the developer developer's point of view is For instance github bit bucket any mirror you can name Is a reliable cure source of Software to be used in the in the cloud and this is not quite true And as get a pointed out the private cloud is required to do a surplus to AWS We surplus in enforcing security rules for instance Hence we restrict Access to these software things It's a hard work, but You have to explain your developers why you do this Why you don't want them them to use bit bucket or whatever directly and that there are things they can use in In a in a matter and that it has got a consequences legal consequences IT security Consequences it might have even Financial consequences if somebody decides on installing Oracle in the cloud Because you will need a software license for this What what they expect as well is that bug fixing has to be has to occur instantly We learned this quite a hard way and we suggest that you do the testing together with with your C with your developers so that they really test end-to-end that they That they test the infrastructure as well as the application and so on and another point of view they take is They want to have non-invasive Bug fixing which is hard So recommendation is that again communication be precise and strict about your service levels And about the state of the product when will they have multiple clouds when will they have a global open and so and so on We do struggle Get added sometimes without me knowing My point of view is we struggle a lot I don't want to lie to you. It's just another point of view. Yeah, it is We have I addressed this already too few resources and skills This is a general problem. It's worsened in our situation and I think in every cloud start project that New products come into production that fast that there is no relaxation time After you finish the first one you get straight to the next one What I find personally very very hard is trouble shooting in deep network issues This is from my point of view the far the far hardest We do struggle in configuration management in particular in August orchestration Applying updates to the environment we struggle with We struggle with to automate configuration changes to the environment this kind of works But having subsequent actions in other systems is hard and to automate them. So if you If you Change a Parameter on some log file collection thing you have to you might have to restart a couple of services on other computers as well Which is hard? And so to speak the the next generation art is to disembark without disruption So to summarize The recommendations be very transparent about your capabilities about your restrictions about your roadmap be patient on kind all I myself hadn't got a clue like 12 or 18 months ago what the cloud is about And most of my customers are in this situation now Give them time to to learn this as well Be aware. It's not just another product. It changes the game Walk in their shoes. What we learned a lot from is we have certain Let's say services which support the cloud like mirrors like repositories Customer portal and it's very beneficial if you do them in cloud as a cloud native Application where where possible it teaches you a lot be communicative do management of expectations with the same one as the first one or Be preemptive of an overwhelming Demand people do want this They actually do They might use it and they might Come up with incidents So if you don't do this and we are struggling there as well a bit You might be a victim of your own success you you opened a box of candies and now The whole school is gathering around you So to speak Surprisingly little problems are technical Almost all about skills resources and the shift of responsibilities And we did state to contributors already Which were Hannes and Ricardo there were two others Fabio and Nardeshtar Who helped us Being interviewed sharing their experience to us Thanks a lot again to this and Next slide is Korean a we have questions. Yeah So so it doesn't seem to be a micro can you go to the mic? Thanks. Thanks Do you have plans to extend the openness that usage beyond the cloud application? So let's say be the eye Classical servers like as a servers or you think it's not possible for a company like you don't know if I get it correctly If you repeat from my company we are Exploring different usages for example the BDI Problem on top of open stack For example SAP on top of open stack. This is not what you have been told. Do you think this is possible? It's not yet your map. I Personally think it's possible, but very demanding So it's a challenge, but I think it's possible We do We do do low hanging fruits first So and this is not a low hanging fruit from our perspective. We have a cloud first strategy. So our aim is to Preferably move first cloud ready applications to the cloud because it's easier That's why we refer to don't open Pandora's box and with providing a lot of Connections to the back end because then you have a problem to provide these back-end connections on other locations as well. It's a very It's a huge set of dependencies In the future it might be possible to move under workloads as well over there So we have a lot of discussions in this onboarding a workload onboarding team For example to move more demanding or challenging applications to the cloud as well if it will be VDI for example at the end I don't know could be the case depends on the requirements for the underlying underlying infrastructure, could you explain something about the balance between the application centers or groups that would Welcome what you're doing. I would really want it and pull and the difference between Maybe something that's maybe ordained at a high level of management where it's actually something that is required to be pushed Okay, I got the question so There is no real resistance to this project because we don't force anybody really to use it we said we want to have a Want to have a Very good offer and if it's not good enough or not good for a specific project Both can walk their way so to speak so there is no real resistance to the project We do have as folks one as a whole a strategy to develop new applications cloud ready Who does like this most I would guess developers first They don't have to to fiddle around with with processes to get a server to just to test something After that I would guess rep prone Applications are obviously Most Happy to use this because I can It's not about OpenStack and IIS but because of the whole techniques. They have Attent there which I didn't before So Yeah, I think there is another demanding group there is the expectation with some workloads that they would save a lot of money if They would move their workload to the cloud But that's not necessarily true. It depends so The goal why this workloads want to move to the cloud might be different from the other ones and You have to explain very in detail and clearly why it might be not a good idea to move this specific workload to the cloud because he consumes non-HA non-cloud ready back-end servers for example and don't have this connection and you don't want to provide this connection because it Fears with your cloud model. It's just Thanks for presentation I Okay, so I see that you have a lot of requirements as a biggest enterprise in the world And I know how internals of OpenStack, so I'm interested How many OpenStack project you invaded did some patching developing etc I saw Sean's presentation about Keystone policies and As I understand Keystone was a patch it to meet your requirements. So Did you patch Nova Neatron other services? How many developers are working on? Unfortunately, I haven't seen your presentation. So I'm lacking information here Yeah So it's one vanilla open-stack So this is so I would like to add a customer's perspective to this I'm not aware of any page to to to as a man we want is open-stack distribution I'm aware of Quite substantial configuration because of network restraint restraints Because of the way we provide for instance mirrors and so on so it's No, not specific but By configuration what I'm aware of I don't know whether this counts as Policy.conf which is always a pain, you know this So I do think we are overdoing our time as far as I'm Getting the the movement So thanks for your patience. Thanks a lot. Thank you for your time


Hello okay um so let's get started in today's presentation I'll be talking about building a production level conversational interface for national language processing using an open source platform called MindMild. The presentation itself will be about generally how to make a production level conversational assistance so it's not particularly to one technology but some of the best practices that I'll be presenting today can be used for other open source projects as well. Just a brief background on myself I am a senior machine learning engineer at the WebEx intelligence team at Cisco and before that I was working at a startup called MindMild where we built conversational assistance for Fortune Founder companies like Starbucks and Uniqlo. Currently I built voice assistance for Cisco's conferencing units so I think we all probably know by now that you know conversational interfaces are already implemented in both domestic use cases as well as in company use cases about 20 percent of all search results are voice searches and around 50 percent of all searches are projected to be voice searches by 2020 according to commscore and we also know that at least at home you have Alexa Cortana Google as well as Siri being used pretty much everywhere. Obviously this trend is moving to workplaces as well and at Cisco at least we built a product called WebEx Assistant which you can sort of say okay WebEx joined the meeting and the conversational interface itself would then you know join a particular meeting for your particular room. This entire experience called WebEx Assistance is powered by this open source platform called MindMild that I'll be discussing today. So one of the challenges about building a production quality conversational assistant is there are many gotchas that come about when building such a product. One is the accuracies kind of are hit and miss so when you say something like call an Uber sometimes your assistant would infer that an Uber is a person name and it won't be able to get the correct person based on that query. Also there are issues with common slang so things like abbreviations and lingos can get misrepresented. So for instance when you say show me an apartment in Fidai sometimes the assistant won't know that Fidai means the financial district and it would get the query incorrectly classified. Using preset rules also break when the user asks something that's a bit more challenging. So for instance when you say something like confirm order for one cob salad and the assistant says can I get dressing on this sorry. So when the assistant says confirm order for one cob salad and you say I want to also add a dressing on the side it won't really understand because it doesn't know what a follow up query is to the main query. And finally shallow knowledge is definitely fails. So for instance when you say show Oscar winning movies since an assistant could be trained only on just show a particular movie by title it won't be able to get a more sophisticated result for instance when you want to find all new movies that are Oscar winning. So again these are some issues that happen when building a conversational assistant and we will be talking about how to solve them using a pipeline. So the machine learning tools today are sort of divided into two categories. One is you have cloud NLP services. These are technologies like dialogue flow Amazon Lex IBM Watson and so on. And again this is just a general classification. The other side you have more specific ML toolkits like SK learn tensor flow carriers and so on. And in the at least in our case when we reviewed some of these services in the cloud NLP side the issue is that there are quite a lot of prebuilt models or pre prebuilt domains that are very useful while starting up a particular application. But when you have any kind of custom domains that are very specific to your enterprise or consumer use case it sort of breaks down at that point just because some of these prebuilt entities are not really supported in your custom use case. The tools for building some of these custom domains can only handle very narrow models and trivial applications. So for instance in dialogue flow it's very easy to onboard and click a button and train your entire machine learning model. But if you want to change certain hyper parameters in your particular model you're not really given the option of doing that. So that sort of configurability for a custom application which is required in order to get very good accuracies is not really supported. And the ML capabilities here only scratch the surface of what you really need to do to build a production application. So for example for a certain entity for example a person name when you're trying to detect a person name these sorts of entities are very hard to detect because they can be very noisy. Your person name could basically be any kind of sequence of characters. So in order to detect that in a way that's very accurate you probably need a different type of model than what you would need for classifying a sequence of words. So text classification. So changing some of these models mixing and mashing them is really hard to do with some of these cloud native platforms. On the machine learning toolkit side you have very powerful technologies like TensorFlow, scikit-learn and so on. However when you want to string together all the applications for example machine learning, information retrieval, dialogue systems all together it becomes just a very challenging experience to bringing them all together by yourself. And so because of this as software developer coming in to develop a sophisticated conversational assistant it becomes really hard to do just by using some of these technologies from scratch. So that's why we built the mind-melt conversational AI platform. It involves four different components which we'll be discussing. One is the natural language processor, the question answer, the dialogue manager and the application manager. And these are all sort of like talking to each other. It's a Python based framework and it's used to build conversational assistants. This is what powers WebEx assistant within Cisco. It's an open source Apache 2 license and it leverages open source libraries like TensorFlow, scikit-learn, numpy and scipy in the back end in order to essentially drive the entire experience. It provides functionality to build state-of-the-art models for natural language understanding and question answering. So this is the GitHub URL. It's just Cisco slash mind-melt. It's open source.  And currently it's being used to power both applications within Cisco as well as outside Cisco. So let's talk about the first component that I described previously which is the natural language processor. This actually contains a sequence of subcomponents that are used to infer the meaning of a user's query and it produces a representation that captures all the salient information within a query. And it applies a combination of techniques that involve both pattern-matching, tech classification, information retrieval and parsing in order to get the right result out. What we generally found is that just by using an end-to-end, for example, a deep learning platform to predict a particular result, it really doesn't, it's not really effective, especially for a production-level application. You need a combination of both pattern-matching, involving even regex for that matter as well as machine learning in order to get the right results out because you will always have some edge cases that you need to take care of. So within the first subcomponent within your NLP module, you have this component called the domain classifier.  So for example, if you are saying something like what's the weather in San Francisco, that is a body of knowledge regarding weather as compared to spots. So it's a pretty simple text classification problem that uses machine learning in order to predict which particular domain that query belongs to. The next subcomponent is the intent classifier. And this is regarding, it's classifying what the particular verb of the query is. So what's the action that you're trying to take? Obviously, not all queries contain verbs, but the intent classifier is generally used for picking an action for a particular query. So for example, when you're saying something like, can I find the Mediterranean restaurant in San Diego? The verb here is find restaurant or something like that. And so for that, you would actually use again a text classification problem or a classifier that uses an intent classifier to do this. And just to make it clear, both the domain and intent classifiers are text classifications. So you're taking a sequence of words and you're having one label that is predicted based on that query. The next classifier is a bit different. It's called the entity recognizer. And what we're trying to do here is we're trying to isolate or classify a phrase or a particular word in a query. So this is slightly different from the previous models. And over here, what you're trying to do is isolate certain phrases within a query. So a phrase could be something like a restaurant name like Starbucks or McDonald's, which are single word names, but it can also be a phrase like, I don't know, Persian restaurant or something like that. Or a movie title. So these are sequences and the model here is going to be a bit different. And it's also going to be a bit more powerful than the previous models, just because for every single word within your query, you're making a classification or a label of what that entity is. And so generally speaking, we use a more complex machine learning classifier to do this. It's usually more heavy duty, something that involves an LSTM in order to classify the entity. There's also a role classifier, which is a sub problem of the entity classifier. So for instance, when you classify a particular time entity, you want to set that to a start time or an end time. So when you're seeing something like set the alarm at 5 a.m., 5 a.m. could be a start time, but if you see something like set, show me movies between 5 a.m., sorry, show me something between 5 a.m. and 7 p.m. 5 a.m. is a start time and maybe 7 p.m. is the end time. So these are subclassifications of an entity. Next up, we have the entity resolver. And what you're trying to do here is you are taking a particular abbreviation or a particular entity and you're trying to resolve that to a canonical name within your business application. So for instance, SF, which is an abbreviation of San Francisco, would be carried out by this component. And for example, lemon bread would be resolved to iced lemon pound cake within your particular application. We use elastic search in order to do this, which is another open source technology. And it primarily uses a technique called term frequency, inverse term frequency in order to retrieve the particular information regarding the canonical name of your query. So this is again sort of already baked into mind-meld that we built. So this comes free for you in order to do this information resolution. And the next step is language parsing. And this is important because you also want to group entities that are logically connected together. So for a query like, I want a pepperoni pizza with extra cheese, a calzone, and two Diet Cokes from Domino's on Gary. Again, you can sort of isolate all these different entities. For example, pepperoni pizza or extra cheese or calzone, two Diet Coke, Domino's, and Gary. These are all entities of interest within your application. However, they are grouped logically in a way that makes sense in only a certain kind of grouping. So for example, the pepperoni pizza and extra cheese are grouped together. Calzone is its own group. Diet Coke and two are grouped together because you are talking about two Diet Cokes and not two Domino's Gary or something like that. So these sorts of entity groupings are important. And this kind of problem for language parsing is actually a very well-studied problem. And there's a lot of research that has gone into how do you group these entities together? We have a certain heuristic that we built within mind-meld and not do this grouping automatically based on some rules that are specified within your configuration. So I've finally talked all about the national language processor itself. It has all these subcomponents that essentially parse out all the information that you need from a particular query. The next step is the question answer. And this is your heavy-duty knowledge base that is used to get the right candidates within your particular application. So when I talked about entity resolution, that's essentially talking to the question answer to get the results out of what the right entity resolution is. And again, this is using Elasticsearch for us, but you can sort of use your own knowledge base if you have a certain preference of what kind of technology you want to use in order to do this. So again, this is using information retrieval techniques and you're trying to match a particular text to a canonical name within your application. The dialogue manager is a very important part about a conversational application. Over here, what you're trying to do is you're matching a particular domain and intent to a particular dialogue state so that you can then give a response back to the user or take a particular action based on what the intent is. And all this happens within the dialogue manager and it basically moves forward to the next dialogue state. So you can think of it as a finite state machine depending on where you are in a particular interaction with the user. So for example, when you say something like, I want five pizzas and then the bot responds, okay, great, what else do you want? And the person says two coffees. That's again, doing a follow up query on the same dialogue state. So you need to have this state machine in order to control the total actions that are taken by the user in order to service a particular request. And that all happens in the dialogue manager. Again, this is provided within MindMeld itself, so you can sort of design your own dialogue state system and essentially give the appropriate response back to the user either which is a follow up or a confirmation on a particular action that you want to take. This all happens within the dialogue manager. And finally, you have the application manager and this is sort of the orchestrator that talks to all the systems. So for instance, when you're making a Facebook chat bot and you're making an Alexa bot, you want to interact both of these clients with the same application manager because this platform itself is generic. It doesn't have to be tied to say Google Assistant or it doesn't have to be only tied to Alexa. It can be a general platform that is being served in the cloud and the application manager allows you to do that by syncing with clients so that you can actually talk to different clients at the same time and give back responses to the appropriate client when necessary. So again, this is very generic. You can sort of like deploy this on just any cloud infrastructure or even on-prem and this can talk to any client that is interacting with it. So briefly talking about just an example interaction of what happens for such a query. So for instance, when a user says schedule a meeting with Janice from accounting from 11 a.m. to noon in Aquarello, what the bot responds at least for this query if it's successful is your meeting with Janice has been scheduled for 11 a.m. today. So we will be talking about what the lifecycle of this particular query is within a conversational application. So firstly, you know, I talked about the domain classifier. So over here, what's happening is that you're classifying this particular query to be in a particular domain. In this case, it's a meetings domain and it's not related to expenses or procurement or travel. So your classifier gives a very high confidence score for the meetings domain, which is correct. The next step is classifying the intent. And over here, the intent here is schedule meeting and it's not cancel meeting or check calendar. And hence, the confidence score for that classifier for the schedule meeting is the highest. The entity recognizer here is doing a lot of heavy lifting. It's detecting that within this query, Janice is a person accounting as a department, 11 a.m. is a time, noon is a time, and Aquarello is a room. So there is a distinction between entities over here. One is a system entity. And this is a sort of lingo that is being used even by TensorFlow, sorry, by Dialogflow, as well as MindMild, where you have these natively supported entities that you don't have to really train your application for. And these are like time entities. 11 a.m. and noon should already be detected on a conversational assistant by itself, just because these are generic entities that should be supported, versus things like Aquarello, which is a room name, is not really a generic entity. So you would need to add your own training data in order to be able to detect some of these other entities within your application. Again, person name, it could be generic, it could be more specific towards your application. In our case, we actually use other techniques to detect person names. For instance, looking at the entire organizational hierarchy within the particular enterprise in order to be able to better detect a person name. Next up, we have is the role classifier. Over here, we have only a role classifier for the time. So in this case, 11 a.m. is the start time and noon is the end time. And once that's done, we call the knowledge base, and we get the resolved entities for every single isolated entity that was detected. So in this case, Janus is resolved to Janus Smith, where the particular employee ID accounting is resolved to corporate accounting, 11 a.m. you get the right UTC time as well as noon you get the right UTC time as well. And Aquarello is resolved to the particular meeting room ID within your organization. And this again is using elastic search in order to do it. And finally, we have the language parser. Over here, you are grouping entities that are logically connected together. So Janus Smith and corporate accounting are linked together because you are referencing Janus Smith, who's part of corporate accounting and not say HR. And the times and meeting rooms are again logically connected because a meeting room has certain bookable times, and so they are logically connected as well. And finally, you have the dialogue manager that goes to a particular dialogue state, and this state is book meeting. And so within your dialogue state, you can sort of have the logic of gathering all these entities together and finally making a call to book that particular meeting room. So right over here, you have an invitee. You do a question-answerer.get with an index of the employees, employee ID, and department. So you have the invitee, you have the location. And finally, you can make an external call to your calendar's API to book that particular meeting room with that invitee. Obviously, this call is to an external service. This is not included within the generic MindMeld platform. But you can imagine sort of making this call to Google Calendar or Outlook in order to get the final result of that query. And so the next step is obviously the natural language response. And so within that particular meeting state, that particular dialogue state, excuse me, for book meeting, you would have to fill some slots in order to give back a response to the user. So these slots are these sort of underlines that you see over here. Your meeting with dash has been scheduled for dash. Obviously, if a slot is not filled, you would ask or re-prompt the user to essentially fill that slot. So this task is called slot filling, and it's sort of done in all conversational applications. And so you want to fill these slots and then give back the response to the user. And so in this case, you're saying that your meeting with Janice has been scheduled for 11 a.m. today. So with those slides, I have briefly gone through how the life cycle of particular query happens in any kind of sophisticated conversational AI platform. The MindMeld platform itself is, again, it's open to all developers. It's a Python-based framework, and it utilizes both machine learning toolkit, information retrieval, as well as dialogue systems in order to build this entire application. We do have extensive documentation that you can use to get tutorials, as well as practical advice on how to build such an application. The community is growing. We actually just open sourced about one and a half months back. So it's kind of a new project, sort of like getting used to the larger community. And it also has pre-built applications called Blueprints, which you can use to sort of play around with a home assistant or a food ordering bot, for instance. And yeah, so please feel free to use MindMeld for your next voice or chat bot. You can find all the details at mindmeld.com. I will extend it for questions in terms of any kind of questions on MindMeld, open source, voice assistance, and so on. Yes. Yeah, so in this case, all you're trying to find is, is there a person entity within that particular dialogue? So in this case, you're talking about, you know, filling it with Janice and a time, right? So in this case, it needs to satisfy two entities. In this case, there is a person entity, and there's a time entity. And once you have both of them, then you can fulfill the request. So it's not doing a combinatorial, you know, exploration of all possible names, it's just trying to find if there are the required entity types in order to fulfill that query. So the number of entity types is generally not that large. You might not be talking about like tens or hundreds of entity types. So, you know, it's a much more easier problem to solve because it's just trying to figure out what are the entity types do I need in order to fulfill that request. Yes. Yeah, yeah. So that's actually a very good question. And that's why we think that having sort of like an open source platform to do this is very helpful than what's sort of like there in the market right now. Generally, what we find is for text classification, which is domain classification, it's quite an easy problem. Like you're talking about an entire, you know, sequence of words and you're trying to make just one label classification for that. So generally, we're talking about, you know, between 500 to 1000 queries in order to make such a classification. So again, this is not using that much data at all. And you can build quite a good production system in order to do that. So for domain and internet classification, we generally don't have that many queries. We use simple models like logistic regression in order to do that. For entity resolution, sorry, for entity classification that requires a lot more data because, you know, it's a lot more powerful for every single word you're making a classification on that. So for that, generally, we're talking about depending on whether it's an open intent and open entity or a closed entity and open entity is something like a person name where it could be an infinite number of variations of what a person name could be. So for that, we're talking about between 1000 to a 10,000 queries in order to make a particular classification on an open entity. You're talking about a closed entity. A closed entity could be something like, for example, time, right, where you don't have that many variations of numbers. And so for those types, we generally have much less training data in order to get a good classification accuracy in order for that to happen. And we're talking about classification accuracies of over 95% on entity recognition in order to get it pretty good for your particular application. Yes. Yeah, so that's actually a very good question. So in the mind map platform itself, we support two different types of question answering. So one is, you know, this type, which is a lot more specific to your application where you're trying to resolve, let's see, you know, for example, Janice Smith or corporate accounting is very specific towards your application. So if we have a tool that you would ingest your entire sort of like iterations of all your HR data, for example, within this knowledge base, again, this knowledge base is based on elastic search. So that is more of the targeted approach of like finding for every single entity type, what are the canonical names within your particular organization. Then there's the more open ended question answering, which is more like, I just want to ingest all my documents within elastic search, and I want to be able to query that so similar to what a search engine would be. And so for that, that's generally more of a FAQ type question answering where you're saying something like, you know, what is the what is the HR policy for my company, you want to be able to retrieve just a large body of text. So mine well supports both types. One is more supervised and the other one is more unsupervised. And again, this is an important distinction because in information retrieval, depending on either this more targeted approach or a more unsupervised approach, some of your parameters for searching would change depending on that. So at least in mine well, we provide you with a particular parameter for an argument in your QA call, where you can just specify if it's structured, or if it's sort of unsupervised or supervised and based on that, it would use a different sort of parameters in order to give to retrieve back results. Cool. Yeah, I think that's it. Thanks for your time.