Almost a year ago, I wrote about semantics and social networking as threats to Google. In that post, I referenced a prior article on investments in natural language processing, such as Microsoft’s acquisition of Powerset, which is now part of Bing.
There has been some speculation that Freebase is a vehicle for Metaweb to prosper from its semantic web infrastructure when used for commercial purposes. As I recall, Metaweb raised over $40 million in Series B around the time they started building Freebase. The investment was led by Goldman Sachs. Metaweb’s seasoned investors were unlikely to invest so much in a business that cannot project a return on that investment. Almost certainly, Metaweb has firm plans for realizing over $100 million in revenues. Most likely, for these investors and the amount of capital, target revenues by 2014, five years after the second round, would be in the vicinity of $1 billion. Obviously, there is a lot of work to get there from around zero today.
Some of the bubble in raising those funds has burst. The economy would crimp the valuation and investment if made today. And the semantic web has yet to produce a winner, so with less enthusiasm, the investment would again be less favorable today. All this is modulo the business plan. If the business plan withstands scrutiny and the rate of return from credibly achievable projections justifies investment, they could get the money again, even now. But no one that I have heard or read over the past few years can explain the business plan adequately – that is, concretely. I would appreciate any insights or opinions on the topic. I believe these are smart people, in the company and among its investors, so I am sure it is there. I just don’t believe in the “we’ll figure out how to make money eventually” business plan in this case.
Some Freebase terms that are worth knowing but are commercially reasonable for any site that provides a free service include:
- The terms of service are subject to change (upon posting).
- The service may be changed or discontinued at any time and without notice.
- Limits concerning access to or use of the services may be established.
- Any disputes shall be heard in San Francisco and governed by California law.
In a recent post I mentioned comments by Sir Tim Berners-Lee concerning the overlap between enterprise information models and semantic web ontology supporting the concept of linked data. Sir Berners-Lee argued that overlap is already sufficient to have a transformative effect on mainstream IT. I think he is right, but also that we are not there yet. There are many obstacles to adoption, not the least of which is the inertia of enterprise IT. Disruptive approaches to software development typically require ten years or so to cross the chasm from visionary and early adopters to the mainstream. We are only a few years into this and the technology is not ready.
First, let’s establish that there is plenty of semantics available for reuse now. There are existing models, some of which are well-designed, mature, and widely used. Unfortunately, most of what exists has little apparent relevance to enterprises. There is little on this diagram that would draw the attention of an enterprise architect, for example.
As I discussed in Over $100m in 12 months backs natural language for the semantic web, Radar Networks’ Twine is one of the more interesting semantic web startups. Their founder, Nova Spivak, is funded by Vulcan and others to provide “interest-driven [social] networking”. I’ve been participating in the beta program at modest bandwidth for a while. Generally, Nova’s statements about where they are and where they are going are fully supported by what I have experienced. There are obvious weaknesses that they are improving. Overall, the strategy of gradually bootstrapping functionality and content by controlling the ramp up in users from a clearly alpha stage implementation to what is still not quite beta (in my view) seems perfect.
Recently, Nova recorded a few minute video in which he makes three short-term predictions: Continue reading “The Semantic Arms Race: Facebook vs. Google”