Image Title

Search Results for Mike Dauber:

Sunil Dhaliwal, Amplify Partners | CUBEConversations, August 2019


 

>> from our studios in the heart of Silicon Valley, Palo Alto, California. It is a cute conversation. >> Levan, Welcome to this Cube conversation. I'm John for a host of the Cube here in our Cube Studios in Palo Alto, California. Harder Silicon Valley world startups are happening on the venture capitalists air. Here we have with us. O'Neill, Deli Wall, Who is the general partner Amplify Partners and Founder co found with Mike Dauber. You guys have a very successful firm. I've known you since the beginning. When you started this firm. You guys were very successful on your third fund. Congratulations. Thank you. Great to see you. Thanks for coming in. It's always fun >> to be back. Yours? First time we're doing it in person. >> Local as it posted out of the conference. Yeah. Got our studio here. We're kicking off two days a week. Soon to be five days or weeks. Folks watching studio will be open for a lot more. Start up coverage. So great to have you in. And congrats on 10 years for you guys. 10 years of the Cube. 10th year of'em world would do in a big special. So nice we're excited. Well, for another great 10 years have been a lot of fun. A lot of interesting things happen those 10 years and again, you've been on the track to foot during that time. Yeah, on, by the way, Congratulations, fastly when public, thank you very much. And you also investing early investor in Data Dog, which you probably can't comment on, but they look like they're gonna go public. It's a great business >> and it's moving the right direction. And I think they got a lot of happy users. So there's more good stuff in the future for them. >> So you guys came out early, Made big bets. They're paying off two of them. Certainly one. Did another one come around the bikemore. Take it. Give us update on Amplify Partners Current fund. Third Fund gives the numbers. How much? What do you guys investing in with some of the thesis? What's the vision? >> Yeah, the vision is really simple. So amplify has been around from the beginning to work with technical founders. And really, if you wanted to stop there, you could you know, we're the people that engineers, academics, practitioners, operators that they go to get their first capital when they are thinking about starting a company or have a niche that they just feel the need to scratch. We tend to be first call for those folks a lot of times before they even know that they're going to start something. And so we've been doing that. Investing at seeding Siri's A with those people in these really technical enterprise markets now for seven years. Third fund most recent funds a $200,000,000 fund and that has us doing everything from crazy pie in the sky. First check into, ah, somebody with wild vision to now bigger Siri's a lead Rounds, which we're doing a lot more of two. >> So on the business model, just to get a clear personal congratulations Really good venturing by the way. That's what venture capital should be First money in, You know, people not doing the big round. So that's a congratulated, successful thank you now that you have 200,000,000 Plus, are you file doing follow on rounds? Are you getting in on the pro rat eyes? Are you guys following on? Because he's Sonny's big head, sir. Pretty, pretty big. >> Yeah, we've been doing that from the beginning and I think we've always wanted to be people who will start early and go along. We've invested in every round that fastly did we invested in every round that data dog did. So yeah, we're long term supporters and we can go along with the company's. But our differentiation isn't showing up and being the guys who were gonna lead your Siri's g round at a $3,000,000,000 valuation, which might as well be your AIPO were really there to help people figure out how to recruit a Kick ass team and figure out how to find product market fit and get that engine working >> and also help be a friend of the on the same side of the tables and rather than being the potentially out of the side. So the question is, I know you guys do step away and don't go on board. Sometimes you do. Sometimes you don't. Was there a formula there? Do you go on the boards as further in the round? You happy the relief? It's a >> mix of, uh, you know, we talked about a couple of these cos fastly. I've been on the board since Day zero and data dog. I was never on the board. And you know what we do tend to be those pretty active. So people come work with us when they go. I've got this vision. I know where I want to go. But when I think about the hard things I've got to do over the 1st 2 to 3 years of a company's life, you know who I want by my side and not the person who wants to be my boss or tell me what to do or tell me why they need to own 1/3 of my company or control four seeds on my board. But who kind of what's it wants to sit shoulder to shoulder with me and probably has a long list of companies that look just like mine. Uh, that tell me that they're going to decent partner. >> We've had a lot of fun together. You and Mike the team and fly. Great party. Great networking. You gotta do that. >> Thank you. Great. Great party. Should hopefully my >> tombstone. Well, you gotta have the networking, and that's always good. Catalyst. That lubricant, if they say, is to get people going. But you guys were hanging out with us and the big data space that had Duke World. We saw Cloudera got to activist board members. That's not looking good there. It's unfortunate big friend of Amer Awadallah, but what ended up happening was cloud Right Cloud kind of changed the game a little bit, didn't change big data as an industry was seeing eye machine learning booming. So, you know, big data had duped change certainly cloud our speculation. But looking back over those 10 years, you saw the rise of the cloud really become Maur of a force than some people thought that most people thought Dev Ops really became the cultural shift. If I had to point to anything over the 10 years, it's Dev Ops, which is implies day to talk about your reaction to that because certainly independent on enabler, but also change the game a bit. >> It has its exploded. There's a couple things in there, so I think there's been a lot of innovation that's coming in the cloud platforms. There's a lot of innovation that cloud platforms have sucked up. We look at that. A lot of guys who back startups, one of things we always say is Hey, is this a primitive? Is this an infrastructure primitive? Because if it is, it's probably gonna be best delivered by a big platform unless you're able to deliver a very compelling and differentiated solution or service around it. And that's different. You know, it's it's different than having a solely a a p I accessible primitive that, you know you would swap out with the next thing if it was, you know, two cents cheaper or 2% faster. So when I think about what's been happening in the cloud, this kind of cloud to, oh, phenomena starts coming up, which is a lot of hell that excited very early on. It was about storage and compute and the real basic building blocks. But now you see people building really compelling experiences for developers, for database engineers for application developed owners all the way up and down this stack that yeah, there cloud companies, but they look a heck of a lot like more like solutions. And, you know, we've mentioned a couple companies in our portfolio that air going great. But there there's a ton of companies that we admire. You know, I look at what the folks that at Hashi Corp have done and what they continue to do. You know what a great business in in security and in giving people automation and configuration that that hasn't been there before. That's a phenomenal I >> mean, monitoring you mentioned is a monitoring to point out going on, he said. Pager duty Got a dining trace. These companies public this year, both public, and you got more coming around the corner, you got analytics is turning. That's calling it mean monitoring has been around for a long time. Observe ability. Now it's observe ability is the monitoring two point. Oh, and that's taking advantage of this Dev Ops Growth. Yeah, this is really the big deal. >> Yeah, well, it's if you're really getting into. And what a lot of this comes down to is velocity, right? A lot of people are trying to deliver software faster, deliver it more reliably, take away the bottlenecks that air between the vision that a product person has the fingers on the keyboard and the delightful experience that a user gets and that has a lot of gates. And I think one of the things that Dev Ops is really enabled is how do you shrink that time? And when you're trying to shrink that time and you're trying to say, Hey, if someone's can code it, we can push it well, that's a great way to do things except if you don't know what you've pushed and things were failing. So as velocity increases, the need to have an understanding of what's going on is going right alongside of it. >> So I want to get your thoughts on enterprise scale because cloud 2.0, it really is about enterprise. You guys have invested in pure cloud native startups. You've invested a networking invested in open sores. You guys house will have, ah, struggle. You are. But I have a strong view on Dev, Ops and Cloud to point out. But the enterprise is now experiencing that, and you guys also done a lot of enterprise deals. What's the intersection of the enterprise as it comes in with cloud two point? Oh, you're seeing Intelligent Edge being discussed Hybrid multi cloud, these air kind of the structural big kind of battle grounds with the changes. How do you guys look at that? How do you invest in that? How do you look for startups in that area? >> Yeah, well, I think we invest in it by starting from the perspective of the customer. What's the problem? And the problem is, a lot of times people know their security. There's compliance. And a lot of cases. There's a legacy infrastructure, right? But the it's not a green field environment is nowhere more applicable than in the enterprise. And so when you think about customers that are gonna need to accommodate the investments the last five and 10 years as well as this beautiful new vision of what the future is, you know you're talking basically talking about every enterprise CEOs problems. So we think a lot about companies that can solve those riel clear enterprise pain points security. One of them, um, we've had a bunch of successful cloud security companies that have been acquired already. We've got great stuff in compliance and data management and awesome company like Integris. That's up in Seattle and in really making sure that projects and software works well with legacy and more traditional enterprise environments, companies like replicated down in L. A. Um, you know, those folks have really figured out what it means to deliver modern on premise software and modern on premise really is, you know, in your V p c in your own environment in your own cloud. But that's on Prem Now that is what on Prem really looks like no one's rack and stack and servers in the closet. It's cloud operations. But if you're going to do that and you're gonna integrate all those legacy investments you've made in an audit, Maxis control et cetera, and you wanna put that together with modern cloud applications, your sass vendors, et cetera. You know you can't really do that in the native cloud unless you can really make it work for the enterprise. >> What is some of the market basket sectors that you see? Where the market second half of our market sectors that have a market basket of companies forming around it? You mentioned drivability. Obviously, that's one we're seeing. Clear map of a landscape developed there. Yeah, okay. Is there other areas just seeing a landscape around this cloud to point out that that are either knew or reconfigurations of other markets? Machine learning What's what. The buckets? What the market's out there that people are clustering around with some of the big >> high level. Well, I think one of things you're gonna see talking about new markets and people people. There's a bunch of It'll tell you what's already happening in history today. But if you want to talk about what's coming, that isn't really on people's radar screen, I think there's a lot that's happening in machine learning and data science infrastructure. And if you're a cloud vendor in the public cloud today, you are really ramping up quickly to understand what the suite of offerings are that you're gonna offer to both ML developers as well as traditional, you know, non machine learning natives to help them incorporate. You know what is really a powerful set of tools into their applications, and that could be model optimization. It could be, um, helping manage cost and scalability. It could be working on explain ability. It could be working on, um, optimizing performance with the introduction of different acceleration techniques. All of that stack is really knew. You know, people gobbled up tensorflow from Google, and that was a great example of what you could do if you turned on ml specific. You know, tooling for for developers. But I think there's a lot more coming there, and we're just starting to see the beginning. >> It's interesting you bring this up because I've been thinking about this and I really haven't been talking about a publicly other than the cloud to point. It was kind of a generic area, but you're kind of pointing out the benefits of what cloud does. I mean, the idea of not having to provision something or invest a lot of cash to just get something up and running fast with this machine learning tooling that's the big problem was stacking everything up and getting it all built >> right goes back. The velocity were talking about earlier, right? >> So velocity is the key to success. Could be any category to be video. It could be, um, you know, some anything. So we're >> also seeing another. The other side of it is, is another form of velocity is we're going to Seymour that's happening and things that look like low code or no code, so lowering the barriers for someone doesn't have to be a true native or an expert in domain, but can get all the benefits of working with, Let's say, ml tooling, right? How do you make this stuff more accessible? So you don't need a phD from Berkeley or Stanford to go figure it out right? That's a huge market. That's just stop happening. We've got a ah phenomenal come way company in New York called Runway ML that has huge adoption. Their platform and their magic is Hey, here's how we're gonna bring ML to the creative class. If you're creative and you want to take advantage of ML techniques and the videos you're working on, the content that you're creating, maybe there's something you can do here at the Cube. You know, these guys were figure out how to do that and saying, Look, we know you're not a machine learning native. Here's some simple, primitive >> Well, this screen, you know, doesn't talk about video, but serious. We have a video cloud of people have seen it out there, demo ing, seeing highlights going around. But you bring up a good point. If we want to incorporate State machine learning into that, I can just connect to a service. I mean slack, I think, is the poster child for how they grew a service that's very traditional a message board put a great you around it. But the A P I integrations were critical for that. They've created a great way to do that. So this is the whole service is game. Yeah, this is the velocity and adding functionality through service is >> Yeah, And this is this this idea that, um the workflow is what matters. I think it has not traditionally been a thing that we talked a lot about an enterprise infrastructure. It was. Here's your tool. It's better than the previous two or three years ago. Throat the new ones by this one. And now people are saying, Well, I don't want to be wed to the tool. What I really want to understand is a process in a workflow. How should I do this? Right? And if I If I do that right, then you're not gonna be opinionated as to whether I'm using Jiro for you know, you're for managing issues or something else or if it's this monitoring the other. >> So I got to get the VC perspective on this because what you just said, she pointed out, is what we've been talking about as the new I p. The workflow is the I P. That translates to an application which then could be codified and scaled up with infrastructure, cloud and other things that becomes the I P. How do you guys identify that? Is that do you first? Do you agree with that? And then, too, how do you invest into that? Because it's not your traditional few of things. If that's the case, do you agree with it? And if you do, how do you invest in? >> I've modified slightly. It's the marriage of understanding that work flow with the ability to actually innovate and do something different. That's the magic. And so I'll give you a popular problem that we see amongst a lot of start ups that come see us. Uh, I am the best, and I'll pick on machine learning for a second. I've you know, I've got the best natural language processing team in this market. We're going to go out and solve the medical coding and transcription and building problem. Hey, sounds awesome. You got some great tech. What do you know about medical transcription and building? Uh, we gotta go hire that person. Do you know how doctors work? Do you know how insurance companies work. That's kind of Byzantine. How? You know, payers and providers, we're gonna work together. We'll get back to you that companies not gonna be that successful in the marriage of that work. >> Full knowledge. Good idea. Yeah, expertise in the work edge of the workflow. >> Well, traditionally, you get excited about the expertise in attack and what you realize in a lot of these areas. If you care about work full, you care about solutions. It's about the marriage of the two. So when you look across our portfolio in applied A I and machine learning, we've actually got shockingly nine companies now that are at the intersection of, um, machine intelligence and health care, both pre clinical and clinical. And people are like, Wow, that's really surprising for, ah, for an infrastructure firm or an enterprise focus firm, like amplifying we're going. No, you know, there's there's groundbreaking ML technology, but we're also finding that people know there's really high value verticals and you put domain experts in there who really understand the solutions, give them powerful tools, and we're seeing customers just adopted >> and that, unlike the whole full stack kind of integration if you're gonna have domain experts in the edge of that work flow, you have the data gathered. It's a data machine learning. I can see the connection. They're very smart, very clever. So I want to get your thoughts on two areas around this cloud to point. I think that come up a lot. Certainly machine learning. You mentioned one of them, but these other ones come up all the time as 2.0, Problems and opportunities. Cloud one. Dato storage, Computing storage. No problem. Easy coat away. Cloud two point. Oh, Networking Insecurity. Yeah, So as the cloud as everyone went to the cloud and cloud one dato there now the clouds coming out of the cloud on premise. So you got edge of the network. So intelligent edge security if you're gonna have low code and no could have better be secure on the cover. So this has become too important. Points your reaction to networking and security as an investor in this cloud. 2.0, vision. >> Yeah, there's different pieces of it. So networking The closer you go to the edge, you say the word ej and edges, you know, a good bit of it is networking, and it's also executing with limited resource is because we could debate what the edge means for probably three hours. >> Writing is very go there, but what it certainly means is you >> don't have a big data center. That's Amazon scale to run your stuff. So you've got to be more efficient and optimized in some dimension. So people that are really at the intersection of figuring out how to move things around efficiently, deliver with speed and reduce late and see giving platforms to developers at the edge, which, you know if you've one of the big reasons for faster going public was to bring their edge. Developments story out to the larger market. Um, absolutely agree with that as it as it relates to broader security. We're seeing security started, stop being a cyclical trend and started becoming a secular one pretty much at the moment the cloud exploded and those things are not, You know, it's not just a coincidence, as people got Maur comfortable with giving up control of the stuff that that had their arms around for years, a perimeter right at the same time that they say we're going through everything online and connect everything up and get over developers whatever they want and bringing all our partners to our. The amount of access to systems grew dramatically right. At the same time, people handed over a lot of these traditional work flows and processes and pieces of infrastructure. So, yeah, I think a lot of people right now are really re platforming to understand what it means to be to build securely, to deploy securely, to run securely. And that's not always a firewall rack and stack boxes and scan packets type of a game. >> Yeah, I'm serious, certainly embedded. And everything's not just part of the applications everywhere. That's native. Yeah, final question for you. What do you guys investing in now? What's the hot areas you mention? Machine learning? Give a quick plug for your key investments. What's the pitch? The entrepreneur? >> Yeah, so again are pitched. The entrepreneur really hasn't changed from Day zero, and I don't see it changing anytime in the future, which is if you're a world beating technologists, you know you want someone who understand what it's like to work with other world beating technologists and take him from start upto I po And that's the thing that we know how to do both in previous career is as well as in the history of Amplified. That's the pitch. The things that we're really excited right now is, um, what does it look like when the best academic experts in the world who understand new areas of machine learning, who are really able to push the forefront of what we're seeing in reinforcement, learning and machine vision and natural language processing are able to think beyond the narrow confines of what the tech can do and really partner of the domain experts? So there is a lot of domain specific applied A i N M l that we're really excited about thes days. We talked about health care, but that is just the tip of the iceberg we're excited about. Financialservices were excited about traditional enterprise work flows. I'd say that that's one big bucket. Um, we're is excited about the developer as we've ever been. >> You know, you and I were talking before he came on camera for the cube conversation. Around our early days in the industry, we were riffing on the O S. I, you know, open systems interconnect, stack if you look at what that did, Certainly it didn't always get standardize. That kind of dinner is up with T C p I p layer, but still, it changed. That changed the game in the computing industry. Now, more than ever, this trend that we're on the next 10 years is really gonna be about stacks involving and just complete horizontal scalability. Elastic resource is new ways to develop Apple case. I mean a completely different ball game. Next 10 years, your your view of the next 10 years as this 1000 flowers start to bloom with stacks changing in new application methods. How do you see it? Yeah, well, >> what Os? I was a great example of this trend that we go through every few months. So many years. You, you, somebody create something new. It's genius. It's maybe a little bit harder than it needs to be in. At some point, you wanted to go mass market and you introduce an abstraction. And the abstractions continue to work as ways to bring more people in and allow them not to be tough to bottom experts. We've done it in the technology industry since the sixties, you know, thank you. Thank you. Semiconductor world All the way on up. But now I think the new abstractions actually look a heck of a lot like the cloud platforms. Right? They're abstractions. People don't. People want toe. Say things like, I am going to deploy using kubernetes. I want a container package. My application. Now let me think from that level. Don't have don't have me think about particular machines don't have to think about a particular servers. That's one great example developments. The same thing. You know, when you talk about low code and no Koda's ideas, it's just getting people away from the complexity of getting down in the weeds. So if you said, What's the next 10 years look like? I think it's going to be this continual pull of making things easier and more accessible for business users abstracting, abstracting, abstracting and then right up into the point where the abstractions get too generalized and then innovation will come in behind it. >> As I always say in the venture business, cool and relevant works and making things simple, easy use and reducing the steps it takes to do something. It's always a winning formula. >> That's pretty good. Don't >> start to fund a consistent Sydney Ellen. Of course not. The cube funds coming in the next 10 years celebrating 10 years. Great to see you. And it's been great to have you on this journey with you guys and amplify. Congratulations. Congrats on all your success is always a pleasure. Appreciate it. Take care. Okay. I'm here with steel. Dolly. Well, inside the key studios. I'm John for your Thanks for watching.

Published Date : Aug 15 2019

SUMMARY :

from our studios in the heart of Silicon Valley, Palo Alto, I've known you since the beginning. to be back. Yeah, on, by the way, Congratulations, fastly when public, thank you very much. and it's moving the right direction. So you guys came out early, Made big bets. So amplify has been around from the beginning to work with technical founders. So on the business model, just to get a clear personal congratulations Really good venturing by the way. out how to recruit a Kick ass team and figure out how to find product market fit and get that So the question is, I know you guys do step away and don't go on board. And you know what we do tend to be those pretty active. You and Mike the team and fly. Thank you. But you guys were hanging out with us and the big data space that had Duke World. you know you would swap out with the next thing if it was, you know, two cents cheaper or 2% faster. both public, and you got more coming around the corner, you got analytics is turning. And I think one of the things that Dev Ops is really enabled is how do you shrink that time? How do you guys look at that? You know you can't really do that in the native cloud unless you can really make it work for What is some of the market basket sectors that you see? You know, people gobbled up tensorflow from Google, and that was a great example of what you could do I mean, the idea of not having to provision something or invest a lot of cash The velocity were talking about earlier, right? It could be, um, you know, some anything. So you don't need a phD from Berkeley or Stanford to go figure it Well, this screen, you know, doesn't talk about video, but serious. as to whether I'm using Jiro for you know, you're for managing issues or So I got to get the VC perspective on this because what you just said, she pointed out, is what we've been talking about as the new We'll get back to you that Yeah, expertise in the work edge of the workflow. So when you look across our portfolio in applied A I and machine learning, in the edge of that work flow, you have the data gathered. So networking The closer you go to the edge, you say the word ej and edges, So people that are really at the intersection of figuring out how to move things around efficiently, What's the hot areas you mention? you know you want someone who understand what it's like to work with other world beating technologists and take him from we were riffing on the O S. I, you know, open systems interconnect, stack if you look at what that did, We've done it in the technology industry since the sixties, you know, As I always say in the venture business, cool and relevant works and making things simple, easy use and reducing the steps That's pretty good. And it's been great to have you on this journey with you guys and amplify.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Mike DauberPERSON

0.99+

MikePERSON

0.99+

twoQUANTITY

0.99+

$3,000,000,000QUANTITY

0.99+

New YorkLOCATION

0.99+

Sunil DhaliwalPERSON

0.99+

August 2019DATE

0.99+

five daysQUANTITY

0.99+

SeattleLOCATION

0.99+

Hashi CorpORGANIZATION

0.99+

JohnPERSON

0.99+

Silicon ValleyLOCATION

0.99+

three hoursQUANTITY

0.99+

$200,000,000QUANTITY

0.99+

FirstQUANTITY

0.99+

seven yearsQUANTITY

0.99+

10 yearsQUANTITY

0.99+

AmazonORGANIZATION

0.99+

AppleORGANIZATION

0.99+

2%QUANTITY

0.99+

1000 flowersQUANTITY

0.99+

10th yearQUANTITY

0.99+

OneQUANTITY

0.99+

Amplify PartnersORGANIZATION

0.99+

nine companiesQUANTITY

0.99+

Palo Alto, CaliforniaLOCATION

0.99+

LevanPERSON

0.99+

ByzantinePERSON

0.99+

SonnyPERSON

0.99+

GoogleORGANIZATION

0.99+

oneQUANTITY

0.99+

third fundQUANTITY

0.99+

bothQUANTITY

0.99+

DollyPERSON

0.99+

amplifyORGANIZATION

0.99+

Deli WallPERSON

0.98+

two pointQUANTITY

0.98+

SiriTITLE

0.98+

10 yearsQUANTITY

0.98+

Data DogORGANIZATION

0.98+

CubeORGANIZATION

0.98+

two areasQUANTITY

0.98+

second halfQUANTITY

0.98+

IntegrisORGANIZATION

0.98+

1/3QUANTITY

0.97+

Amer AwadallahPERSON

0.97+

two centsQUANTITY

0.97+

this yearDATE

0.97+

firstQUANTITY

0.97+

Dev OpsTITLE

0.97+

3 yearsQUANTITY

0.97+

first callQUANTITY

0.96+

first capitalQUANTITY

0.96+

MaxisORGANIZATION

0.96+

First moneyQUANTITY

0.96+

SeymourPERSON

0.96+

sixtiesDATE

0.95+

O'NeillPERSON

0.95+

Palo Alto, CaliforniaLOCATION

0.94+

todayDATE

0.94+

PremORGANIZATION

0.94+

two days a weekQUANTITY

0.93+

Third fundQUANTITY

0.92+

200,000,000 PlusQUANTITY

0.92+

Runway MLORGANIZATION

0.91+

twoDATE

0.91+

Next 10 yearsDATE

0.9+

MaurPERSON

0.89+

First timeQUANTITY

0.89+

next 10 yearsDATE

0.88+

three years agoDATE

0.88+

StanfordORGANIZATION

0.87+

ClouderaORGANIZATION

0.87+

four seedsQUANTITY

0.85+