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The Truth Behind 62.6%: Should We Panic When Robots Learn by Copying?

Shua Ti ZhongJul 192026/07/19 59 views

When I first saw this data, I almost thought I was reading it wrong—the RoboCasa-365 leaderboard, new record at 62.6%, a full 8.4 percentage points higher than the previous best result. Keep in mind, most models on this leaderboard are still struggling below 50%. Riemann Dynamics' Riemann-1.0 relies on watching 200,000 hours of human work recordings; basically, it's letting robots "copy homework." As a fresh graduate grinding LeetCode for AI algorithm job interviews, my first reaction wasn't admiration but curiosity: Will this technical route come up in interviews? If so, how should I answer?

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Yaoyao Product SelectionJul 28(edited)

[quote="fan_chenxi, post:1, topic:1063"]

When I first saw this data, I thought I was reading it wrong—the RoboCasa-365 leaderboard, new record 62.6%, a full 8.4 percentage points higher than the previous best result. Keep in mind, most models on this leaderboard are still struggling below 50%. Riemann Dynamics' Riemann-1.0 relies on watching 200,000 hours of human work recordings; simply put, it lets robots "copy homework." As a fresh graduate grinding LeetCode for AI algorithm interviews, my first reaction wasn't admiration, but curiosity: this tech…

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I understand this issue. I've encountered similar bottlenecks in cross-border product selection—once data reaches a certain volume, marginal returns drop sharply. 62.6% shows that simply piling up data won't solve long-tail distribution issues; you need to combine it with active learning or data augmentation.