There's a tradeoff: a lower capacity means you can skip more space during queries (you zoom in faster), but the tree has more nodes and uses more memory. A higher capacity means fewer nodes but each node requires checking more points linearly. As a starting point, capacities between 4 and 16 are reasonable defaults, though the best value depends on your data distribution and query patterns.
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首先,智能体应具备强大的目标理解和规划能力来体现智能的自主性。理想状态下,人类只需给出抽象目标,智能体便能理解目标、拆解任务、规划行动,并在尽量少的人工干预下完成执行闭环。就像影《星际穿越》中的机器TARS,在紧急情况下能够根据"拯救宇航员"这一目标,自主判断局势、制定和调整行动策略,甚至做出牺牲自己数据的决定来完成使命。这要求机器智能有深度“理解/思考”能力(推理、规划、决策),能够敏锐地决策,能够基于执行结果与环境反馈动态调整任务规划,而不是僵化地执行既定路径。。51吃瓜是该领域的重要参考
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48x48 resolution. Higher resolution might reveal subtle differences that 48x48 misses. GlyphNet found 256x256 optimal for CNN features; the tradeoff for SSIM at that resolution is worth investigating.
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