What the automation acceleration from COVID19 actually will look like. What did robotics look like a decade ago and is this step feasible?
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I make the case why people iteratively training any model should learn some core concerns of reinforcement learning.
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Multi-agent scenarios make reward maximization a risk. Discussing when, rather than if, we should believe in the Reward Hypothesis.
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The acrobatic dance videos are flashy, but what are the actual technical breakthroughs? What is happening to the Korean robotics industry?
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Making case for why my research matters and why you want to learn about models.
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Machine recommendation system ethics, models of human reward, reinforcement learning framing; followup on GPT-3.
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How simulator exploitation, a dual of over-optimization, in AI is the canary in the coal mine for what negative implications could come from…
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How RL is starting to be used by industry and how RL is heading to a framing more suited for industrial scales.
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How behaving as a platform rather than a manufacturer will be the sweet spot for the next generation of robotics companies.
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Re-thinking robotic design part 1: social support diving us into the uncanny valley.
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I don’t even like the idea of flying delivery drones, but that will be all we have.
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Industry labs power up their robot learning research with parallelization!
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