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EHeller comments on New report: Intelligence Explosion Microeconomics - Less Wrong
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It is my experience that many labs do in fact run all night, with researchers taking shifts baby sitting equipment and watching data roll in.
Well, those are the labs that don't have a blindingly obvious route to speedups just by speeding up the researchers, though de facto I'd expect it to work anyway up to a point.
When I wrote my thesis, a major limiting factor was the speed of the computers doing the analysis; I would start the latest variant of my program in the afternoon, and come back next morning to see what it reported. I'm currently working on software to take advantage of massively-parallel processors to speed up this process by a couple of orders of magnitude.
Next time, try shifting processing resources from your brain to the analytic computers until neither is waiting on the other!
Ahem
But then his brain will be too slow.
The difficulty of brain-computer interfaces is that the brain does not appear to work with any known executable format, making running anything on it something of a hit-and-miss affair.
Of course, he could solve this by simply increasing the precision of his computer calculations until it's the right speed for his brain...
Someone baby-sitting equipment is a technician, not a researcher, properly understood.
Not every part of research is glamorous, there is a lot of routine labor to do, and most of the time its the researchers (grad students or postdocs) doing it. The first lab I ever worked in, we spent about 3 months designing and building the experiment and almost a year straight of round-the-clock data collection, I suppose you could say we temporarily stopped being researchers and became technicians but that seems a bit odd. During one of my postdocs, a good 60% of my job was sys-admin type work to keep a cluster running, while waiting for code to run. My point is that the rate-limiting step in a lot of research is that experiments take time to perform, and code takes time to run. Most labs have experiments/code running round the clock.
I guess if you want to differentiate technician work from researcher work, you could do something non-standard and say that every postdoc/grad student in a lab is 30% sales (after all, begging for money isn't being a researcher, properly understood), 60% technician, 10% researcher.
The cluster of thingspace you're referring to can properly be called researchers (probably).
Just the same, if that were how the term were typically used -- for cases where the deep theoretical, high-inferential-distance understanding is vital for core job functions -- I would not feel the need to raise the point I did.
Rather, it's because people tend to inflate their own job descriptions, and my frequent observation of anyone working in lab-like environments being classified as a "researcher" or "doing research", regardless of how small the intellectual component of their contribution is, that I feel the need to point out the possible mis-labeling.
(A high-profile example of this mistake is Freeman Dyson's criticism of climate scientists for being too lazy to do the hard work of collecting data in extreme conditions, which is itself not the scientific component of the work. Start from:"It is much easier for a scientist to sit in an air-conditioned building..." )
"Baby-sitting equipment" is rather a condescending description of what a shift-taker at a particle physics experiment does. This being said, it must be admitted that the cheapness of grad-student labour is a factor in the staffing decisions, here.