 Data Science at Bitly is an interesting job. We have access to data flowing through all types of networks. So we have data coming from Twitter, from Facebook, traffic, email. And through that data, we can get location information, country of work, like country with the refers, how information is jumping from one network to the other. All that analytics that I've described is free. If you put the plus at the end of a Bitly URL, you get to see all the free analytics. And we all have enterprise analytics for our enterprise customers who have the custom URL shortener so they can get a little bit more information about sentiment, reputation monitoring, a little bit more geographical information, and stuff like that. You know, I remember just, it seemed like a decade ago, but it was only a couple of years ago, the big rage in real time search. You had Collectika One Riot, which when Collectika went out of business, One Riot was sold to walmart.com. And with Cosmix, you guys were around, you guys were being incubated, I believe, at the time. People were building these real time search engines like Google, like thinking that people are going to really actually sit there and watch a screen and go really fast. But it's different, though. I mean, it's not necessarily the same search experience, but it's about discovery, right? So can you share with us the data science involved around surfacing discovery, whether that's analytics, connecting people, some of the magic that has to happen behind the scenes? Well, in the old traditional way of search engines, you basically wrote mini crawlers, you put them out on the internet, and you tried to discover new leaks. With the social media, the real time web, the content comes to you. It's basically instead of spiders and crawlers, you're more filtering pipes. And it's a fire hose in how well you can handle it. And that's the nice thing about Bitly, especially as we're starting to do a little bit more research, it's not older content. We have the freshest content because it's the stuff people uploaded just minutes ago. So the data science component is how do you take interesting things from a torrent and make sense of it, make sense of it in real time, and provide information to people in a timely manner that they can make some decisions based on it. I mean, we're totally geeks on this whole movement of what this all means in terms of the new social web. I mean, SiliconANGLE, our motto is where social science meets computer science. So there's a lot of math involved, there's a lot of computer science, there's a lot of kind of sociology in this real time web. The question I want to ask you is, because a lot of folks are new to this, like real time, what does it all mean? Talk about this notion you mentioned, content finds you, right? That's kind of most intelligent content based upon you now connected to the network. You guys have source destination event where people share stuff on Facebook or share something on Twitter, which is now a norm in the internet society. People are sharing with mobile phones, et cetera. You have source destination events. So you guys are tracking these new channels. And marketing people and people in general say, oh, there's new channels are out there. Social channels. I mean, social channels basically means basically distribution of content in social networks or the web, mobile phones, social networks. Explain to activity streams and this new paradigm. What is it, is it real? How real? And what are some of the factors involved in that? I believe very much it's real. It's real in the fact that just the number of devices people are using to connect to the network is changing and adapting in ways, 10 years ago, we're just not everyday occurrences. I mean, just the amount of people who have internet-based mobile phones and how they use it and how they use social networks and how they gather information. I mean, back 10 years ago, people had the palm that could connect to the network and that was a boutique item that was very expensive. Phone.com. Remember those days? Exactly. And now, you know. Crappy browser. Typing in URLs. And now, it's ubiquitous, nearly. And so that changes how people access information and how they produce it, too. So updates are not necessarily coming in huge, long blog posts. They're coming in quick tweets about a plane going into the Hudson and that real-time nature of it and how that creates a critical mass. I mean, we're seeing examples. Obviously,