General LLMs are rewriting robotics R&D, from code to benchtop experiments
A TMTPost analysis describes two ways general-purpose LLMs are entering robotics. On Oct 16, MicroFactory founder Igor Kulakov said a single customer deployment used Claude Opus and GPT-6 Astra to generate control plans and code while dedicated programs executed the work, running 1.5 hours of autonomous electronics assembly with zero errors (a company claim). Two days earlier, Poke & Wiggle let Claude Opus 5.5 handle the full loop of reading papers, writing algorithms, training models and running real-robot evaluations to reproduce 10 robotics papers; an agent integrated and trained Microsoft's ~5B-parameter open-weight dual-arm Rho model the next day, reaching 87% success on a screw-driving task, and once diagnosed and rolled back its own inference-code bug in under 35 minutes. The piece also recounts a DSD reproduction where the agent widened the action-normalization range, flattening DSD's edge (45.3% vs 46.0%); restoring the paper's parameters gave DSD 45.3% against a 32.0% baseline, a 13.3-point lead. The author concludes R&D and integration workflows are shifting, but the evidence does not show general LLMs broadly replacing VLA models.
If general models cut design and debugging costs, automation may become viable for more low-volume work, though real-time control still rests on VLA and dedicated programs.
（本文作者为 智讯智库，钛媒体经授权发布）
文 | 智讯智库分析师 陈宥文
这次，把机器人行业推到分叉路口的，是通用大模型这个“最熟悉的陌生人”——
有人拿它“替掉”VLA，有人拿它“加速”VLA。
短短两天，两桩标志性事件先后落地，把这条分叉路的两端踩得异常清晰。
10月16日，工业自动化初创公司MicroFactory创始人披露，据其自述，在单次客户部署项目中，团队采用通用大模型生成控制方案、专用程序执行作业的路线，整套系统基于Claude Opus、GPT-6 Astra等通用大模型搭建[1]——机器人连续1.5小时自主装配电子产品且全程零操作失误，覆盖的自动化范围超出团队最初预期[2]。
#Claude Opus 5.5#Claude Opus#GPT-6 Astra#MicroFactory#Poke & Wiggle#Anthropic#Microsoft#Rho