对比昆虫大脑，质疑大模型在机器人中的实用性
Are Transformers Truly Foundational for Robotics?
- 用昆虫大脑的高效性反衬GPT的高算力依赖
- 指出GPT在机器人应用中需巨大算力与训练成本
- 建议从生物智能中汲取设计启发
生成式预训练变换器（GPT）被寄予厚望，有望革新机器人技术。然而本文质疑其在自主机器人中的实际效用。当前基于GPT的机器人系统需要巨额且昂贵的计算资源、极长的训练时间，且常依赖离线无线控制。相比之下，微小的昆虫大脑却能在无需这些条件的情况下实现稳健的自主行为。本文由此提炼出可从生物智能中学习的经验，以提升GPT在机器人领域的实用价值。
原文摘要 · Abstract (English)
Generative Pre-Trained Transformers (GPTs) are hyped to revolutionize robotics. Here we question their utility. GPTs for autonomous robotics demand enormous and costly compute, excessive training times and (often) offboard wireless control. We contrast GPT state of the art with how tiny insect brains have achieved robust autonomy with none of these constraints. We highlight lessons that can be learned from biology to enhance the utility of GPTs in robotics.
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