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A general “tell” of control strategies is beauty. The more elegant it looks, the more symmetry there is to the behavior. Which means many variables are being reduced to a few via symmetry-exploiting maneuvers.
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Contrast with the awkward flailing of trying to learn *any* workable functional behavior. Babies and injured pets often learn weird looking maneuvers this way. But more elegant looking ones are either strong attractors everybody will stumble into, or explicitly trained.
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Hardware — solved Basic control — solved Maneuver control — solved Localized deep learning: 2022 Deep learning entire behavior envelope from humans: 2024 Doing it without human training examples: 2026 Learning the unstable/high-risk bits in simulation: 2028 Akira entity: 2030
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My predictions regarding robotics advance is roughly similar timeline. Do you think independent self-funded research with cheap bots (spot knockoff, robotic arms) could be a valid alternative to big labs and academic path?
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that's what we're doing with the yak rover project... a bunch of us just building rovers with low-cost self-funded research. I've spend about $1000 in parts and tooling for mine so far...
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I'm at fork in the road so to speak. Leverage money from a well paying job towards funding this type of experiments. Or go for a research masters in germany, then figure things out by getting into their lab. I would really appreciate your thoughts here if any.
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My grad school experience is almost 20y ago, and conditions have changed, but there's still a lot of value to being around others in a campus environment with lots of serendipity. Online open collaboration is good in a complementary way. They're not substitutes really.
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Thanks! Value of serendipity in such spaces was precisely the question that was eating me up. I always knew it was big in back of my head. The either/or comes from full job +online/free-time robotics might be better because the money might help more towards the goal.
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