From a computer science perspective, while it might sound easier to get a computer to understand something than a human I believe that "Artificial Intelligence" Phd's would argue that until the cows come home...

There are some things that appear complex and computers solve them very fast. Other things were considered very simple 20+ years ago and still haven't had much progress. Put simply, don't forget computers are 1's and 0's - the dumbest creation on the planet.

Given the wide reaching proposal that computers are in fact smarter than the average human we should be at a point where there are efficient Big 0 solvable algorithms for everything.

Sorry, don't mean to diverge. But when we're talking about human to computer versus computer to computer interaction then it should really be in the conversation. When we talk about computer to computer, of course we mean interoperability of programming solutions, including databases and data stores, etc etc etc. For us to move into a context aware computing paradigm it would be a requirement at some point to have computers talking to computers.

As long as we aren't looking in that direction we're really saying that our software will aim to work in unique or limited silos of interoperability.

Anyway, diverging again Adrian. Sorry. Naturally the whole web won't suddenly do this magic computer to computer inter-talking magic context thing all at once. There needs to still be mom and pop (and me) coding basic content. But software will get a lot out of that ability so big organisations with big apps would get a lot of advantage - web technologies in relation to service provisioning, etc etc. come to mind.

It would be very sad to see the ultimate goal of a "meaningful" web disappear because it doesn't appear attainable at the moment. This is still a young field and we're just getting up and running.

There's something extremely boring about a web paradigm that doesn't include my toilet taking medical stats to send to my health specialist etc.

In short, machines need a common language to communicate. The more complex we make either end of that conversation the more programming effort we're going to have to put in to interpretation. Some research on natural language understanding techniques and difficulties are worth investigating.

I think the human to computer vs computer to computer argument does sound logical on face value, but in science its probably not that true.