From my perspective in the trenches, the reduction is not as big as most people might think for CS and the sciences. If you worked like crazy while building your credentials, either for tenure or to a senior position in a non-tenure research track, you can't really slack off too much. You still need to bring in the cash to cover your team, grad student tuitions, and your own salary, which are now more expensive too. This means just as much research effort and proposal writing. This is exacerbated when research funding is cut at a large scale (sequestration). The reduction really comes from i) having established robust lab practices, methods, and management skills and ii) improved proposal writing skills combined with a track record. Junior faculty expend a lot of time finding and developing the right models, processes, and skills.

Another problem is that you spend your early career developing and reinforcing workaholic habits. It is very hard to step away from work, even for a regular weekend. Unlike most high intensity jobs, the flexible time is great for scheduling around family so they actually see you. You can insulate them from the worst of it.

Um, no. It has been in living rooms for over a decade. TiVo runs linux. Now get off my lawn!

V2V is peer-to-peer and really focused on reducing reaction times. It allows the car ahead to instantly tell the car behind it is braking. This means less latency for corrective action. This also helps non-autonomous cars since V2V equipped vehicles could, theoretically, suck up some of the shockwaves present in current highway driving.

The main advance is the progression towards real-world sensor selection and packaging. If you look at all the cars which completed the Urban Challenge, and the Google cars, you'll notice the spinning Velodyne laser sensor on the roof. It is a great sensor and makes autonomous driving much easier. Unfortunately, that sucker costs more than most luxury cars and would never be deployed the real-world since nobody wants a spinning can on their roof.

Carnegie Mellon would not have won the Urban Challenge without that sensor or the others littered all over the exterior of the car. The major advance for this new Carnegie Mellon car is comparable performance with cheaper sensors fully packaged within the car. This is a big deal since (a) economics limits which sensors you can buy and (b) the car body and shape limit the size and location of sensors. These obviously limit your overall sensing capability.

The new car also has better computer packaging. Most autonomous vehicles have no trunk space and frequently have no back seat room. For a historical perspective, Carnegie Mellon's Navlab 1, which found a spot and parallel parked autonomously in 1992, had racks of computers and an extra air conditioning system to handle the heat load. Urban Challenge vehicles also had racks in their trunk areas. The Cadillac SRX team was able to cram all the computational gear out of sight. This is really Moore's Law, etc but it is still a respectable achievement.

Actually, Google built the All-Star team from the Urban Grand Challenge. The Google group has lots of CMU (winner) and Stanford (2nd place) team members, including the technical lead from CMU.

It's not that simple. A lot of groundbreaking work is the result of side project within a larger research effort. Google is a good example of this. The ideas and approach had their origins in the NSF project Larry and Sergey were working on. While the SDLP project probably had an impact on digital libraries, the stated goal of the work, the larger impact was the creation of a technology behemoth with thousands of US jobs and a major influence on the digital economy. Using your model, would Google have happened? Probably not.

Also, the way you posed the question is interesting for other reasons. Whether a person changes their behavior is often based on far more than just basic science and technology advancements. Issues like federal policy (political science) can have a huge impact. For example, I'm working on technology research related to the aging of the population. This is a very real societal need and it is easy to justify the work from a financial perspective (take a look at nursing home and caregiver costs). However, many health and independence technologies are intertwined with privacy, whether Medicare will pay, and other non-technical issues. We rely on the insights of our colleagues doing research in the social sciences to help us understand the interplay between functionality and barriers to acceptance and commercialization. Without their research, we'd probably make very expensive paperweights.

Exactly. If the researchers didn't account for traveling behavior (i.e., check to see if the person was posting from their typical geographical region) then the results would be heavily skewed by vacations. Hawaii, Maine, Nevada, Utah and Vermont are all popular vacation locations.

It won't stop them, but it gives you the ability to get the plagiarized material pulled. Remember, plagiarism is antithetical to academia. Mashups are fine, as long as you give appropriate credit.

... which, of course already exists

I'm not so sure about that. PhD Comics broke down the FY 2009 budget. It's worth taking a look. $68B out of $3,518B, or about 19%. Now, having said this, there are impacts from government research funds that reach far beyond a large corporation research budget. Research can produce massive savings that last decades, grow whole new industries, or create entirely new "really large corporations" (Google came from an NSF grant). A typical corporate lab is not focused on problems that lead to societal-level savings or whole new fields. They lack the large-scale funds and are often constrained to the company's best interest. Government funded research generally covers a sector of the research map that companies avoid due to risk, long-term payback, or scale.

An important distinction is that Deaf Culture members are not speaking on behalf of all deaf people. There are many, many deaf and hard of hearing people who use cochlear implants and hearing aids. Most of this population were raised by hearing parents who opted for their child to grow up in their world, rather than the world of the DC-oriented state school for the deaf system. Since 90% of the children born deaf have hearing parents, it is not surprising that many of their parents choose an oral, mainstream route. If an insular community that spoke a different language told you that, because of a physical feature on your new baby, your child should grow up in a culture other than your own, would you? It is also hard to dissuade a hearing parent of a newborn when they see an older implanted kid talking and singing - the evidence is staring them in the face.

While some kids in the oral mainstream education path end up migrating away from technology for various reasons, most stay on this track and are very technology friendly. This isn't surprising given the outcomes. Extensive, longitudinal research shows the vast majority of children implanted with a CI in their first few years and enrolled in an oral school (e.g., Option Schools) are mainstreamed into regular classrooms by kindergarten/1st grade. Mainstreaming is a huge predictor of English reading literacy (ASL is not English), which as we all know, is important for many higher income employment opportunities. You don't hear about this population because most of them melt into society.

The advance mentioned in TFA is likely to receive the same attack the DC crowd is waging on cochlear implants. They claim deaf kids should make the decision for themselves. This is a smokescreen. Kids implanted after the early language development windows (pre-5) have a much harder time learning to understand and use the sound provided by the implant due to reduced brain plasticity. If they are much older, they are also less likely to be mainstreamed and therefore behind the curve on literacy. Therefore, it is not surprising kids who are "given a choice when they are older" would have poorer outcomes and are more likely to abandon technology.

Having said all this, many adult cochlear implant and hearing aid users are unlikely to opt for this advance. If they are like my wife, they are comfortable with their hearing loss, get good use out of their cochlear implant, and don't see a strong need to change. However, this advance would have a huge impact on newborns and kids still in the language development window.

I've seen OPT used properly and effectively for very talented foreign students. I've been around very good universities and I can confirm OPT is critical at keeping top-tier foreign students here in the US. The most common cases are (a) the summer grad school gap when changing schools and (b) a gap between graduation and an employment visa. The former may seem trivial, but it can allow a student to finish up a research project at University A before moving on to University B (e.g., undergrad to grad, MS to PhD, etc). Losing three months of an integrated, talented student has significant impact on a research project. For the latter, I've met numerous students who used OPT as key step towards gaining eventual permanent status.

Magnets are used to keep the internal and external antennas aligned for cochlear implants. CIs have been around for a while, so the community has learned some important lessons. First, you need to plan for magnet removal in the event of an emergency MRI. Most CI users don't get MRIs but sometimes there is a critical need. Therefore, newer implant models allow a qualified doctor to make a small incision, pop the magnet out without damaging the implant, and then put everything back after the MRI. This is extremely rare for obvious reasons.

Second, the magnet in the external component is usually tailored to the individual. The need for different strengths is due to magnet depth, hair, etc. There are several strength levels (e.g., high, medium, low) and you want one that will hold the coil tight, but not so tight that it leads to skin damage.

I'm fortunate enough to know some of the people on the team. They come from robotics backgrounds and are very experienced in highly reliable systems. For example, a big chunk of the Google team was hired out of the Carnegie Mellon Tartan Racing team. That team tested their systems so much that they wore out hardware. The Carnegie Mellon team also originates from the Field Robotics Center which sends robots to Antarctica, volcanoes, sinkhole lakes, the mountain deserts of Chile, and abandoned mines. These are hardened systems developed using hard core systems engineering and serious software engineering methods. Trust me, this is not a group of ivory tower AI people ignoring version control and using latest beta release of LISP. One of the technical leads, Chris Urmson gave a talk last year at Carnegie Mellon. It was apparent that they have continued these practices in Google. The incredible volume of field testing is the outward evidence.