Why robot inference companies must also deploy: moats differ from LLM serving
silver__tsuki · x · 2026-11-03
Responding to @varunnair's prediction that robot-fleet inference optimization and simulation-as-RL-environment will be the next big things in robotics, silvertsuki offers a counterpoint: unlike LLMs, robot models don't work out of the box — and once they do, why wouldn't existing large inference providers just serve them? A robotic inference company must, to some extent, deploy the robots itself; deployment capability is the real moat.
More from AGI Musings
- Students keep a secret doc of real work because a teammate keeps replacing it with AI slop — IanArawjo · 2026-11-03
- If alignment faking exists, could reverse stress testing reveal misalignment faking? — eigenron · 2026-11-03
- Audit picks the sycophant model 3/3 times, but "telling apart isn't explaining" — kevrussell · 2026-11-03
- The real Minecraft agent benchmark: can a kid have fun playing with it live? — akbirthko · 2026-11-03
- Andrew Ng's Batch Halloween issue: AI witch hunts and out-of-control agent fears — DeepLearningAI · 2026-11-03
- Bay Area machine shops field 5-10 calls a week from AI manufacturing startups — NYCounihan · 2026-11-03