The deeper impact of Uber’s hiring may be how it affects what ideas roboticists will pursue. After all, 20 years ago, if you wanted to push the frontiers of robotics, you had primarily abstract academic options to consider. But now that the field is booming, a faculty member or grad student with an ambitious idea has to ask questions: Where’s the best place to pursue my research — at a university, or in the corporate R.& D. lab at a place like Uber? What type of engineering work is so far out, so hard and so unsolved that it can only be done at a university?

Moore says there is still blue-sky work to be done in robotics. One example is the problem of ‘‘grasping.’’ Sure, wheeled robots can steer themselves through an Amazon shipping center pretty accurately; a self-driving car can trundle around San Francisco without running people over. But no robot can yet match the dexterity of a human hand. It can’t fluidly and confidently manipulate objects on a table — like picking up a coffee mug (assuming it can first identify it). This is, Moore notes, a huge research challenge in the humanitarian and health fields, because such robots could transform the lives of people with mobility issues, including both the elderly and people with spinal-cord injuries.

‘‘There’s maybe about one million people in the United States who, if they dropped their TV remote on the floor, just have to wait for a caregiver to come along and pick it up for them,’’ Moore says. Grasping is a classic early-stage technology, one that the Ubers of the world won’t spend any time developing because the payoffs are too far away. Moore says he also wants this research done in a university setting so the results will be published openly and benefit the world at large.

But given the lucrative payouts that come when Silicon Valley decides to invest in a field — compared with the evaporating federal funds for ‘‘basic’’ research — will there even be academics who want to do early-stage, public-minded work?

Based on my conversations at Carnegie Mellon, there are many such idealists left. One of them is Siddhartha Srinivasa, a leading expert on manipulation in the Robotics Institute who works on adding intelligence to robot limbs. Right now, someone with a spinal-cord injury can get a robot to pick up a spoon and use it to eat a meal. But the arm is so laborious to control that a single sip from a bowl takes fully 10 minutes. If Srinivasa succeeds, the arm will intuit a gesture (‘‘Feed me some soup’’) and complete the task on its own.

Srinivasa is 37, and after a decade at Carnegie Mellon is frequently approached by firms — ‘‘the Googles and Ubers and others of the world’’ — but he has yet to abandon academia. He says he doesn’t want to give up the intellectual freedom, the ability to do good for the world at large without worrying about profit. Still, he acknowledges industry’s attractions. It’s not just money; it’s also validation. Investors and customers paying for your work is proof that it truly works.

‘‘It’s like the Uber thing, right?’’ he says. ‘‘You can come up with a scheduling algorithm, but does it work when there are 50,000 people trying to do this? How does it scale? Does it work when somebody comes and pours grease over your robot arm? Like, I don’t know, and I want to know.’’ Last year, Srinivasa created his own part-time start-up in part to try to answer that question. The lab is still where ideas are born, but the market is now where they are put to the test.