It would be helpful to run simulation algorithms with "tunable resolution" on supercomputers to see at what level the interesting properties appear. Though I have better hopes of seeing an answer to this question from the guys doing AI research than from a medical mega-research project or a collaboration... This is very different from the human genome project (where people alredy knew what information they needed and they put together resources to obtain it faster) that they try to imitate in the PR vids...
> Give the state of our knowledge, a massive publicly-funded project seems premature
One billion might sound like bucket loads of money, but it is not. There are close to 90 institutions involved and a huge percentage of the funding will need to go to the platforms that need to built. This is more about building the necessary infrastructure to do higher-impact research.
Of course you can... but I sincerely hope the PR video was inaccurate, because lumping together goals like: (1) small scale cell simulation for basic pharmacology research and, (2) better medical imaging for clinical purposes and (3) large scale simulation for really understanding how things work seems a recipe for confusion and badly allocating resources... yeah, it's a common goal, but the people doing this have very different expertise and are close to "not speaking the same language" in terms of the way they approach problems... an you'd have them competing among each other for funding instead of competing for funding in the overall "research market" and then, let's say, the guys doing low level simulation and more clinical oriented research win the big bucks over the guys interested in large-scale simulations and understanding.
I'm speaking out of my ass a little bit, but what I've learned from my contact with medical research is that the whole system is extremely ("criminally" I'd say...) "good" at mismanaging resources (hardware, smart people, money... everything), and the only hope to have "decent" resource utilization would be by letting small teams self-manage and compete for funding in the broadest "market" not just heir own area of study...
> And with no clear roadmap to guide priorities, that overhead won't provide any benefit
But that is one of the purported advantages of a flagship project. You do have a roadmap and a unifying goal that is provided by the project. Thus you can avoid different institutions performing the same research over and over without any concern to how this relates to previous results and other relevant areas. The difference is that the roadmap is provided by the project instead of the funding agency and as such there is more flexibility.
> building ambitious 'platforms'
To take one of the platforms as an example, the idea behind the brain simulation platform is to be able to aggregate scientific data collected one way or another (even outside the project) to build a simulation model. The more data collected the better the model. Then scientists can come and test their hypotheses or run scenarios. Based on the results the brain model may be adjusted. The way I see it, this will be an evolving tool that will facilitate basic research. I am not a neuroscientist so I can't really comment on whether this tool makes sense or not.