big. There’s too much to retrofit. No one can agree on a standard. And it’s too much work. It’s hard enough to get people to put hyperlinks in.
X: So tell us about your approach to the problem. (At Xconomy, we’ve reported extensively on Evri, which helps you browse information by making connections between entities on the Web, and Gist, which integrates your e-mail inbox with blogs, articles, and social media to keep you informed about your contacts.)
SH: The birth of Evri was sort of an “aha” moment that we had through the back and forth moments. If you could up-convert the Web itself, by using smart, scalable algorithms that understand, “This is a person, this is a place, this is how these things are connected, this is the meta-data about those things”—you can effectively rewire the Web at the surface level. Such that any information you’d want to know at any moment in time is a click away. In effect, convert the Web into a truly browsable interface, versus a searchable interface. You reduce the need to keep going back to [your inbox or search box] by bringing contacts back at the moment you need them. If algorithms understand that at a foundational level, there are big opportunities around that. That’s the genesis of the thinking. Paul was in every one of those conversations.
X: How does this kind of information discovery relate to what’s going on with social media more broadly?
SH: My current fascination is the catalyst that Twitter has been to convert Web media into almost a stream, or feed-based view, of the world. Granted, all of this today—Twitter and Facebook feed views—are through the lens of other people. Facebook is mostly social stuff, and Twitter is a bit more business. But with Twitter, it’s about this person who I respect just wrote about something, so now I should follow this link. That’s discovery for me. I’m not Googling for it. I’m not going to some start page or a media site. I’m just reading links based on my network and people that matter to me. In some cases, they are re-tweeting other people. So this human filter becomes this highly valuable, highly accurate lens of data—it is sort of our new model for consuming media. Which I’m sure you guys think about, being in that business.
X: So let’s sum up Vulcan’s role in all of this. Where is search and social media headed?
SH: When I think about how it relates to us, as it relates to Gist and Evri, it is very thematic. How do you solve information overload? Can you use algorithms to do a better job of bringing the data to us? In Gist’s case, we’re still early days, but we figured out a bunch of stuff that matters to you because you let us, and now we’re giving you a feed. Just turn it on, dial in, and it’s coming at you. You can consume it or not, but it’s all there for the taking.
In the case of Evri, and I’m not sure Neil Roseman [founder and CEO] has alluded to all of this yet, but what you’re going to see is, we’ve got Evri pages and widgets and so forth, but what we’ve really got is 3-plus million feeds being created on the fly by semantic parsing of the Web as it comes through in real time.
Imagine if suddenly you don’t need to rely on a single person you’re following to get an interesting feed. Imagine you can follow anything you want. Even any category of thing, because we semantically understand that. I might want to follow Seattle journalists, not specifically, but as they are referenced in the media. I might want to follow a quarterback, or a band, or a song, or so forth. These all become portable, subscribable, smart objects that can be passed around and consumed in different applications. So if you think of Tweetdeck for example, it’s symbolic of a new Netscape. It’s a new window into a new form of content that didn’t exist a year ago. What sort of new things will feed that ecosystem? We think of Evri as being a new source of content on these new feed-view platforms we’ll bring at you. It will radically change how we think about consuming media.
