You should promote this to a full answer rather than a comment! It more than qualifies.
Regarding 1, I suspect a lot of recent progress in neuroscience has come from applying computational and physics-style approaches to existing problems. See, for example, the success Ed Boyden has had in his lab with applying physics thinking to building better neuroscience tools–optogenetics, expansion microscopy, and most recently implosion fabrication.
I think nanotechnology is a prime example of 2. AIUI, a lot of the component technologies for at least trying to build nano-assemblers exist but we lack the technology/institutions/incentives/knowledge to engineer them into coherent products and tools.
I agree regarding neuroscience. I went to a presentation (from whom I have suddenly forgotten, and I seem to have lost my notes) that was describing an advanced type of fMRI that allowed more advanced inspection than previously, and the big discovery mostly consistent of “optimize the c++” and “rearrange the UI with practitioners in mind.” I found it tremendously impressive—they were using it to help map epilepsy seizures in much more detail.
I am strongly tempted to say that 2 should be considered the highest priority in any kind of advanced engineering project, and I am further tempted to say it would sometimes be worth considering even before having project goals. There has been some new work in systems engineering recently that emphasizes the meta level and focusing on architecture-space before even getting the design constraints; I wonder if the same trick could be pulled with capabilities. Sort of systematizing the constraints at the same time as the design.
You should promote this to a full answer rather than a comment! It more than qualifies.
Regarding 1, I suspect a lot of recent progress in neuroscience has come from applying computational and physics-style approaches to existing problems. See, for example, the success Ed Boyden has had in his lab with applying physics thinking to building better neuroscience tools–optogenetics, expansion microscopy, and most recently implosion fabrication.
I think nanotechnology is a prime example of 2. AIUI, a lot of the component technologies for at least trying to build nano-assemblers exist but we lack the technology/institutions/incentives/knowledge to engineer them into coherent products and tools.
Copied to full answer!
I agree regarding neuroscience. I went to a presentation (from whom I have suddenly forgotten, and I seem to have lost my notes) that was describing an advanced type of fMRI that allowed more advanced inspection than previously, and the big discovery mostly consistent of “optimize the c++” and “rearrange the UI with practitioners in mind.” I found it tremendously impressive—they were using it to help map epilepsy seizures in much more detail.
I am strongly tempted to say that 2 should be considered the highest priority in any kind of advanced engineering project, and I am further tempted to say it would sometimes be worth considering even before having project goals. There has been some new work in systems engineering recently that emphasizes the meta level and focusing on architecture-space before even getting the design constraints; I wonder if the same trick could be pulled with capabilities. Sort of systematizing the constraints at the same time as the design.