Re:Open Problems in Robotics
by R0b0t1 on Wednesday August 19, 2020 @10:33AM
(#24210759)
Robotics and embedded just doesn't make that much money. I had to turn down a job offer due to the seriously low counteroffer I was given. Or rather, I was given no counteroffer, just told to pound sand after the market rate I gave apparently insulted them.
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Re:Open Problems in Robotics
by tachyonbeam on Wednesday August 19, 2020 @11:18AM
(#24211244)
I think a big part of the issue here is that the robotic boom hasn't happened yet. There just isn't that much demand for robotics skills, and the market is not efficient.
If robotics and machine learning can progress to the point where household robotics or general-purpose robots become a thing, there will suddenly be an explosion in demand. Salaries for robotics experts will go through the roof, and all of a sudden, everyone will want to study robotics in school. This could take another 10-20 years to happen though!
If you count autonomous driving vehicles as robotics (I know it's a stretch), the funding (and therefore pay) story is a lot better, although you get the usual startup vs BigTech debate.
Source: I work in an ADV company.
The amount of money that's gone into that area without shipping a product is insane.
The potential upside for the company that gets it right is enormous. Billions of people are tired of wasting their time driving. Entire industries can be built on the technology if it works well.
That said it's a problem that steers awfully close to needing a full real AI and that's been a showstopper for loads of potential solutions for decades now.
My observation is that the industry ("we") as a whole is slowly but steadily making progress, without throwing our hands and say we need AGI. A big part of this comes from the upscaling of test fleets, which now generate data with enough quantity and variety that you can leverage the existing data tools to analyze and give developers precise and actionable feedback. While Tesla might seem like a popular punch bag in the ADV world, they are a big practitioner of this paradigm and did get good value out of it. That, and the trend of replacing more and more hand-crafted rules with fuzzy numerical models designed to "blend together" the rules (therefore retaining explainability).
In some cases you need to invest as risk mitigation. If someone else does self driving cars and proves that it is safer than human driven cars by a large margin yiy might find yourself out of the car business when governments mandate the technology and you can't afford the license.