Supercloud 3 Analyst Panel | Supercloud 3

foreign welcome back to super cloud 3 we are live in Palo Alto for our third edition of super clouds we break down the next gen Cloud multiple environments multiple clouds Edge data this is Security Plus AI is the focus today's been the theme throughout it I'm Jeffrey Dave vellante SARP Jeep Joe owls here Cube Collective part of our our team member of our influencer group that we hang out with at all the events and certainly a distinguished Cube alumni great to see you coming on to do the analysts section of what we've been talking about supercloud so listen we're going to analyze Dave good to see you sir thanks Mom thank you okay let's let's analyze so super cloud 3 Security Plus AI Dave this is the continuation more and more momentum we just had Doug Merritt come out of retirement he's now the CEO of Aviation he's going to take them past 100 million take it public he did that with Splunk a data company Jay shawbury with z-scaler absolutely killing it one of the high performing SAS companies on the planet they're up on the top of the ranks of the of the of this new generation of companies Pro game game great speed of acceleration just the acceleration of what's going on in super cloud it's like the big clouds they're not going away they don't have to die to bring in multi multi-interoperability they're continuing to do great Amazon web services Azure news today Microsoft teaming up on the AI side with open AI moves are being made in the cloud The Edge is developing what's the analysis well I think that that prior to I mean the super cloud Trend was happening right we saw that but prior to chat GPT chat GPT I've created this Awakening and I think it's accelerated the intensity Within These specific sectors so you talked about we talked to Doug Merritt about how the granularity is actually going to get greater and the focus is going to get greater so those companies my view love to hear what subject thinks that really lean in aggressively are going to extend their position you're seeing that with Microsoft you heard that with z-scaler we heard that with cloudflare we heard that with VMware right they're in a strong position and they're investing and their goal is to get stronger now having said that you've got these interesting disruptions the other piece of that is I don't think they know yet what to do with generative AI right and it's like Jeff Jonah said it's it's good it's amazing but it gives you different answers every time so how do they apply that in Security in other areas they're still trying to figure that out so there's a lot of opportunity I want to get I want to get into that in a second storm geek let's get it to you first on the on the top level cloud players super cloud 3 Security Plus AI I think the time compression as Doug said that that's a huge thing right so everybody's trying to rush in and put the solutions out there right now the the usage of generative models or llms right is in the on the design time you know when you're cooking up stuff right so when you're planning for it right when you're coding um that that sort of like we that's so obvious for us right but but the problem is that how do you apply that at the runtime because at runtime you need consistency and accuracy yeah at design time you you have still have human in the picture but at runtime you want to take the human out of the picture right so that's challenge I think to to take out that problem out of uh llms there will be domain specific llms which will be more precise and they will give you I would say not same answer maybe perhaps almost same answer every time so the domain specific llms will emerge that's what my uh you know I think the acceleration is a great point I want to get you guys reaction on this because what came out of Jay chaudry's and um interview and we heard from kit and others and we love sports analogy so I'll just say it it's a pro game and you know you talk sports the speed of the game is so different than College you know in football for instance security is a Speed game and it's a pro game and you know that leaves this whole democratization on the table interesting because how do you democratize a slower game okay and we saw that in the data world so you know in security you cannot compete if you don't have that game because the defense levels or requirements are so high on security um it's going to be very challenging so the question is does AI accelerate and open that bottom end of the feeder to bring up talent because what we're seeing from all the pros here on the cube talking about super cloud 3 is Security's a pro game the speed is at a level that you got to be a certain athlete to play at this is a big issue because that that means startups might be looking different um do you have to do more work on the front end even get in the game what's your what's your take first of all I think you got to be cross-cloud you got to be super cloud insecurity that to me is table Stakes the second thing is you absolutely have to apply AI whether it's generative AI or other machine intelligence to that Corpus of data that you have and those that have the best data are going to win and I think that during the pandemic we had this flood of venture capital come into the security space at not all those guys are going to survive I mean you do see companies you know like whiz pops up in the data I mean we saw this at RSA yeah all you do is look at the line outside their party right practitioners are enthused about them but then you have you have companies that are popping up specializing in Edge security is that the right model do we need another stovepipe or is it so unique and so different that actually you do need a best of breed stove so you think you have to be cross-cloud you have to be applying Ai and you do have to be best to breed at something and as Jason was saying if you try to stretch that too thin you know it's like when you're rolling the pizza dough and you get a hole in it you know that creates no you don't have the game you can't compete that's what you're basically saying of the game you can't compete it pro level is definitely different than College yeah it's not this is not JV I I think in um it seems like in software World in x86 world right now it seems like it's a championship round the AI is the championship round before we start with you know the next round with super Computing and you know different Paradigm and shift but in this one that round because because like what we're trying to do is like we used to write logic um that was that's what coders did right we put like brain into machines right but now machines will learn from data so that's what I think it's the sort of towards the end game of this sort of era if you are putting logic into Data yeah yeah flipping and data and data Fusion too yeah and data fusions come up too all right so let's get into that let's get in the generator because there's a hype cycle and you've got spending data that matches that says that's a unique thing you've never seen before where the hype cycle is strong and the spending momentum is aligned with that that's not normal okay that's we'll get to that in a second I also want to bring up the machine learning I mean I don't know if you remember Dave but back go back to 2011 2012 when we were doing the cube at that time machine ml Engineers were out in the market and it was well known that Google was paying up to two to three million dollars per person in Accu hires if they had machine learning Engineers on staff so you know machine learning CPUs okay but machine learning has been around for a decade hardcore so a lot of this generative AI is is the discussion it's generating new things but it's based upon supervised machine learning not unsupervised so you know a lot of the people come in like all the top companies like Z scalar Natives and others like we've been doing ml for a while so that is kind of AI so it's a different kind of AI scene the gender of AI is super hyped but it's new but it's not it's this it's machine learning too it's data I think it comes back to the design time what's the runtime right so the we have been doing machine learning kind of work for so long I used to work at Visa in 96 and whenever you swipe your card we ran an algo very quickly within milliseconds IBM tpf technology behind the scenes super fast right so it was like we know your spanning pattern if if your amount is anomaly will stop you like you have to call somebody to get the approval right it's nothing new but with with the llms which is part of generator when LMS are a little different right so the whole idea is to get the like the corpse of data and get the intelligence out of that but the problem is that it's not accurate all the time it Cooks things up it makes things up right there's uh hallucination and gives you different answers multiple times yeah what you're trying to do is now it's like trying to start okay oh you know everything now but like don't say this but say this like we're trying to uh tame it if you will with like a in SQL world like we have a not clouds like give me all that but all these things but not that it's also a lot um a lot less controlled it's just it was distributed that transaction processing facility example that you gave was it was distributed you might have some terminal NCR terminal at the edge but today you've got cell phones you've got machines you've got it so it's it's kind of this wild wild west you know you don't have like everything rack f everything controlled inside the Mainframe you've got all kinds of different standards different Open Standards and so it's a lot harder to actually control what's happening throughout the network yeah and another true but another thing is very important is that that um he revised his blog about like new new modes right so I have been talking about these three types of systems the system of a record system of differentiation and systems of innovation and he used that sort of system demarcation um methodology in his analysis as well I think systems of record are very close to what we need from uh Regulators point of point of view like we have Accounting in place and we have Regulators they'll look at your books and you can't just cook up stuff right so the systems of record I think they they will not be going anywhere near llms anytime soon I think systems of innovation will very quickly but and systems of uh engagement or system of differentiation they will flirt with these models pretty soon and they're already doing that in many ways so I think at that brings in another aspect another sort of Pros another aspect of looking at the problem right that is consumer versus the business right b2c people are like oh they're like oh my God this is cool stuff and we all like personally we are like very um nicely like pleasantly shocked now this is productivity all that stuff but when you go to business side then you're like hold on right so it's always been harder if you look at the search business remember back in the day when Google was getting in the business and I'll search into the internet it was easy to do search on Public Information than inside a company get structured data different databases so I think the B2B Market's interesting because you have one confidential information you have different infrastructure and this brings up the conversation that we've been having around okay how do you define your value and the data and the data values key so Dave you know when we talk about the super cloud love to get both of your perspective when you think about the digital transformation okay I'm an Enterprise I'm a B2B company I look different from an AI perspective than say a consumer company that's going to be a search engine like a Bing or whatever open AI it's public right the private is going to use llms differently because the the operation you have to operationalize it so the question I guess for you guys is is how should companies think about operationalizing the super cloud security and AI story because and we've heard some people low-hanging fruits configuration some automation but observability comes up how much data we have that we haven't Harvest before um I'm not always this is the key it's got to start with the data is it because you know the the language model itself is going to be commodity right I can get it from Amazon I can get it from Google I can get it from Microsoft I get it from open Ai and get it from open source whatever it's the data and that's where you're going to get a moat and so you really got to get you know the old Rob Thomas you can't have ai without IA you got to really get your data architected architect your data models you know together what's what is that should be the question that you're asking what is our most valuable data and how can we take advantage of it you got to start there Rob Thomas and referring to Rob Thomas from IBM who almost what seven years ago seven eight years ago was saying IA informational architecture before AI yeah AI without IA and you can't have ai without a data architecture you agree with that I agree with it actually Georgia earlier today he mentioned that they are ingesting multiple llms into their security operations that's what they do right so they specialize in security so I think just like Cloud we are on multi-cloud one right right now in AI we'll be in the multi-llm world so as you said like llms will be commodity and he said that too and I believe in that well we talk about llms which stands for large language models but there's also Foundation models because language is text you've got multimodal which is text audio and video so computer vision as Foundation models that's not an llm that's Vision so so you know just to get the semantics right llm is for text yes and language but computer vision when you're looking at say a picture and someone's climbing a fence I interviewed a company who detects people climbing fences that's someone breaking in to a a yard or something you know what's interesting if you if you listen to Ilia from open AI the interview he did that fireside chat with Jensen he will tell you the two things he said the scale was underestimated the importance of scale and having all this data the second was vision that Vision actually dramatically increased the accuracy of llms so they kind of go hand in hand and I think one of the things just Jeff Jonas I think nailed and people talk about it but I think we don't fully understand it yet is we are going to replace this with this yes huge difference John Chambers said that on the cube in our podcast he did yeah voice will be authenticating things be part of access well I don't think people have really grocked that yet you're talking about the security Ops right security operations right right now we're looking at the logs people are sitting at these you know looking at the monitors and what's going through and all that stuff like things are changing gradually but in future we'll be talking to these machines and let's say we see DDOS coming from China or some national adversary or even some friendly country like within the country right so it's like block you know any traffic coming from Arizona or something which isn't you know somebody's ddosing from there so you can just talk to machines and and then it will take action behind the scenes because it knows what you're trying to do and it just Maps it so actually is that going to be generative this is the question I have is that going to be generative AI is it you say tell me who's what's the signature of this DDOS is it where's it coming from is it North Korea is it Iran is it China is it Russia whatever okay and then and then what to do about it block okay are you going to use generative AI for that because I'm sorry generative so it's sort of guessing what they're generating the solution it's generating the next word essentially hey I don't actually you will I I thought about that one yeah some notes so when I was doing something like thinking like I used to work at EMC and we had a very sophisticated sniffer actually we call it cmdb but it was not but anyway it's a long story right so like we were looking at every nth packet on the network right so we because we couldn't look at every package so you're sampling yeah we were sampling so in this case that's also like I between my two jobs I did a stint at Port of Oakland ran a trucking company for some while and figure out all the containers coming from China we can't inspect every container in real world right so we were they were picking the the Port Authority pick every like 50th container and look through that or sort of almost like a random thing right so and it seemed like security at you know a Tel Aviv airport like they do it differently so everybody will do these things differently but they they will pick every nth packet or or buy how the packet looks or by the intensity of the workload like how critical it is yeah yeah once you get that packet now you want to analyze look what it is like what's the signature of the the payload right then you can give it to the llms and and generative AI kind of you know mechanism find out what is this is a small air who's attacking us so there will be like the comp these packets are coming in like boom boom boom right and you pick some random packets and give it to these super sticker llm based security models and say okay tell me what it is so are you going to get that's the same rough probability each time right you're saying you are yes if you have the right controls because then the other thing the Ilias said and people debate this in fact Jeff Jonas was like nah it's generative Ilya said look chatgpt wasn't designed to be that consistent you know accurate buddy but it will it will over time evolve there and so and others are saying yeah maybe not maybe there's different machine intelligence it depends on the data their reasoning is based upon only supervised not unsupervised which changes the dimension of how much the reasoning is accurate but I think also the the idea of prompting is going to change how we fuse data so to me what I'm hearing people talk about and my vision would be that the fusion of data interplaying between data sets is going to be a new thing that's going to be outside the scope of traditional like how to organize data in a warehouse or Cloud because if data is free to move around and interact that's where the generative AI could really kick in here's what I think I think because it's probabilistic the way in which gen AI models at least chat CPT is going to approach it is when there's a lack of confidence it's going to communicate that to the prompter and or ask the prompter questions can you tell me more and it really doesn't do that today it doesn't have those types of that's what when people talk about guardrails that's the type of guardrail that I would imagine that it is sort of self monitoring you know and then it's it's forcing you to give it more information so that you know it doesn't give you incorrect no no that that the key is incorrect like is important in operations right so I I believe like let's take an analogy like when we go to like university colleges right we some people specialize in certain areas there's some stringent guidelines in some areas some areas are very very wide open you know Humanities and art and in in science or domains right so just think of these llms as individuals for a minute right some people know a lot about everything right their Humanities major right communication right you guys remember you are actually special right so you know a lot a lot of things about a lot of things right but there's a people like they just day in day out back their head against like how the atoms work and that how this you know genetics work and all that they specialize in that so they know their information coming from them is more accurate as compared to somebody who knows many things but many things right so I think morals will be same way specialized model will have more accuracy uh it's it's all relevant relative I think in that at that point because it's still llm but I I believe that that we will have like security models for you know different type of Industries as well and Industry models itself like for regulators and kind of like Wikipedia actually we make a Wikipedia with Technical and Mathematics and stuff like that is actually very accurate because you have experts that really know that you have to change those pages but make sure they're accurate but yeah but the problem is it's a situations right it's yeah right sorry final question for you Security Plus AI is the theme for super cloud three a couple questions to end this out what where do you think the momentum at supercloud is right now and super cloud 3 AI and security what's your analysis what's your final take super cloud momentum and then the second question is the Security Plus AI what's the critical message there I think super cloud momentum is that that we have to make the the multi-cloud work and to make that work we need another abstraction layer and that's why we see the rise of uh Cloud Player companies like cloudflare Snowflake and all these companies are built on top of Cloud and now the cloud providers are having second thoughts what should we play in that we go at one layer above Amazon is having this identity crisis there I believe like they they are saying oh we are Builders Cloud but on the other side Microsoft is saying oh we will give you these you know apps which are like AI apps actually um a lot of experts say that that that chat GPT 4 is an llm app it's not llm itself it's an app it's a it's an app right yeah so so they have app there these these people are saying Google let you build llms or we'll have we have our one of our own so there's a lot of uncertainty there so um I usually say that technology is like a medicine right and every pill has a side effect and so so will Ai and there's over-the-counter AI which is the these llms which are public llms and they are prescriptions prescriptive AI like just like medicines which will be just for you made for you because you have certain kind of symptoms I eat and you're trying to fix as a company so we will have sort of different demarcation of like a staggered AI adoption of course security is a huge problem because bad guys have access to the same tools what good guys have and bad guys can break more rules than good nights can in many ways the even the the good guys look bad these days you know Sam Offman going around the world you know saying like Okay oh it's very dangerous thing it's very dangerous thing but he's cooking it up on the fly a very tricky situation I think that's a hedge too Sergeant thanks for coming on Dave great analysis okay wrapping up that sex we're gonna have live coverage coming in remote live from Dell technology CTO I'm John Furrier Dave vellante and serpicho all here breaking down with the cube Collective super cloud 3 we'll be right back in the world thank you foreign

2023-08-26 01:16

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