Our problem is not the lack of particle accelerators, but the lack of the organizational and funding processes associated with particle accelerators.
Mark Liberman disagrees:
However, I continue to believe that Patrick is addressing an important set of issues. As both Patrick and Fernando observe, the hardware that we need is not prohibitively expensive. But there remain significant problems with data access and with infrastructure design.
On the infrastructure side, let's suppose that we've got $X to spend on some combination of compute servers and file servers.. What should we do? Should we buy X/5000 $5K machines, or X/2000 $2K machines, or what? Should the disks be local or shared? How much memory does each machine need? What's the right way to connect them up? Should we dedicate a cluster to Hadoop and map/reduce, and set aside some other machines for problems that don't factor appropriately? Or should we plan to to use a single cluster in multiple ways? What's really required in the way of on-going software and hardware support for such a system?
These are issues that a mildly competent team with varied expertise can figure out if they have the resources to start with. The real problem is how to assemble and maintain such a team and infrastructure in an academic environment in which funding is unpredictable. I generally disagree with Field of Dreams "if you build it, they will come" projects. While we can all agree that some combination of compute and storage servers and distributed computing software can be very useful for large-scale machine learning and natural-language processing experiments, the best way to configure them depends on the specific projects that are attempted. Generic infrastructure hardware, software, and management efforts are not really good at anything in particular, and they have a way of sucking resources to perpetuate themselves independently of the science they claim to serve.
I'd rather see our field push for funding opportunities that pay attention in a balanced way to both the science and the needed infrastructure.