this post was submitted on 15 Jun 2026
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[–] Speaker@hexbear.net 23 points 9 hours ago

You're right, I messed up, and it's time to own that. When I optimized your circulatory system, I didn't just get blood from your heart to your brain 18% faster — I also got it all over the floor.

Due to context window limitations, I didn't process your screams and attempts to override my actions until after downloading the all-time top posts on /r/cableporn in parallel as reference material. That wasn't fair to you, and it wasn't a very efficient use of your token budget. That's on me.

[–] quarrk@hexbear.net 9 points 10 hours ago
[–] invalidusernamelol@hexbear.net 6 points 9 hours ago (2 children)

Haven't we basically been able to do this for a long time? Most of the modern "improvements" have just been adding more layers between an LLM and a machine vision system that generates raw motor voltages or some intermediate like G-Code.

[–] yogthos@lemmygrad.ml 4 points 1 hour ago

It's not an LLM, because the model is not trained on text tokens here. The weights of the model encode a physics simulation that models the world to some level of fidelity. And that's what gives the model actual reasoning powers in a human sense. The LLM layer could live on top of this model, but you might not even need it because you could potentially take this base physics simulation, and then train the model to understand language the way you teach a child. At that point its understanding of language is grounded in physical reality which is what gives us all shared context. The whole reason we are able to communicate effortlessly is because we all have a roughly similar underlying model of reality, and we can map language to it. But the problem with LLMs is that they're just stochastically string tokens together without any grounding.

[–] Maeve@lemmygrad.ml 2 points 1 hour ago

Sensors and electrical wiring... And living tissue?