Or IBM-sized. But if you confined your ambitions to analyzing just meta-analyses, it would be much more doable. The narrower the domain, the better AI/NLP works, remember. There’s some remarkable examples of what you can do in machine-reading a narrow domain and extracting meaningful scientific data; one of them is ChemicalTagger (demo), reading chemistry papers describing synthesis processes and extracting the process (although it has serious problems getting papers to use). I bet you could get a lot out of reading meta-analyses—there’s a good summary just in the forest plot used in almost every meta-analysis.
Or IBM-sized. But if you confined your ambitions to analyzing just meta-analyses, it would be much more doable. The narrower the domain, the better AI/NLP works, remember. There’s some remarkable examples of what you can do in machine-reading a narrow domain and extracting meaningful scientific data; one of them is ChemicalTagger (demo), reading chemistry papers describing synthesis processes and extracting the process (although it has serious problems getting papers to use). I bet you could get a lot out of reading meta-analyses—there’s a good summary just in the forest plot used in almost every meta-analysis.