[protected-iframe id=”3247996cace7c8edb11bc389feb82e0f-14960843-61002135″ info=”http://new.livestream.com/accounts/74987/events/2117818/videos/22051661/player?autoPlay=false&height=360&mute=false&width=640″ width=”640″ height=”360″ frameborder=”0″ scrolling=”no”]
Input sound file:
1001.Day 2 Batch 2
Session Name: Launchpad
Please welcome your MC, Joe Weinman, back to the stage.
Joe Weinman 01:39
Hi there everyone.
Joe Weinman 01:40
Welcome back, hopefully you had a great break. Couple of quick things, cellphones off, mikes for questions, no-one’s standing at the wall, so I don’t have to say that. This is, I have to tell you, my absolute favorite part of the incredible GigaOM Structure event, which has already raised the bar so high. I don’t want to take any time away from it by telling you how great it is, I’ll let you see for yourself. We have first of all, a distinguished moderator, three distinguished judges. We’ve got Farah Giga, well-known venture capitalist, we’ve got Ann Winblad, we’ve Bipul Sinha, we’ve got Luis Robles, and they are going to either make mincemeat or create the future billionaires, and so without further ado, let’s bring Farah out on stage, and she’ll explain the whole launchpad process. Keep your cellphones on, because audience voting is a critical part of the competition. So without further ado, Farah.
Farah Giga 02:45
Thank you for the introduction Joe. As you said, I’m Farah Giga, currently an EIR at Data Collective VC. For the rare few who don’t know who they are, DCVC is the premier early stage fund investing in big data companies. Before data collective, I used to be a VC, but saw the error of my ways, and left the dark side to become an entrepreneur. No offense to our esteemed judges, who I’m going to introduce in a few minutes. First, let me tell you a bit about the Launchpad competition. Six companies were selected by the GigaOM team out of a ton of submissions. They each get four minutes to tell us about their companies, and if they go over the four minute mark, watch out, I’m going to come on stage and cut them off. After the presentation, each judge will give them a score between one and ten. If I find them interesting, we’ll ask the judges for additional commentary. If they’re super boring, I’ll save you the pain and we’ll just move along. Hopefully that doesn’t happen to any of our companies. Once all the companies are presented, we’re going to tally the results for the judges’ choice award. As we all know, VCs don’t always get it right, so American Idol style, we’re going to ask you, the audience, to text your vote to the numbers displayed on the big screen. We’ll see if the crowd has more wisdom than the judges, which I think they do. We’ll be tracking real-time results, especially handy for those of you running a sports book here at the conference. We’ll then present the judges’ choice awards and the people’s choice awards to the winning companies. Okay, let’s meet the judges. First, we have partner at Sequoia Capital, Luis Robles.
Farah Giga 04:30
I introduced them a bit early, I guess. Next, we have managing director at Hummer Winblad Venture Partners, Ann Winblad, and finally we have Bipul Sinha, partner at Lightspeed Venture Partners.
Farah Giga 04:58
Well, that puts the majority of the women here at the conference up on stage. Let’s start the show. Please welcome 28 Milliseconds.
Hi. My name is Matthias, and I’m from 28 Milliseconds. At 28 Milliseconds we are a group of people who are extremely passionate about database technology. We want to fundamentally change the way people extract meaning and valuable out of all the data that they have. Today’s world is full of data, and it comes in a huge variety of data sources. For example, traditional database systems, NoSQL data stores, or web services. The data is represented in a huge variety of data formats, from completely structured tables to nested flexible data formats such as JSON or XML, down to completely unstructured text. For this data to be valuable, a lot of processing needs to happen to turn it into actionable information. For example, the data needs to be extracted from the source, transformed, cleaned, filtered, aggregated, and correlated. People are doing this today, but they are mostly gluing and stitching together solutions around a technology that was developed in 1978, called SQL. As you can imagine, in 1978, SQL was not designed for today’s complex data challenges, because it requires an upfront schema and works with tables instead of nested data structures. At 28 Milliseconds, we have developed a platform that allows people to get from raw data to actionable information far faster than ever seen before. In the heart of our technology is a language called Jsonic. Like SQL, Jsonic is declarative, it is highly productive, and very easy to use and understand for all of the SQL users in today’s marketplace. However, it delivers to them a set of capabilities that allow them to do more with far more data types, but much less code than ever before. We are harnessing this powerful language into an information processing platform called 28. io. With 28. io, you can connect to all of your data sources, and process the data across all of them. Our architecture allows us to massively scale and parallelize the information processing across cloud resources. To give you a sense of what that means in the real world, I’d like to explain to you how one of your customers is using it. Every day, the trademark office publishes all of its data as XML on the web. Within our platform, we extract that one terabyte of XML data, preprocess it, transform it into JSON, store it in MongoDB, and index it. This allows trademark lawyers to use our platform to do the full-text and phonetic searches that they need to do every day. At the same time, we are transforming this XML data into beautiful websites, and store the HTML on Amazon allowing people to take a look at all the information around a given trademark. The entire data processing part of this application has been built on top of 28. io using Jsonic. However, the amount of code and effort that was required to build this was extremely small. 28. io is available starting today. It comes as a subscription service, with free and multiple paid plans. It is also available on-premise using a traditional license-based model. I would love to show you the platform and all the details offline. Thank you very much.
Farah Giga 09:05
Thank you, 28 Milliseconds. Now judges, can we get your scores please? We have a nine, an eight, and a seven. They’re pretty close. Luis, can you tell us why you thought they were a nine?
Luis Robles 09:20
Sure. Pretty intrigued by this company, maybe a little biased by our involvement with Mongo. With the amounts of data being generated in NoSQL databases, I think there’s a real opportunity to do analytics separately from it. Sounds like a very powerful alternative to ETL, which is a very complicated process, and so I think there’s a great opportunity here.
Farah Giga 09:36
Great, thank you. Next, let’s welcome to the stage AppScale Systems.
Woody Rawlings 09:55
Good morning, and thank you. My name is Woody Rawlings, and I have the pleasure to serve as the CEO of AppScale Systems. AppScale is in the data recovery business. Our products provide automated failover and migration for your apps and data across clouds. We make your apps highly available and hybrid-aware across cloud platforms and in your data center. We bring portability to your applications. Public clouds are amazing. ADB West has blazed the way, and their peers both big and small are looking to replicate the model. It’s clear that on-demand utility computing is here to stay, and now we’re pushed further up the stack, beyond infrastructure as a service, as we’re witnessing this proliferation of public platform as a service offerings. Why? Because the future is web and mobile. Enterprises need to support a new choose your own device world order. PAS makes this easy. But there’s a big problem. Now, you have no control over your infrastructure, because it’s running on somebody else’s resources. Compounding this is the multiple concerns regarding lock-in, disruption, and privacy. AppScale solves this problem. We future-proof your app. With AppScale, your app and your data will automatically failover into the public cloud or into your own data center, ensuring 100% uptime for your revenue producing, mission-critical applications. We’ve targeted Google App Engine as the first platform that we’re going to provide our failover product for. The reason for this is simple. Google has studied their developers over the past ten years, and they have now taken their best practices and packaged them in a platform called Google App Engine. Google App Engine– if you haven’t tried it, you should. It vastly simplifies the process of creating mobile and web applications. The numbers are impressive. Right now there are 3 million active applications running on Google App Engine, and that is up from 1 million applications a little over a year ago. Pretty amazing. More impressive is the statistic that half of the internet in the course of a week touches a Google App Engine service. Our business model is simple, and it’s straightforward. We’re open source. The code is freely available and always will be. We’re going to monetize buy our proprietary products, and the first of those products is called ScaleSafe. It provides this automated failover and migration for your Google App Engine application. Our future products will support other public PAS platforms as they gain adoption and market share. We’re excited today, because we’re launching our company here at structure, and we’re very grateful to GigaOM for giving us this opportunity. Our initial products will be ScaleSafe, and they will provide this automated failover, and they’re ready for purchase today. Other PAS vendors will soon follow. If you’re a Google App Engine developer, or your company depends on Google App Engine, we’d love to talk to you. Wouldn’t it be worth $1000 a year to make sure that your app never suffers downtime? Thank you.
Farah Giga 13:56
Thank you, AppScale. Judges, can we get your scores? A seven from Luis, a seven from Ann, and a six from Bipul. Got to ask you, why the six?
Bipul Sinha 14:09
I like the vision, but you asserted that you are going to provide the failover solution, but you never told us why your solution was better, why you would win in the marketplace, and what the unique angle is that you have in the market.
Woody Rawlings 14:29
Sure. I’d be happy to follow up with that offline.
Farah Giga 14:31
Good questions, Bipul, thank you. Let’s get the next company on stage. Next we have Factor. io. Got to love the company branding right there.
Maciej Skierkowski 14:50
Hi, my name is Maciej Skierkowski, I’m the CEO and co-founder of Factor. io. We automate the deployment process so developers can focus on revenue generating code. We are here today because deploying to the cloud sucks. When you look at the way developers work today, they have the code that they write on their own machines, they want to be able to easily deploy it to the cloud. But it isn’t that easy. They first have to collaborate with with their teammates to make sure none of their code conflicts. They’re not just deploying to a single cloud, they’re deploying to multiple cloud provders with multiple servers in each. Along the way, they have to work with a lot of different tools. They have their code repository tools, project management tools, live chat and email, continuous integration for test automation, and configuration management to set up all those servers. This is what the deployment process looks like. It is spaghetti, yet there is no single service out there that allows us to integrate all these services together. A few companies though, these smart guys have figured it out. They have implemented sophisticated automation for the deployment process. For example, Amazon.com on average deploys code into production in six seconds. Speed is their competitive advantage, and time to market is everything. The rest of us are stuck trying to glue all those things together piece by piece, and none of the work we put into it generates revenue. It is time spent away from working on the product, and really doesn’t get us any closer to customer value. There is a better way, Factor. io. We automate that entire deployment process. Let’s have a look at a few specific examples. Unfortunately we don’t have time for a few, so we’re going to look at one. [chuckles] In this case, we’re looking at NBC. What they have done is using Factor. io’s Dragon Drop user interface, they have created a workflow. In this case, they’re listening for events from Github, when a developer pushes new code, they run it through the test process, compile it, and deploy it through Heroku. This is just one specific example, but we can also support a lot of different services and a lot of different workflows. In just two minutes, they are able to do more than two weeks’ worth of dev work. Yes this saves time and money, but it also integrates and organizes all those services. For example, if I hire a new developer, Joe, I can let him have access to our test systems but not production. Just as easily we can revoke his access, too. We also have central accountability, so we know exactly who, when and what was deployed. That by the way is my co-founder right there. By automating the entire process, we have a high level of confidence that everything will work every single time. You don’t have to take our word for it though, there is a graph there that shows in the last three months over 350 developers from these companies and others have signed up for this service, and we are working on a few key partnerships to help further accelerate this growth. Before starting Factor. io I was a Director of Product at AppFog, my co-founder was engineering manager. Together we played a critical role in growing the user base from just 1, 000 to over 100, 000 users through acquisition by Savvis Centurylink. For the hosted service, we have a freemium pricing model, it is free for developers working individually, and when they work in a team environment, we have two paid tiers. We are also working on an on-premise enterprise offering. As of right now, I’d like to officially announce that we are launching into public beta. Help Factor. io become the new de-facto standard for how developers automate their processes, so they can focus on revenue generating code.
Farah Giga 18:50
Not going to be tough. [chuckles]
Farah Giga 18:57
Okay, judges. A seven, nine and eight. Luis, why the seven?
Luis Robles 19:02
I really like the premise, I think it could be really powerful to apply to a broader set of SAS applications as an integration point. I worry a little bit about the defensibility, I worry a little bit about the developer audience as the initial target, which is very capable of cobbling a couple of these things together. But great customer traction, I’m sure you’ll iterate and evolve.
Farah Giga 19:22
Great, thanks for your input, Luis. Defensibility is what keeps me up at night too. Let’s bring the next company on stage. Next we have Metrica. I wonder what this could be about. Analytics anyone?
David Crawford 19:40
I’ll just bring this down… okay. A couple of friends have a brilliant idea. They quit their jobs and start a company. FitBit for dogs. They throw up this website, and of course they want to monitor traffic with Google Analytics. They start a blog on Tumblr, start posting on Facebook and Twitter. They build their mobile app on top of Pars, which stores user data in the cloud, and they need mobile analytics as well. So they add Google solutions as well, but it’s not quite perfect, so they add MixPanel and Flurry. They start tracking with Optimizely, and drive traffic with Google Adwords, Facebook ads, and Twitter for business. They add MailChimp and SendGrid for email, Stripe for payments, and Zendesk for cutomer service. Phew. Then they hire a data analyst.
David Crawford 20:32
They ask her what kind of emails are improving customer attention, so she looks at data from three services. To evaluate social media, she looks at posting activity and analytics data from five services. To measure customer lifetime value, she needs Stripe. To segment that by marketing source, that’s stored in Parse, and then to compare cost of acquisition, she needs to look at three more services. With the advent of cloud, data fragmentation is the new status quo. There’s valuable insight hidden in those silos. Today, businesses are throwing people at the problem, creating whole teams that build tools for analysts, or requiring that their analysts be programmers themselves. This is expensive, it’s a recruiting nightmare, and now there’s a better way, MetricaDB. MetricaDB removes the complexity of integrating all these services and unifies them behind that 30 year old lingua franca of data analysis, which is SQL, that hundreds of thousands of analysts and developers know. Here’s how it works. You simply create an account on our website, connect to a data source, often you just click “Allow Access”, and then write a query and export the results to Excel. We give you a console in the cloud, where your services look like tables in a database. When all of your data’s in one place, it’s easy to experiment and explore the intersection between those services. You might find patterns in your MixPanel data that can predict customer support tickets in ZenDesk. You might segment your Optimizely data by real customer spending in Stripe. But your most valuable data is still in your own proprietary databases. That’s why we connect cloud to proprietary data, either SQL or NoSQL, on-premise or not. The data integration market is four billion dollars. Entrants like MuleSoft and SnapLogic are tackling cloud integration for enterprise, but there are tens of thousands of customers for whom enterprise software is not meeting their needs. These companies, whether they are small companies, or agile teams inside of larger ones, are looking for self-service software that works with the tools and services that they already know. At MetricaDB, our ambition is to be the analytics platform for this new data world, and we’re just getting started. I’m David Crawford, and I’ve worked as a product manager and an engineer at companies backed by Kleiner Perkins, and Andrews and Horowitz. MetricaDB is born of my own experience, and I’m excited to help companies embrace data-driven culture. So, sign up on our website, and if you’d like to chat, drop me a note at [email protected] Thank you very much.
Farah Giga 23:36
Thank you Metrica. Judges, can I get your scores, please? Got a nine from Bipul, and eight from Ann, and a seven from Luis. Let’s ask the person in the middle for a change, Ann.
Ann Winblad 23:46
I’m on the board of Neilsoft, so I understand the problem of data integration quite well, and how important these solutions are. Clearly SQL is the lingua franca. I’d like to understand how it works better, that’s why I didn’t give you a nine, but definitely whoever can bring this data integration solution to the individual analyst, corporation, is the company that wins. It looks like a big opportunity to me.
Farah Giga 24:15
Great. High praise from Ann. Next we have Salt Stack, don’t know what this one could be about.
Mike Chen 24:40
Good morning. My name is Mike Chen, and I’m the chairman and co-founder of Salt Stack. Two and a half billion people use the internet, but you and I know that all this cloud and web scale doesn’t happen by magic. Behind the internet of everything are servers, data centers and software that make it all work. Web consumers expect modern infrastructure to support massive scale and the always-on experience. There are hundreds of millions of servers in the world today. With automation, let’s realistically assume one sysadmin can manage 50 servers, assuming a 60 hour work week and unlimited five hour energy shots. This is a problem, and you I know that the internet and cloud is at risk. Servers need to be deployed and virtualized, and application stacks provisioned and configured to support complex production environments at scale. This complexity becomes a breeding ground for Murphy’s law, and things will break. When infrastructure breaks, sysadmins redploy and reconfigure over and over again. Data centers are the factories of our time, and we have new industrial revolution our hands. Legacy systems and configuration management tools that were supposed to help typically make the problem worse. Salt Stack exists to make the cloud assembly line fast and effective, and our clients are deploying legions of software based minions to automate all the internet factory jobs that no-one wants to do by hand any more. Tom Hatch, my co-founder, was an assembly worker, building the internet one cloud at a time. He was fed up with legacy management tools that were too slow, too difficult to use, and too difficult to automate web scale. He wrote Salt in his basement, in February 2011. He wrote it in Python as a very fast and flexible remote execution engine. In two short years, it has exploded in popularity. Salt was built from the ground up to manage the complexity of physical or virtual server environments, at the scale of public and private clouds like AWS and Google Compute Engine or Rackspace. According to the 2012 Github Octoverse list, Salt Stack was listed as a top ten project for attracting the highest number of contributors. For perspective, we were listed right next to Openstack on that list. About a year ago, after two successful software exits and a stint on Wall Street, I was asked to join Tom as Salt Stack’s CEO and co-founder. Together, we make a unique blend of open and commercial software expertise. Today our software is being used by massive software development organizations and thousands of dev ops pros from around the world to essentially build and maintain a better internet. Early adopters include companies like LinkedIn, HP Cloud Services, amongst hundreds of other first movers. Before I wrap up, I’d like to share how Salt Stack, an open source software company with 15 employees intends to continue to build out its commercial model and its open source community. First, Salt Stack is 100% open. Second, our platform is entirely agnostic. We run on any cloud, any infrastructure, any OS or hypervisor. Third, I’m pleased to announce today that Salt Stack’s enterprise license is available today commercially. In conclusion, Salt Stack is modern automation for the modern infrastructure. We have a substantial opportunity in front of us, we’re growing rapidly, we’re hiring selectively, and today I’d appreciate your vote for Salt Stack. Thank you very much.
Farah Giga 28:38
Thank you, Salt Stack. It was great learning more about what you guys do. Judges. A ten, a seven, and a nine. Wow, a ten! Luis, does your sister work there or something?
Luis Robles 28:50
Very intriguing value proposition here with a grassroots adoption. This project has come out of nowhere, with hundreds of contributors, lot of momentum behind it, I think it’s very intriguing. Some of our portfolio companies are using this, we’ve heard wonderful things, obtaining server to admin ratios of hundreds to one, which I think is fairly compelling. Intrigued to find out more about how you turn that open source project into a commercial business. Nice job.
Farah Giga 29:17
Thank you Salt Stack. Last, but definitely not least, we have Synapsify.
Stephen Candelmo 29:35
Thank you very much. Good morning, my name is Stephen Candelmo, CEO and Co-Founder of Synapsify, the text analytics and search API that is solving the problem of written content overload. Just a quick snapshot, other than being sixth in your program but hopefully number one in your hearts, we are headquartered in Washington DC, with a satellite office in Los Angeles. We just closed a seed round of $750, 000, led by ICG ventures, which is the venture capital round of Ingram Content company. We have five pilot clients, that are enjoying our cloud-based solution all hosted on AWS. Our team of six is led by a management team with over sixty years of combined experience in starting and growing technology companies, such as FitBit, Lumify, and Visible Technologies. What is the problem that we are trying to solve today? The text analytics vendor space is very crowded, and that’s primarily due to the fact that there has been an explosion of written content. It appears that everyone is generating written content at an unprecedented rate. In fact, unstructured text accounts for 80% of all data available for companies to analyze and understand, which truly represents the other side of big data. This has created a huge market opportunity, which Gardner predicts to reach $3.8 billion by the end of this year, with double digit growth over the next several years. Unfortunately, text analytics is currently in a trough of disillusionment, primarily due to the fact that the results have not met the expectations. The question is why. Despite all the advances in technology, to actually get beyond simple positive or negative sentiment or keyword extraction companies are still required to use humans to read and analyze this content, which is costly, time consuming, and simply cannot scale. We believe that there’s a better way. With our patented technology, we can automatically analyze and read any text, all the way up to a book, be able to summarize and reveal the qualitative metrics in a human-like way, which ultimately allow us to score and rank any piece of text that is pushed through our system, enabling the most relevant and useful content to always be raised to the top, allowing our users to perform their jobs in minutes instead of hours. We are delivering this through our API platform which allows our users to access this technology at scale in an effective manner, producing what we believe is unique qualitative metrics, which measure the value of content, such as credibility, quality, gravitas, tension and more. Further, being able to create a visual snapshot or fingerprint of text, which allows us greater accuracy of search and thematic analysis. Given the ubiquity of text, we believe that the applications are endless, and we’re just scratching the surface in our use cases of social media analytics and publishing. We are attacking this market through an enabling strategy, by offering our API and self-service apps to the enterprise, market research companies, developers, and analytical partners, through direct sales and channel partnerships. It’s all based on a very straightforward business model, with flexible tiered pricing all based on data usage. In summary, we are very excited about Synapsify, given its disruptive technology, its massive and growing market that is not going away, its application in multiple industry use cases, backed by a clear business strategy, all building towards a highly scalable and capital efficient business, all achieving our mission of enabling others to create and understand smarter contents for a smarter role. Thank you very much.
Farah Giga 33:42
Wow, three sevens. I’ll just choose randomly, Ann.
Ann Winblad 33:47
I think for the venture capital community, if you’ve been around for while, you’ve the analyst movie too many times. It sounds like you’ve done some incredible things technically, my big question would be how long does it take, even with your open APIs, to really prove the value proposition and the use cases. What will all the competing forces be between that use my technology to build a solution, can you build a big company around that?
Farah Giga 34:19
Guy, do you agree with that? Or is there another reason you gave them all sevens?
Bipul Sinha 34:21
From my perspective, it is not a technology play, it is a business use case play. You have so many ways to use these analytics, it’s really your enemy. You need to finalize one or two core use cases where you are creating disproportionate value, and go to market. It’s all about identifying use case, who you sell to, and what’s you disproportionate advantage over what they are doing today.
Ann Winblad 34:49
I think we’re saying the same thing.
Farah Giga 34:50
Whoever said VCs aren’t lemmings? Thank you, Synapsify.
Farah Giga 35:01
Thanks to all the companies that presented today, it was definitely a great set of presentations. GigaOM really knows how to put on a good show. Why don’t we give them all another round of applause?
Farah Giga 35:16
Now the fine folks at GigaOM are going to tally the results, quite a nailbiter. In the meantime, audience, it’s your turn. You can vote by texting the code associated with your favorite company to 22333. While you guys are voting, let’s see what the judges thought about the companies and the overall competition? Bipul, what did you think? Any standouts? Any you wish you had put money into and didn’t? Or any you think that aren’t currently in an area you’re investing in?
Bipul Sinha 35:52
I like Metrica the best, because the data fragmentation over cloud services, and how do you integrate that data and get intelligence out of that data is a very interesting space. I also thought 28 Milliseconds is an interesting company. Just having the new access layer is not enough to get market penetration, they need to integrate one or two apps and then provide the platform for the rest of the crowd.
Farah Giga 36:28
How about you, Ann. How do these companies relate to some you’ve seen in the past? You’ve had a lot of experience in the VC industry.
Ann Winblad 36:35
I gave my highest scores to the two that I would put in a class called dev ops. I think this is a new emerging category, where before we’ve had developers over here and operations over here. We’ve certainly seen that happen already in our portfolio companies, that those are not separate. In enterprises more and more, we’re seeing a new leadership role called dev ops. That’s extremely interesting to me, I’m also on the board of Sonatype, which runs a central repository, last year we had about 8 billion components downloaded. So we know the acceleration of app development is increasing, and deployment has to follow that. So I like the dev ops category and I like Factor. io the best.
Farah Giga 37:21
I think we’d all agree about dev ops. Thank you Ann. How about you Luis, anyone you’d give the classic, “It’s not me, it’s you, we have competing investment, it’s not in my area of expertise”?
Luis Robles 37:34
Overall I thought it was a great set of companies, I really like how focused they were on customer needs and requirements, and I think they’ve accomplished a lot. AppScale in particular stood out to me as a company that had done a lot with a very small team to replicate the Google App Engine with such a small team is impressive.
Farah Giga 37:47
Great, thank you all for your feedback. Now, for the moment we’ve all been waiting for. We have the results, of the judges’ choice awards. Let’s see. We were going to a third place, but we actually had a three-way tie for second, between 28 Milliseconds, Factor. io, and Metrica. So congratulations to those companies.
Farah Giga 38:24
The overall winner for the judges’ choice awards was Salt Stack. Can we please have them on stage to get their award?
Farah Giga 38:37
Great job, we really enjoyed your presentation. Congratulations. Let’s see what you, the audience thinks. It looks like the audience didn’t agree with the judges, looks like Factor. io was the people’s choice award, just by a smidge, although Metrica was a very close second. So could we please have Factor. io come on stage to get their people’s choice award. Great job. Well, it’s been a fantastic competition. Congratulations again to Salt Stack and Factor. io. Now I’m going to turn it back to Joe to continue the show.
Joe Weinman 39:26
Thank you Farah. Thank you judges, thank you to all the contestants, that was fantastic. This is the Structure conference, but it isn’t just infrastructure. It’s also superstructure. So to talk about the transition of value above the core infrastructure layer up into the applications layer, we have Barb Darrow from GigaOM with Lew Cirne and Steven O’Grady.