华创资本合伙人陈欢：能落地、可应用且具备直接商业价值的机器人，是华创资本长期关注的赛道。觉物科技依托全球首创的模块化变形系统设计，其大载重全地形野外机器人平台已率先在农业场景实现规模化商业落地，超百万公里的实地打磨，充分印证了技术的可靠性与产品的场景适配能力。本轮融资将助力觉物科技加速全球化布局与新场景拓展，我们坚定看好觉物科技团队兼具硬核研发实力与扎实商业落地的能力，相信他们未来大有可为。
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There are a couple ways mitigate this drawback, both of which are outside the scope of this article. One is “garbage collection”: pruning tombstones from CRDTs, which prevents you from merging states with any changes made before the tombstones were removed. Another is creating an efficient format to encode the data. You can also combine these methods. Research suggests that this can result in as little as 50% overhead compared to the “plain” data CRDTs: The Hard Parts A talk on the latest research on CRDTs, originally given at the Hydra distributed computing conference on 6 July 2020.References: https://martin.kleppmann.co... youtu.be/x7drE24geUw?t=3587 . If you’d like to skip ahead and see some of this optimization in action, check out the final part in this series: Making CRDTs 98% More Efficient Making CRDTs 98% More Efficient | jakelazaroff.com State-based CRDTs grow monotonically, but that doesn't mean they can't be efficient. We'll learn how to compress the pixel editor state by 98%. jakelazaroff.com/words/making-crdts-98-percent-more-efficient/ . ↩
a signal to fix the confusing labeling by renaming or removing the