I would disagree with the statement that our algorithms are all domain-specific. Often some amount of domain-specific knowledge is needed to design a good algorithm, but it is often quite minimal. For instance, my office-mate is building a parser for interpreting natural language semantics, and has taken zero linguistics classes (but has picked up some amount of linguistics knowledge from talks, etc.). Of course, he's following in the footsteps of people who do know linguistics, but the point is just that the methods people use tend to be fairly general despite requiring task-specific tuning.

I agree, of course, that there are few systems that work across multiple domains, but I'm not sure that that's a fundamental issue so much as a symptom of broader issues that surface in this context (such as latent variables and complex features).